Digital Commons Network^™

Mucormycosis (Black Fungus) Maiming Covid Patients: Scientometrics Analysis Through Prism Of Biblioshiny, Sivankalai S, K Sivasekaran

Library Philosophy and Practice (e-journal)

This study analyses the global level outlook of research publications on Mucormycosis output between the period of 1923 to 2021 (May) on different limitations including contribution of authors, communication channel, publications on Institutions, countries, Journals, cited articles and mode of languages. 4451 data was downloaded from core collection of Web of Science bibliographic database using the search term ‘Mucormycosis’ and limited the publications 1900 to 2021, first publication was started in 1923 onwards. 3798 institutions and 8562 different disciplines contributed and 2808 records are in Articles. 4451 records published by 17320 authors and 23552 collaborated authors, documents per author are …

The Journal Of Information Science Theory And Practice (Jistap): A Bibliometric Analysis (2017-2020), Oladotun Ayowumi Osunkentan, Amudat Oyinlade Imam, Kamorudeen Wumi Adeleke, Taiwo Mujidat Eyinade

Library Philosophy and Practice (e-journal)

No abstract provided.

Electricity Generation Utilising Solar Energy: A Bibliometric Review And Prospects For Future Research, Ayushi Kamboj, Harikrishnan R

Library Philosophy and Practice (e-journal)

Anthropogenic global warming, deforestation, and resource depletion have been probably the most important challenges affecting the planet today. To address problems, we'll need to make significant modifications to our power connectivity. The author of this paper demonstrates the effectiveness of using sunlight, a green energy source, whose goal is to provide global power for all applications (electricity, transport infrastructure, heat pumps, and several others). As a consequence, energy is important to both the global economy and everyday life. Notwithstanding the increasing demand and productivity, the electrical power grid has held constant throughout the last 20 years. However, the implementation and …

An Empirical Study Of Awareness And Use Of Ict By School Teachers Before And During Lockdown Due To Covid-19 Pandemic, Pooja P. Dadhe, Shraddha M. Patil

Library Philosophy and Practice (e-journal)

The COVID-19 pandemic has taken almost all the countries across the globe by surprise. It was this time a year ago when the sudden outbreak of the coronavirus forced the closure of educational institutions resulting billions of children out of the classroom. Like many countries worldwide, India also faced the challenges of unexpectedly switching to online classes. Given to this background the study aims at understanding the practical experiences of teachers who were part of the teaching which undertook remotely and on digital platforms. This is a quantitative research using survey technique through a questionnaire that comprised demographic variables, ICT …

Socio-Cultural And Economic Factors As Correlate Of Academic Performance Of Undergraduates In The Department Of Library And Information Science Benue State University, Makurdi, Tofi Simon Ternenge, Tamen Timothy Torkuma

Library Philosophy and Practice (e-journal)

ABSTRACT

The study investigated socio-cultural and economic factors as correlate of academic performance of undergraduates in the department of Library and Information Science, Benue State University, Makurdi. Three (3) research questions were raised in line with the objectives of the study. The study adopted correlation research design, the population of the study was 951 undergraduates in the department of Library and Information Science Benue State University, Makurdi from 2019/2020 session. However, a sample sized of 282 using proportionate stratified random sampling method, simple random sampling and Taro Yamene’s formula was used to determine the sample size from the population. The …

Circularly Polarised Reconfigurable Antenna In 5g Application:A Bibliometric Study Using Scopus Database, Urja Ingle, Vaishnavee Chaurasia, Megha Basu, Chiranjivi Arjun, Sanjeev Kumar, Priyanka Tupe-Waghmare

Library Philosophy and Practice (e-journal)

The field of wireless technology has come a long way from connecting humans to humans, human to machines and now machines to machines. The boom in the wireless communication and increased number of systems used in latest wireless and radar applications creates the need for reconfigurable antennas. This paper presents an analysis of a circularly polarized reconfigurable antenna for 5G applications. The activation mechanisms, design and ways to optimize the operation of reconfigurable antennas are discussed. With the world moving towards 5G, which expects its reach in remote areas as well, the circular polarization patch antennas are well suited for …

Bibliometric Analysis On Optimal Path Planning For Robots, Varad Sandeep Nerlekar, Tathaagat Nihar Mamtura, Nishant Singh, Suket Anand, Sushma Parihar

Library Philosophy and Practice (e-journal)

Traversing from a given point to another while avoiding collision with obstacles is one of the key goals of path planning for robots [1]. Doing so in the most optimal way - the minimum total distance traveled by the robot is the objective of our study [2,3]. To do so, the algorithms implemented on the robots need to constantly map the environment or workspace in real time and subsequently create paths for the traversal in the environment without colliding with objects or obstacles [4,5]. Throughout the years, many researchers have conducted their own studies, researches and have proposed approaches for …

