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Sjsu Erfa News, Summer 2020, San Jose State University, Emeritus And Retired Faculty Association

Emeritus and Retired Faculty Association (ERFA) Newsletter

Volume 33, Number 4

Scientometric Portrait Of Nobel Laureate Venkatraman Ramakrishnan, Manoj Kumar Sa, Nirmalendu Panda

Library Philosophy and Practice (e-journal)

The study presents an analysis of 165 research papers by Nobel Laureate Venkatraman Ramakrishnan published during 1977 to 2019 in the diverse field of science such as Biochemistry, Genetics and Molecular Biology, Medicine, Chemistry, Neuroscience, Immunology and Microbiology, Physics and Astronomy, Engineering and Materials Science. The highest number of publications contributed during the 2^nd and 4^th decade with 49 (29.70%) papers each. His paper entitles “Structure of the 30s ribosomal subunit” got maximum 1560 citations. Kelley, A. C. Was the most collaborative author and Europe was the most dominant continent collaborating with 132 papers whereas the United States …

Comparing Students' Solutions To An Open-Ended Problem In An Introductory Programming Course With And Without Explicit Modeling Interventions, Kelsey Joy Rodgers, Matthew A. Verleger, Farshid Marbouti

Faculty Research, Scholarly, and Creative Activity

Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students' solutions to a complex, open-ended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in …

Change In Student Understanding Of Modeling During First Year Engineering Courses, Farshid Marbouti, Kelsey Joy Rodgers, Matthew A. Verleger

Faculty Research, Scholarly, and Creative Activity

All engineers must be able to apply and create models to be effective problem solvers, critical thinkers, and innovative designers. To be more successful in their studies and careers, students need a foundational knowledge about models. An adaptable approach can help students develop their modeling skills across a variety of modeling types, including physical models, mathematical models, logical models, and computational models. Physical models (e.g., prototypes) are the most common type of models that engineering students identify and discuss during the design process. There is a need to explicitly focus on varying types of models, model application, and model development …

Trends In Annual Seminar Papers Of Ahmedabad Library Network: A Bibliometric Analysis, Shanti P Chaudhari, Atul Bhatt, Shishirkumar H. Mandalia

Library Philosophy and Practice (e-journal)

A Bibliometric Study of Communications Published in Journal of Informetrics from 2012 to 2016. This research study demonstrates a bibliometric study of scholarly communication published by Ahmedabad Library Network (ADINET) in proceedings of annual conference (seminar). ADINET celebrates Librarian’s Day every year to commemorate the birthday of Dr. S R Ranganathan by organizing seminar in Gujarat, a leading state of India. This bibliometric study is intended to bring out the results of seminar proceedings published by ADINET from 2005 to 2019. This study investigated 176 papers published in Proceedings of ADINET seminar during 15 years. Study revealed that most of …

Patterns Of Authorship And Scientific Collaboration In Education: The Production Of Colombia In Esci, Alexander Maz-Machado, Bibiana Muñoz-Ñungo, David Gutiérrez-Rubio, Carmen León-Mantero

Library Philosophy and Practice (e-journal)

This paper aims to carry out a bibliometric study on the scientific production on Education that occurs in Colombia and it is indexed in the Emerging Sources Citation Index (ESCI) database. To carry out this study, the data related to the documents indexed in the ESCI database of WoS were downloaded and, by counting frequencies, the patterns of document production by journal and by year, the most productive institutions, the indicators of collaboration in authorship and the type of collaboration were identified. An increase in co-authorship and collaboration rates, as well as in international collaboration was detected for the examined …

Scientometric Analysis Of Nanotechnology Research With Special Reference To India (2008-17), Banasri Deka, Tilak Hazarika

Library Philosophy and Practice (e-journal)

Nanotechnology research covered in the Web of Science database during the period 2008-17 has been analyzed. A total of 16935 articles were retrieved and this forms the basis of this study. The growth of the article over the study window is 123 articles per year. 2017 is the most productive year with 2220 (13%, approx) articles. Journals and authors' productivity are analyzed based on their h-index and z-index. Among the 30 top productive journals taken for the study, ACS Nano is occupying the top position with 400 articles. The paired t-test showed a strong and significant correlation of h-index and …

Citation Analysis Of Doctoral Theses Submitted To The Department Of Library And Information Science, Gauhati University (2011-2017), Banasri Deka, Jitu Das

Library Philosophy and Practice (e-journal)

The present study is done by collecting and analyzing the references from the thirty theses submitted to the Department of Library and Information Science, Gauhati University in between 2011 to 2017. The year-wise distribution of theses is tabulated. From the 30 theses, 3684 citations have been retrieved where journals are found to be the most preferable source material followed by books and conference proceedings. Among the top 40 highly cited journals, 18 journals are from the UK followed by 14 from India. DESIDOC Journal of Library & Information Technology is on top rank with 72 citations. The citation half-life of …

