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3d Bionic Arm, Anny Baez Silfa 2021 CUNY New York City College of Technology

3d Bionic Arm, Anny Baez Silfa

Publications and Research

Previous work had been done on what was an adaptation of a robotic arm for Roboqueen, which is a persistent research project of the Department of Computer Engineering Technology. This robotic arm consisted of removing the cardboard hands from the Roboqueen and being replaced by 3D printed fingers and wrists to add functionality that did not exist before. Servo motors connected to Arduinos hidden in the forearm will be used to move the fingers and pick up and hold objects in the hand. Currently, the Finger Myoware is an update of the robotic arm in order to understand how prosthetic ...


Jack Voltaic 3.0 Cyber Research Report, Erica Mitchell, Douglas Fletcher, Erik Korn, Steven Whitham, Jason Hillman, Ron Yearwood, Clint Walker, Aryn Pyke, Gabriel Weaver, Brandon Pugh, Katherine Hutton, George Platsis, Timothy Klett, Ryan Hruska 2021 Army Cyber Institute

Jack Voltaic 3.0 Cyber Research Report, Erica Mitchell, Douglas Fletcher, Erik Korn, Steven Whitham, Jason Hillman, Ron Yearwood, Clint Walker, Aryn Pyke, Gabriel Weaver, Brandon Pugh, Katherine Hutton, George Platsis, Timothy Klett, Ryan Hruska

ACI Technical Reports

The Jack Voltaic (JV) Cyber Research project is an innovative, bottom-up approach to critical infrastructure resilience that informs our understanding of existing cybersecurity capabilities and identifies gaps. JV 3.0 contributed to a repeatable framework cities and municipalities nationwide can use to prepare. This report on JV 3.0 provides findings and recommendations for the military, federal agencies, and policy makers.


Jack Voltaic 3.0 Cyber Research Report Executive Summary, Douglas Fletcher, Erica Mitchell, Erik Korn, Steven Whitham, Jason Hillman, Aryn Pyke 2021 Army Cyber Institute

Jack Voltaic 3.0 Cyber Research Report Executive Summary, Douglas Fletcher, Erica Mitchell, Erik Korn, Steven Whitham, Jason Hillman, Aryn Pyke

ACI Technical Reports

This condensed Executive summary provides an overview of the information contained in the full JV 3.0 Cyber Research Report.


Knowledge Infused Policy Gradients For Adaptive Pandemic Control, Kaushik Roy, Qi Zhang, Manas Gaur, Amit P. Sheth 2021 University of South Carolina - Columbia

Knowledge Infused Policy Gradients For Adaptive Pandemic Control, Kaushik Roy, Qi Zhang, Manas Gaur, Amit P. Sheth

Publications

COVID-19 has impacted nations differently based on their policy implementations. The effective policy requires taking into account public information and adaptability to new knowledge. Epidemiological models built to understand COVID-19 seldom provide the policymaker with the capability for adaptive pandemic control (APC). Among the core challenges to be overcome include (a) inability to handle a high degree of non-homogeneity in different contributing features across the pandemic timeline, (b) lack of an approach that enables adaptive incorporation of public health expert knowledge, and (c) transparent models that enable understanding of the decision-making process in suggesting policy. In this work, we take ...


"Is Depression Related To Cannabis?": A Knowledge-Infused Model For Entity And Relation Extraction With Limited Supervision, Kaushik Roy, Usha Lokala, Vedant Khandelwal, Amit P. Sheth 2021 University of South Carolina - Columbia

"Is Depression Related To Cannabis?": A Knowledge-Infused Model For Entity And Relation Extraction With Limited Supervision, Kaushik Roy, Usha Lokala, Vedant Khandelwal, Amit P. Sheth

Publications

With strong marketing advocacy of the benefits of cannabis use for improved mental health, cannabis legalization is a priority among legislators. However, preliminary scientific research does not conclusively associate cannabis with improved mental health. In this study, we explore the relationship between depression and consumption of cannabis in a targeted social media corpus involving personal use of cannabis with the intent to derive its potential mental health benefit. We use tweets that contain an association among three categories annotated by domain experts - Reason, Effect, and Addiction. The state-of-the-art Natural Langauge Processing techniques fall short in extracting these relationships between cannabis ...


Bibliometric Analysis Of One-Stage And Two-Stage Object Detection, Aditya Lohia, Kalyani Dhananjay Kadam, Rahul Raghvendra Joshi, Dr. Anupkumar M. Bongale 2021 Symbiosis International University

Bibliometric Analysis Of One-Stage And Two-Stage Object Detection, Aditya Lohia, Kalyani Dhananjay Kadam, Rahul Raghvendra Joshi, Dr. Anupkumar M. Bongale

Library Philosophy and Practice (e-journal)

Object Detection using deep learning has seen a boom in the recent couple of years. Observing the trend and its research, it is important to summarize bibliometrics related to object detection which will help researchers contribute to this subject area. This paper details bibliometrics for one-stage object detection and two-stage object detection. This uses Scopus database for data analysis. This also uses tools like Sciencescape, Gephi, etc. It can be observed that the advancements to the field of object detection are seen in recent years and explored to its full extent. It is observed that Chinese universities and researchers are ...