Measuring The Impact Of Ict On Students’ Academic Performances: Evidence From Higher Educational Institutions Of The Remote Areas Of Pakistan, Shahzadi Humbhi, Shabbir Tareen

Library Philosophy and Practice (e-journal)

The main purpose of this paper is to investigate students’ perceptions and attitudes towards the usage of ICT and its challenges in the higher educational institutions of Balochistan. A convenient sampling method was used to select 420 students from the top 6 higher educational institutions of Balochistan. Moreover, a Lickert-based closed-ended questionnaire was used for data collection purposes. The collected data were analyzed in SPSS Software. The results showed that 150 (39.5%) respondents were using ICT for academic events and 142 (37.4%) respondents were using ICT for their assignment completion. Furthermore, the study also highlighted some major challenges preventing students …

Attitude, Anxiety, And Technostress As A Correlate Of The Use Of Mobile Phones By Undergraduate Students In A Delta State University (Delsu), Abraka, Marcus L. Isebe

Library Philosophy and Practice (e-journal)

This study assessed attitude, anxiety, and technostress as a correlate of the use of mobile phones by undergraduate students in Delta State University (DELSU), Abraka. The total population for this study was 6,675 undergraduate students registered with the library of Delta State University in the 2019/2020 academic session. The instrument used for data collection was a structured questionnaire which was designed in print formats. A total number of 1001 copies of the questionnaire were distributed to the respondents with the aid of 5 research assistant and a total of 797 questionnaires was duly completed and found usable for the study. …

Differential Gene Expression Analysis Of Mice Thymi After Spaceflight, Roshani Codipilly

Master's Projects

With increases in space travel and a desire to inhabit the moon and Mars comes a pressing need to understand the impact of spaceflight on the body. Some effects are already known, such as reduced cardiac function and bone loss, but one area that needs to be further explored is the immune system. Differential gene expression analysis of mice thymi was performed to determine the impact of spaceflight on the immune system. The dataset that was analyzed, GLDS-289, was obtained from GeneLab, a space-omics database developed by NASA. Differential gene expression analysis was accomplished using a Nextflow implementation of GeneLab’s …

Clickbait Detection In Youtube Videos, Ruchira Gothankar

Master's Projects

YouTube videos often include captivating descriptions and intriguing thumbnails designed to increase the number of views, and thereby increase the revenue for the person who posted the video. This creates an incentive for people to post clickbait videos, in which the content might deviate significantly from the title, description, or thumbnail. In effect, users are tricked into clicking on clickbait videos. In this research, we consider the challenging problem of detecting clickbait YouTube videos. We experiment with logistic regression, random forests, and multilayer perceptrons, based on a variety of textual features. We obtain a maximum accuracy in excess of 94%.

Spaceflight And The Differential Gene Expression Of Human Stem Cell-Derived Cardiomyocytes, Eugenie Zhu

Master's Projects

The National Aeronautics and Space Administration (NASA) has performed many experiments on the International Space Station (ISS) to further understand how conditions in space can affect life on Earth. This project analyzed GLDS-258, a gene set from NASA’s GeneLab repository which examines the impact of microgravity on human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs). While many datasets have been run through NASA’s RNA-Seq Consensus Pipeline (RCP) to study differential gene expression in space, a Homo sapiens dataset has yet to be analyzed using the RCP. The aim of this project was to run the first Homo sapiens dataset, GLDS-258, through the …

Prediction Of Financial Capacity Using Diffusion Compartment Imaging, Lok Yi Tai

Master's Projects

Financial Capacity (FC) is the ability to manage one’s financial affairs, which is essential for autonomy and independence particularly for aging adults. Since dementia develops gradually, it is often difficult to detect the early signs that this cognitive dysfunction is developing This project aims to use Neurite orientation dispersion and density imaging (NODDI) to identify the white matter tracts that are associated with FC. Diffusion Tensor Images (DTI) and T1 Magnetic Resonance Images (MRI) of 18 Alzheimer’s Disease (AD) subjects, 47 Mild Cognitive Impaired (MCI) subjects, and 193 healthy control (CN) are compared to neuropsychological tests. Orientation Dispersion Index (ODI) …

Tolkien: Scholar And Modern Game Pioneer, Alicia Breinke

ART 108: Introduction to Games Studies

History can be a necessity, or necessary evil for some people when we want to comprehend real-time issues or trends. Gaming is a trend that applies to this since we often seem to be drawn in by the excitement of the graphics, music, and storylines, yet it seems like people seldomly try to uncover their origins. At the same time, though, a game’s historic foundation is essential to understand since it can help us gain a greater appreciation for these experiences. Role play games are an exceptional example of this since many renowned ones have external influences. J.R.R. Tolkien’s “The …