Development Of Reduced Chemical Kinetic Models For The Numerical Simulation Of Combustion And Emissions Behavior Of Representative Conventional And Bio-Derived Fuels, Mazen A. Eldeeb

Mineta Transportation Institute

The study addresses two of the main challenges facing combustion modeling for transportation fuels: simultaneous simulation of non-related combustion problems and reducing the computational cost of the modeling process itself. To address the first challenge, researchers determine a characteristic flame time from thermal diffusivity and laminar burning velocity. Researchers examine parametric dependence of flame time and ignition delay time on pressure, temperature and equivalence ratio for methane, based on validated chemical kinetic mechanisms. The study reveals flame time and ignition delay time show similar temperature dependence, flame time has stronger dependence on equivalence ratio and weaker dependence on pressure than …

A Trend Analysis Of The Doctoral Dissertations In Lis Research In West Bengal, India During 1979-2018, Kaustuv Chakrabarti, Dhiman Mondal, Arabinda Maity Dr.

Library Philosophy and Practice (e-journal)

The present analytical study demonstrates the present status and trend of doctoral research in Library and Information science (LIS) discipline in the Universities of West Bengal. For this purpose, the primary data have been collected from the Central Library and LIS Schools of the respective Universities. Total 230 Ph.D. theses have been awarded in LIS discipline from West Bengal for 40 years period from 1979 to 2018. The bibliographical details of the theses have been interpreted using different parameters like university, year, researcher’s gender, supervisor’s gender, supervision pattern, active supervisor, language and subject. A steady development has been observed till …

Developing The Delta: Capturing Cultural Changes In Undergraduate Departments, Courtney Ngai, Mary E. Pilgrim, Daniel L. Reinholz, Joel C. Corbo, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

Departments are now recognized as an important locus for sustainable change on university campuses. Making sustainable changes typically requires a shift in culture, but culture is complex and difficult to measure. For this reason, cultural changes are often studied using qualitative methods that provide rich, detailed data. However, this imposes barriers to measuring culture and studying change at scale (i.e., across many departments). To address this issue, we introduce the Departmental Education and Leadership Transformation Assessment (DELTA), a new survey aimed at capturing cultural changes in undergraduate departments. We describe the survey’s development and validation and provide sugges-tions for its …

Assessing Complete Street Strategies Using Microscopic Traffic Simulation Models, Bernice Liu, Alireza Shams, Jonathan Howard, Serena Alexander, Alex Hughes, Anurag Pande

Mineta Transportation Institute

Authors of this research developed a traffic simulation model for the downtown San Jose network and evaluated five different street redesign and travel demand combinations. This model aids understanding of network-wide effects of changes in street design for local and regional agencies who are interested in implementing complete streets and/or one-way to two-way conversion. The base network may be altered to model and evaluate other complete streets (e.g., road diet) and tactical urbanism (e.g., farmer’s market on city streets on certain days of the week) scenarios. The 3-dimensional animated videos for each scenario are also created to be used for …

Colloquium: Bell's Theorem And Locally Mediated Reformulations Of Quantum Mechanics, K. B. Wharton, N. Argaman

Faculty Research, Scholarly, and Creative Activity

Bell's theorem rules out many potential reformulations of quantum mechanics, but within a generalized framework it does not exclude all locally mediated models. Such models describe the correlations between entangled particles as mediated by intermediate parameters that track the particle worldlines and respect Lorentz covariance. These locally mediated models require the relaxation of an arrow-of-time assumption that is typically taken for granted. Specifically, some of the mediating parameters in these models must functionally depend on measurement settings in their future, i.e., on input parameters associated with later times. This option, often called retrocausal, has been repeatedly pointed out in the …

Virtual Try-On With Generative Adversarial Networks: A Taxonomical Survey, Andrew Jong, Melody Moh, Teng Sheng Moh

Faculty Research, Scholarly, and Creative Activity

This chapter elaborates on using generative adversarial networks (GAN) for virtual try-on applications. It presents the first comprehensive survey on this topic. Virtual try-on represents a practical application of GANs and pixel translation, which improves on the techniques of virtual try-on prior to these new discoveries. This survey details the importance of virtual try-on systems and the history of virtual try-on; shows how GANs, pixel translation, and perceptual losses have influenced the field; and summarizes the latest research in creating virtual try-on systems. Additionally, the authors present the future directions of research to improve virtual try-on systems by making them …

Aerosol Indirect Effects On Cirrus Clouds Based On Global Aircraft Observations, Ryan Patnaude, Minghui Diao