Exploring The Efficiency Of Self-Organizing Software Teams With Game Theory, Clay Stevens, Jared Soundy, Hau Chan 2021 University of Nebraska - Lincoln

Exploring The Efficiency Of Self-Organizing Software Teams With Game Theory, Clay Stevens, Jared Soundy, Hau Chan

CSE Conference and Workshop Papers

Over the last two decades, software development has moved away from centralized, plan-based management toward agile methodologies such as Scrum. Agile methodologies are founded on a shared set of core principles, including self-organizing software development teams. Such teams are promoted as a way to increase both developer productivity and team morale, which is echoed by academic research. However, recent works on agile neglect to consider strategic behavior among developers, particularly during task assignment–one of the primary functions of a self-organizing team. This paper argues that self-organizing software teams could be readily modeled using game theory, providing insight into how ...


Addressing Multiple Bit/Symbol Errors In Dram Subsystem, Ravikiran Yeleswarapu, Arun K. Somani 2021 Iowa State University

Addressing Multiple Bit/Symbol Errors In Dram Subsystem, Ravikiran Yeleswarapu, Arun K. Somani

Electrical and Computer Engineering Publications

As DRAM technology continues to evolve towards smaller feature sizes and increased densities, faults in DRAM subsystem are becoming more severe. Current servers mostly use CHIPKILL based schemes to tolerate up-to one/two symbol errors per DRAM beat. Such schemes may not detect multiple symbol errors arising due to faults in multiple devices and/or data-bus, address bus. In this article, we introduce Single Symbol Correction Multiple Symbol Detection (SSCMSD)—a novel error handling scheme to correct single-symbol errors and detect multi-symbol errors. Our scheme makes use of a hash in combination with Error Correcting Code (ECC) to avoid silent ...


A Bibliometric Analysis Of Distributed Incremental Clustering On Images, Ayushi Agrawal, Preeti Mulay, Krithika Iyer, Saloni Sarbhai 2021 Ph.D. Guide and Associate Professor, Symbiosis Institute of Technology (SIT) affiliated to Symbiosis International (Deemed University), Pune, India.

A Bibliometric Analysis Of Distributed Incremental Clustering On Images, Ayushi Agrawal, Preeti Mulay, Krithika Iyer, Saloni Sarbhai

Library Philosophy and Practice (e-journal)

Unstructured information is continuously irregular and streaming information from such a sequence is tedious because it lacks labels and accumulates with time. This is possible using Incremental Clustering algorithms that use previously learned information to accommodate new data and avoid retraining. This paper therefore seeks to understand the status of "Distributed Incremental Clustering" on images with text and numerical values, its limitations, scope, and other details to devise a better algorithm in future. To further enhance the analysis, we have also included methodology, which can be used to perform clustering on images or documents based on its content.


Plasmonic Waveguides To Enhance Quantum Electrodynamic Phenomena At The Nanoscale, Ying Li, Christos Argyropoulos 2021 Nanjing University of Information Science and Technology

Plasmonic Waveguides To Enhance Quantum Electrodynamic Phenomena At The Nanoscale, Ying Li, Christos Argyropoulos

Faculty Publications from the Department of Electrical and Computer Engineering

The emerging field of plasmonics can lead to enhanced light-matter interactions at extremely nanoscale regions. Plasmonic (metallic) devices promise to efficiently control both classical and quantum properties of light. Plasmonic waveguides are usually used to excite confined electromagnetic modes at the nanoscale that can strongly interact with matter. The analysis of these nanowaveguides exhibits similarities with their low frequency microwave counterparts. In this article, we review ways to study plasmonic nanostructures coupled to quantum optical emitters from a classical electromagnetic perspective. These quantum emitters are mainly used to generate single-photon quantum light that can be employed as a quantum bit ...


Enhanced Interest Aware Peoplerank For Opportunistic Mobile Social Networks, Yosra Saad Shahin 2021 The American University in Cairo AUC

Enhanced Interest Aware Peoplerank For Opportunistic Mobile Social Networks, Yosra Saad Shahin

Theses and Dissertations

Network infrastructures are being continuously challenged by increased demand, resource-hungry applications, and at times of crisis when people need to work from homes such as the current Covid-19 epidemic situation, where most of the countries applied partial or complete lockdown and most of the people worked from home. Opportunistic Mobile Social Networks (OMSN) prove to be a great candidate to support existing network infrastructures. However, OMSNs have copious challenges comprising frequent disconnections and long delays. we aim to enhance the performance of OMSNs including delivery ratio and delay. We build upon an interest-aware social forwarding algorithm, namely Interest Aware PeopleRank ...


Performance Of Single Board Computers For Vision Processing, Curtis Manore CDT'21, Pratheek Manjunath, Dominic Larkin 2021 United States Military Academy

Performance Of Single Board Computers For Vision Processing, Curtis Manore Cdt'21, Pratheek Manjunath, Dominic Larkin

West Point Research Papers

With the increasing complexity of machine vision algorithms and growing applications of image processing, how do computers without a dedicated graphics processor perform? This research discusses the computational abilities of two lowcost single board computers (SBCs) by subjecting them to various Visual Inertial Odometry (VIO) algorithms. The end goal of this research is to identify a SBC which meets the requirements of being employed on an Unmanned Aerial System for autonomous navigation.