Hidden Markov Model-Based Clustering For Malware Classification, Shamli Singh

Master's Projects

Automated techniques to classify malware samples into their respective families are critical in cybersecurity. Previously research applied ��-means clustering to scores generated by hidden Markov models (HMM) as a means of dealing with the malware classification problem. In this research, we follow a somewhat similar approach, but instead of using HMMs to generate scores, we directly cluster the HMMs themselves. We obtain good results on a challenging malware dataset.

Keystroke Dynamics For User Authentication With Fixed And Free Text, Jianwei Li

Master's Projects

YouTube videos often include captivating descriptions and intriguing thumbnails designed to increase the number of views, and thereby increase the revenue for the person who posted the video. This creates an incentive for people to post clickbait videos, in which the content might deviate significantly from the title, description, or thumbnail. In effect, users are tricked into clicking on clickbait videos. In this research, we consider the challenging problem of detecting clickbait YouTube videos. We experiment with multiple state of the art machine learning techniques and a variety of textual features.

Cyberbullying Classification Based On Social Network Analysis, Anqi Wang

Master's Projects

With the popularity of social media platforms such as Facebook, Twitter, and Instagram, people widely share their opinions and comments over the Internet. Exten- sive use of social media has also caused a lot of problems. A representative problem is Cyberbullying, which is a serious social problem, mostly among teenagers. Cyber- bullying occurs when a social media user posts aggressive words or phrases to harass other users, and that leads to negatively affects on their mental and social well-being. Additionally, it may ruin the reputation of that media. We are considering the problem of detecting posts that are aggressive. Moreover, …

Wildfire Risk Prediction For A Smart City, Rekha Rani

Master's Projects

Wildfires are uncontrolled fires that may lead to the destruction of biodiversity, soil fertility, and human resources. There is a need for timely detection and prediction of wildfires to minimize their disastrous effects. In this research, we propose a wildfire prediction model that relies on multi-criteria decision making (MCDM) to explicitly evaluates multiple conflicting criteria in decision making and weave the wildfire risks into the city’s resiliency plan. We incorporate fuzzy set theory to handle imprecision and uncertainties. In the process, we create a new data set that includes California cities’ weather, vegetation, topography, and population density records. The model …

Image-Based Real Estate Appraisal Using Cnns And Ensemble Learning, Prathamesh Dnyanesh Kumkar

Master's Projects

Real Estate Appraisal is performed to evaluate properties during a range of activities like buying, selling, mortgaging, or insuring. Traditionally, this process is done by real estate brokers who consider factors like the location of a house, its area, the number of bedrooms and bathrooms, along with other amenities to assess the property. This approach is quite subjective since different brokers may arrive at a different quote for the same property depending on their analysis. The development in machine learning algorithms has given rise to several Automated Valuation Models (AVMs) to estimate real estate prices. Real estate websites use such …

Fake Malware Classification With Cnn Via Image Conversion: A Game Theory Approach, Yash Sahasrabuddhe

Master's Projects

Improvements in malware detection techniques have grown significantly over the past decade. These improvements have resulted in better security for systems from various forms of malware attacks. However, it is also the reason for continuous evolution of malware which makes it harder for current security mechanisms to detect them. Hence, there is a need to understand different malwares and study classification techniques using the ever-evolving field of machine learning. The goal of this research project is to identify similarities between malware families and to improve on classification of malwares within different malware families by implementing Convolutional Neural Networks (CNNs) on …

Malware Classification With Bert, Joel Lawrence Alvares

Master's Projects

Malware Classification is used to distinguish unique types of malware from each other.

This project aims to carry out malware classification using word embeddings which are used in Natural Language Processing (NLP) to identify and evaluate the relationship between words of a sentence. Word embeddings generated by BERT and Word2Vec for malware samples to carry out multi-class classification. BERT is a transformer based pre- trained natural language processing (NLP) model which can be used for a wide range of tasks such as question answering, paraphrase generation and next sentence prediction. However, the attention mechanism of a pre-trained BERT model can …

Presentation Attack Detection In Facial Biometric Authentication, Hardik Kumar

Master's Projects

Biometric systems are referred to those structures that enable recognizing an individual, or specifically a characteristic, using biometric data and mathematical algorithms. These are known to be widely employed in various organizations and companies, mostly as authentication systems. Biometric authentic systems are usually much more secure than a classic one, however they also have some loopholes. Presentation attacks indicate those attacks which spoof the biometric systems or sensors. The presentation attacks covered in this project are: photo attacks and deepfake attacks. In the case of photo attacks, it is observed that interactive action check like Eye Blinking proves efficient in …