Faculty Research, Scholarly, and Creative Activity

Cirrus clouds have large climate impacts, yet aerosol indirect effects on cirrus microphysical properties remain highly uncertain. There is a lack of observational analysis on thermodynamic, dynamical, and aerosol indirect effects simultaneously, which limits the quantification of each effect. Using seven National Science Foundation aircraft campaigns, impacts of temperature, relative humidity, vertical velocity, and aerosols are individually quantified. Nonmonotonic correlations of ice water content, ice crystal number concentration (Ni), and mean diameter (Di) with respect to aerosol number concentrations (Na) are consistently seen at various conditions. Positive correlations become significant when Na > 500 nm (Na500) and >100 nm (Na100) are …

Evidence-Based Detection Of Pancreatic Canc, Rajeshwari Deepak Chandratre

Master's Projects

This study is an effort to develop a tool for early detection of pancreatic cancer using evidential reasoning. An evidential reasoning model predicts the likelihood of an individual developing pancreatic cancer by processing the outputs of a Support Vector Classifier, and other input factors such as smoking history, drinking history, sequencing reads, biopsy location, family and personal health history. Certain features of the genomic data along with the mutated gene sequence of pancreatic cancer patients was obtained from the National Cancer Institute (NIH) Genomic Data Commons (GDC). This data was used to train the SVC. A prediction accuracy of ~85% …

Predicting Students’ Performance By Learning Analytics, Sandeep Subhash Madnaik

Master's Projects

The field of Learning Analytics (LA) has many applications in today’s technology and online driven education. Learning Analytics is a multidisciplinary topic for learn- ing purposes that uses machine learning, statistic, and visualization techniques [1]. We can harness academic performance data of various components in a course, along with the data background of each student (learner), and other features that might affect his/her academic performance. This collected data then can be fed to a sys- tem with the task to predict the final academic performance of the student, e.g., the final grade. Moreover, it allows students to monitor and self-assess …

Using Machine Learning To Optimize Predictive Models Used For Big Data Analytics In Various Sports Events, Akhil Kumar Gour

Master's Projects

In today’s world, data is growing in huge volume and type day by day. Historical data can hence be leveraged to predict the likelihood of the events which are to occur in the future. This process of using statistical or any other form of data to predict future outcomes is commonly termed as predictive modelling. Predictive modelling is becoming more and more important and is trending because of several reasons. But mainly, it enables businesses or individual users to gain accurate insights and allows to decide suitable actions for a profitable outcome.

Machine learning techniques are generally used in order …

Detection Of Mild Cognitive Impairment Using Diffusion Compartment Imaging, Matthew Jones

Master's Projects

The result of applying the Neurite Orientation Density and Dispersion Index (NODDI) algorithm to improve the prediction accuracy for patients diagnosed with MCI is reported. Calculations were carried out using a collection of 68 patients (34 control and 34 with MCI) gathered from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI). Patient data includes the use of high-resolution Magnetic Resonance Images as with as Diffusion Tensor Imaging. A Linear Regression accuracy of 83% was observed using the added NODDI summary statistic: Orientation Dispersion Index (ODI). A statistically significant difference in groups was found between control patients and patients with MCI with …

Pattern Analysis And Prediction Of Mild Cognitive Impairment Using The Conn Toolbox, Meenakshi Anbukkarasu

Master's Projects

Alzheimer's is an irreversible neurodegenerative disorder described by dynamic psychological and memory defalcation. It has been accounted for that the pervasiveness of Alzheimer's is to increase by 4 times in a few years, where one in every 75 people will have this disorder. Hence, there is a critical requirement for the analysis of Alzheimer's at its beginning stage to diminish the difficulty of the overall medical complications. The initial state of Alzheimer’s is called Mild cognitive impairment (MCI), and hence it is a decent target for premature diagnosis and treatment of Alzheimer's. This project focuses on coordinating numerous imaging modalities …

Probabilistic And Machine Learning Enhancement To Conn Toolbox, Gayathri Hanuma Ravali Kuppachi

Master's Projects

Clinical depression is a state of mind where the person suffers from persevering and overpowering sorrow. Existing examinations have exhibited that the course of action of arrangement in the brain of patients with clinical depression has a weird framework topology structure. In the earlier decade, resting-state images of the brain have been under the radar a. Specifically, the topological relationship of the brain aligned with graph hypothesis has discovered a strong connection in patients experiencing clinical depression. However, the systems to break down brain networks still have a couple of issues to be unwound. This paper attempts to give a …