Estimating Remaining Useful Life In Machines Using Artificial Intelligence: A Scoping Review, Sameer Sayyad, Satish Kumar, Arunkumar Bongale, Anupkumar Bongale, Shruti Patil 2021 Symbiosis Institute of Technology (SIT), Symbiosis International (Deemed) University, Pune

Estimating Remaining Useful Life In Machines Using Artificial Intelligence: A Scoping Review, Sameer Sayyad, Satish Kumar, Arunkumar Bongale, Anupkumar Bongale, Shruti Patil

Library Philosophy and Practice (e-journal)

The remaining useful life (RUL) estimations become one of the most essential aspects of predictive maintenance (PdM) in the era of industry 4.0. Predictive maintenance aims to minimize the downtime of machines or process, decreases maintenance costs, and increases the productivity of industries. The primary objective of this bibliometric paper is to understand the scope of literature available related to RUL prediction. Scopus database is used to perform the analysis of 1673 extracted scientific literature from the year 1985 to 2020. Based on available published documents, analysis is done on the year-wise publication data, document types, language-wise distribution of ...


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 2021 Sreyas Institute Of Engineering and Technology

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 ...


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 2021 Symbiosis International University

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 ...


Diabetes Prediction Using Machine Learning : A Bibliometric Analysis, Vijayshri Nitin Khedkar, Sina Patel 2021 Symbiosis Institute of Technology, Symbiosis International (Deemed University)

Diabetes Prediction Using Machine Learning : A Bibliometric Analysis, Vijayshri Nitin Khedkar, Sina Patel

Library Philosophy and Practice (e-journal)

Diabetes Mellitus is a chronic disease which can be deadly if undetected for longer time. Artificial intelligence is helping in healthcare industry to a great extent by helping professionals to derive useful information and patterns from data available in various formats: Survey data, electronic health records, laboratory data.. Diabetes, if predicted at an early stage can help many people to save lives and cost for healthcare. Decision-making, diagnosing and predicting diabetes have become an increasing trend in recent years. There are numerous publications in diabetes prediction and yet it’s an ongoing research topic with availability of new data and ...


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 2021 Electronics and Telecommunication Engineering Department, Symbiosis Institute of Technology (SIT), Symbiosis International (Deemed University) (SIU), Lavale, Pune, Maharashtra, India

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 ...


Effect Of Information Technology Capital: Technology Infrastructure, Database, Software, And Brainware Toward Optimize The Use Of Information Technology (Case Study : Uin Sunan Ampel Of Surabaya), Rismawati Br Sitepu, Ilham m.said, Tanti Handriana, Praptini Yulianti 2021 Airlangga University of Surabaya, East Java East Java, Indonesia

Effect Of Information Technology Capital: Technology Infrastructure, Database, Software, And Brainware Toward Optimize The Use Of Information Technology (Case Study : Uin Sunan Ampel Of Surabaya), Rismawati Br Sitepu, Ilham M.Said, Tanti Handriana, Praptini Yulianti

Library Philosophy and Practice (e-journal)

This research was conducted to determine the extent of the influence of technology infrastructure costs, software costs, database costs and brainware costs to increase the information technology budget of the Sunan Ampel State Islamic University in Surabaya and efficient use of the budget. The purpose of this study is to prove that there is a positive and significant influence of technology infrastructure costs, software costs, database costs and brainware costs to increase information technology budgets by using validity and reliability tests and classic tests such as the Normality test, Multicollinearity test, autocorrelation test, Heteroskedasticity test , and Linearity test. This study ...


Bert For Question Answering On Bioasq, Eric R. Fu, Rikel Djoko, Maysam Mansor, Robert Slater 2021 Southern Methodist University

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 ...


A Literature Survey And Bibliometric Analysis Of Application Of Artificial Intelligence Techniques On Wireless Mesh Networks, Smita R. Mahajan Mrs., Harikrishnan R Dr., Ketan Kotecha Dr. 2021 Symbiosis Institute of Technology, Symbiosis International University, Pune, Maharashtra, India

A Literature Survey And Bibliometric Analysis Of Application Of Artificial Intelligence Techniques On Wireless Mesh Networks, Smita R. Mahajan Mrs., Harikrishnan R Dr., Ketan Kotecha Dr.

Library Philosophy and Practice (e-journal)

Recent years have seen a surge in the use of technology for executing transactions in both online and offline modes. Various industries like banking, e-commerce, and private organizations use networks for the exchange of confidential information and resources. Network security is thus of utmost importance, with the expectation of effective and efficient analysis of the network traffic. Wireless Mesh Networks are effective in communicating information over a vast span with minimal costs. A network is evaluated based on its security, accessibility, and extent of interoperability. Artificial Intelligence techniques like machine learning and deep learning have found widespread use to solve ...


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