Keystroke Dynamics Based On Machine Learning, Han-Chih Chang

Master's Projects

The development of active and passive biometric authentication and identification technology plays an increasingly important role in cybersecurity. Biometrics that utilize features derived from keystroke dynamics have been studied in this context. Keystroke dynamics can be used to analyze the way that a user types by monitoring various keyboard inputs. Previous work has considered the feasibility of user authentication and classification based on keystroke features. In this research, we analyze a wide variety of machine learning and deep learning models based on keystroke-derived features, we optimize the resulting models, and we compare our results to those obtained in related research. …

Fake Malware Opcodes Generation Using Hmm And Different Gan Algorithms, Harshit Trehan

Master's Projects

Malware, or malicious software, is a program that is intended to harm systems. In the past decade, the number of malware attacks have grown and, more importantly, evolved. Many researchers have successfully integrated cutting edge Machine Learning techniques to combat this ever present and growing threat to cyber and information security. One big challenge faced by many researchers is the lack of enough data to train machine learning models and specifically deep neural networks properly. Generative modelling has proven to be very efficient at generating synthesized data that can match the actual data distribution.

In this project, we aim to …

Machine Learning To Detect Malware Evolution, Lolitha Sresta Tupadha

Master's Projects

Malware evolves over time and anti-virus must adapt to such evolution. Hence, it is critical to detect those points in time where malware has evolved so that appro-priate countermeasures can be undertaken. In this research, we perform a variety of experiments to determine when malware evolution is likely to have occurred. All of the evolution detection techniques that we consider are based on machine learning and can be fully automated—in particular, no reverse engineering or other labor-intensive manual analysis is required. Specifically, we consider analysis based on hidden Markov models and various word embedding techniques, among other machine learning based …

Malware Analysis With Auxiliary-Classifier Gan, Rakesh Nagaraju

Master's Projects

A generative adversarial network (GAN) is a powerful machine learning concept where both a generative and discriminative model are trained simultaneously. A recent trend in malware research consists of treating executables as images and employing image-based analysis techniques. In this research, we generate fake malware images using GANs, and we also consider the effectiveness of GANs for malware classification. Specifically, we consider auxiliary classifier GAN (AC-GAN), which enables us to work with multiclass data. We find that AC-GAN generates malware images that cannot be reliably distinguished from real malware images. In addition, we find that the detection capabilities of AC-GAN …

Data Augmentation With Malware As Images, Aditi Walia

Master's Projects

Machine learning and deep learning techniques for malware detection and classifi- cation play an important role in the mitigation of cybersecurity threats. However, such techniques are often limited by a lack of data. Previous research has shown promising classification results by treating malware executables as images. In this research, we consider data augmentation using noise addition, geometric transforma- tions, and Auxiliary Classifier Generative Adversarial Networks (AC-GAN) for data augmentation of malware images. We train convolution neural networks (CNN) to verify that our generated images accurately model the original malware samples.

Higher-Order Link Prediction Using Node And Subgraph Embeddings, Kalpnil Anjan

Master's Projects

Social media, academia collaborations, e-commerce websites, biological structures, and other real-world networks are modeled as graphs to represent their entities and relationships in an abstract way. Such graphs are becoming more complex and informative, and by analyzing them we can solve various problems and find hidden insights. Some applications include predicting relationships and potential links between nodes, classifying nodes, and finding the most influential nodes in the graph, etc.

A large amount of research is being done in the field of predicting links between two nodes. However, predicting a future relationship among three or more nodes in a graph is …

Overlapping Community Detection In Social Networks, Akshar Panchal

Master's Projects

Social networking sites are important to connect with the world virtually. As the number of users accessing these sites increase, the data and information keeps on increasing. There are communities and groups which are formed virtually based on different factors. We can visualize these communities as networks of users or nodes and the relationships or connections between them as edges. This helps in evaluating and analyzing different factors that influence community formation in such a dense network. Community detection helps in revealing certain characteristics which makes these groups in the network unique and different from one another. We can use …

Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta

Master's Projects

Earlier researches have showed that the spread of fake news through social media can have a huge impact to society and also to individuals in an extremely negative way. In this work we aim to study the spread of fake news compared to real news in a social network. We do that by performing classical social network analysis to discover various characteristics, and formulate the problem as a binary classification, where we have graphs modeling the spread of fake and real news. For our experiments we rely on how news are propagated through a popular social media services such as …