Higher-Order Link Prediction Using Graph Embeddings, Neeraj Chavan

Master's Projects

Link prediction is an emerging field that predicts if two nodes in a network are likely to be connected or not in the near future. Networks model real-world systems using pairwise interactions of nodes. However, many of these interactions may involve more than two nodes or entities simultaneously. For example, social interactions often occur in groups of people, research collaborations are among more than two authors, and biological networks describe interactions of a group of proteins. An interaction that consists of more than two entities is called a higher-order structure. Predicting the occurrence of such higher-order structures helps us solve …

Detection And Analysis Of Malware Evolution, Sunhera Barunkumar Paul

Master's Projects

Malware is a malicious software that causes disruption, allows access to unapproved resources, or performs other unauthorized activity. Developing effective malware detection techniques is a critical aspect of information security. One difficulty that arises is that malware often evolves over time, due to changing goals of malware developers, or to counter advances in detection. This evolution can occur through various modifications in malware code. To maintain effective malware detection, it is necessary to detect and analyze malware evolution so that appropriate countermeasures can be taken. We perform a variety of experiments to detect points in time where a malware family …

Sentiment Analysis For Troll Activity Detection On Sina Weibo, Zidong Jiang

Master's Projects

The impact of social media on the modern world is difficult to overstate. Virtually all companies and public figures have social media accounts on popular platforms such as Twitter and Facebook. In China, the micro-blogging service provider Sina Weibo is the most popular such service. To overcome negative publicity, Weibo trolls the so called Water Army can be hired to post deceptive comments.

In recent years, troll detection and sentiment analysis have been studied, but we are not aware of any research that considers troll detection based on sentiment analysis. In this research, we focus on troll detection via sentiment …

Video Synthesis From The Stylegan Latent Space, Lei Zhang

Master's Projects

Generative models have shown impressive results in generating synthetic images. However, video synthesis is still difficult to achieve, even for these generative models. The best videos that generative models can currently create are a few seconds long, distorted, and low resolution. For this project, I propose and implement a model to synthesize videos at 1024x1024x32 resolution that include human facial expressions by using static images generated from a Generative Adversarial Network trained on the human facial images. To the best of my knowledge, this is the first work that generates realistic videos that are larger than 256x256 resolution from single …

Word Embedding Techniques For Malware Classification, Aniket Chandak

Master's Projects

Word embeddings are often used in natural language processing as a means to quantify relationships between words. More generally, these same word embedding techniques can be used to quantify relationships between features. In this paper, we conduct a series of experiments that are designed to determine the effectiveness of word embedding in the context of malware classification. First, we conduct experiments where hidden Markov models (HMM) are directly applied to opcode sequences. These results serve to establish a baseline for comparison with our subsequent word embedding experiments. We then experiment with word embedding vectors derived from HMMs— a technique that …

Ai Quantification Of Language Puzzle To Language Learning Generalization, Harita Shroff

Master's Projects

Online language learning applications provide users multiple ways/games to learn a new language. Some of the ways include rearranging words in the foreign language sentences, filling in the blanks, providing flashcards, and many more. Primarily this research focused on quantifying the effectiveness of these games in learning a new language. Secondarily my goal for this project was to measure the effectiveness of exercises for transfer learning in machine translation. Currently, very little research has been done in this field except for the research conducted by the online platforms to provide assurance to their users [12]. Machine learning has been used …

Housing Market Crash Prediction Using Machine Learning And Historical Data, Parnika De

Master's Projects

The 2008 housing crisis was caused by faulty banking policies and the use of credit derivatives of mortgages for investment purposes. In this project, we look into datasets that are the markers to a typical housing crisis. Using those data sets we build three machine learning techniques which are, Linear regression, Hidden Markov Model, and Long Short-Term Memory. After building the model we did a comparative study to show the prediction done by each model. The linear regression model did not predict a housing crisis, instead, it showed that house prices would be rising steadily and the R-squared score of …

An Ai For A Modification Of Dou Di Zhu, Xuesong Luo

Master's Projects

We describe our implementation of AIs for the Chinese game Dou Di Zhu. Dou Di Zhu is a three-player game played with a standard 52 card deck together with two jokers. One player acts as a landlord and has the advantage of receiving three extra cards, the other two players play as peasants. We designed and implemented a Deep Q-learning Neural Network (DQN) agent to play the Dou Di Zhu. At the same time, we also designed and made a pure Q-learning based agent as well as a Zhou rule-based agent to compare with our main agent. We show the …

Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen

Master's Projects

The spread of information about current events is a way for everybody in the world to learn and understand what is happening in the world. In essence, the news is an important and powerful tool that could be used by various groups of people to spread awareness and facts for the good of mankind. However, as information becomes easily and readily available for public access, the rise of deceptive news becomes an increasing concern. The reason is due to the fact that it will cause people to be misled and thus could affect the livelihood of themselves or others. The …