Comparison Of Word2vec With Hash2vec For Machine Translation, 2020 San Jose State University
Comparison Of Word2vec With Hash2vec For Machine Translation, Neha Gaikwad
Machine Translation is the study of computer translation of a text written in one human language into text in a different language. Within this field, a word embedding is a mapping from terms in a language into small dimensional vectors which can be processed using mathematical operations. Two traditional word embedding approaches are word2vec, which uses a Neural Network, and hash2vec, which is based on a simpler hashing algorithm. In this project, we have explored the relative suitability of each approach to sequence to sequence text translation using a Recurrent Neural Network (RNN). We also carried out experiments to test ...
Improved Chinese Language Processing For An Open Source Search Engine, Xianghong Sun
Natural Language Processing (NLP) is the process of computers analyzing on human languages. There are also many areas in NLP. Some of the areas include speech recognition, natural language understanding, and natural language generation.
Information retrieval and natural language processing for Asians languages has its own unique set of challenges not present for Indo-European languages. Some of these are text segmentation, named entity recognition in unsegmented text, and part of speech tagging. In this report, we describe our implementation of and experiments with improving the Chinese language processing sub-component of an open source search engine, Yioop. In particular, we rewrote ...
Prediction Of Drug-Drug Interaction Potential Using Machine Learning Approaches, 2020 Rowan University
Prediction Of Drug-Drug Interaction Potential Using Machine Learning Approaches, Joseph Scavetta
Theses and Dissertations
Drug discovery is a long, expensive, and complex, yet crucial process for the benefit of society. Selecting potential drug candidates requires an understanding of how well a compound will perform at its task, and more importantly, how safe the compound will act in patients. A key safety insight is understanding a molecule's potential for drug-drug interactions. The metabolism of many drugs is mediated by members of the cytochrome P450 superfamily, notably, the CYP3A4 enzyme. Inhibition of these enzymes can alter the bioavailability of other drugs, potentially increasing their levels to toxic amounts. Four models were developed to predict CYP3A4 ...
Emerging Technologies In Healthcare: Analysis Of Unos Data Through Machine Learning, 2020 CUNY Bernard M Baruch College
Emerging Technologies In Healthcare: Analysis Of Unos Data Through Machine Learning, Reyhan Merekar
The healthcare industry is primed for a massive transformation in the coming decades due to emerging technologies such as Artificial Intelligence (AI) and Machine Learning. With a practical application to the UNOS (United Network of Organ Sharing) database, this Thesis seeks to investigate how Machine Learning and analytic methods may be used to predict one-year heart transplantation outcomes. This study also sought to improve on predictive performances from prior studies by analyzing both Donor and Recipient data. Models built with algorithms such as Stacking and Tree Boosting gave the highest performance, with AUC’s of 0.6810 and 0.6804 ...
Real-Time Ad Click Fraud Detection, 2020 San Jose State University
Real-Time Ad Click Fraud Detection, Apoorva Srivastava
With the increase in Internet usage, it is now considered a very important platform for advertising and marketing. Digital marketing has become very important to the economy: some of the major Internet services available publicly to users are free, thanks to digital advertising. It has also allowed the publisher ecosystem to flourish, ensuring significant monetary incentives for creating quality public content, helping to usher in the information age. Digital advertising, however, comes with its own set of challenges. One of the biggest challenges is ad fraud. There is a proliferation of malicious parties and software seeking to undermine the ecosystem ...
Load Balancing In Cloud Computing, 2020 San Jose State University
Load Balancing In Cloud Computing, Snehal Dhumal
Cloud computing is one of the top trending technologies which primarily focuses on the end user’s use cases. The service provider needs to provide services to many clients. These increasing number of requests from the clients are giving rise to the new inventions in the load scheduling algorithms. There are different scheduling algorithms which are already present in the cloud computing, and some of them includes the Shortest Job First (SJF), First Come First Serve (FCFS), Round Robin (RR) etc. Though there are different parameters to consider when load balancing in cloud computing, makespan (time difference between start time ...
Network Traffic Based Botnet Detection Using Machine Learning, 2020 San Jose State University
Network Traffic Based Botnet Detection Using Machine Learning, Anand Ravindra Vishwakarma
The field of information and computer security is rapidly developing in today’s world as the number of security risks is continuously being explored every day. The moment a new software or a product is launched in the market, a new exploit or vulnerability is exposed and exploited by the attackers or malicious users for different motives. Many attacks are distributed in nature and carried out by botnets that cause widespread disruption of network activity by carrying out DDoS (Distributed Denial of Service) attacks, email spamming, click fraud, information and identity theft, virtual deceit and distributed resource usage for cryptocurrency ...
Virtual Robot Locomotion On Variable Terrain With Adversarial Reinforcement Learning, 2020 San Jose State University
Virtual Robot Locomotion On Variable Terrain With Adversarial Reinforcement Learning, Phong Nguyen
Reinforcement Learning (RL) is a machine learning technique where an agent learns
to perform a complex action by going through a repeated process of trial and error to maximize a well-defined reward function. This form of learning has found applications in robot locomotion where it has been used to teach robots to traverse complex terrain. While RL algorithms may work well in training robot locomotion, they tend to not generalize well when the agent is brought into an environment that it has never encountered before. Possible solutions from the literature include training a destabilizing adversary alongside the locomotive learning agent ...
Using Color Thresholding And Contouring To Understand Coral Reef Biodiversity, 2020 San Jose State University
Using Color Thresholding And Contouring To Understand Coral Reef Biodiversity, Scott Vuong Tran
This paper presents research outcomes of understanding coral reef biodiversity through the usage of various computer vision applications and techniques. It aims to help further analyze and understand the coral reef biodiversity through the usage of color thresholding and contouring onto images of the ARMS plates to extract groups of microorganisms based on color. The results are comparable to the manual markup tool developed to do the same tasks and shows that the manual process can be sped up using computer vision. The paper presents an automated way to extract groups of microorganisms based on color without the use of ...
Implementing Tontinecoin, 2020 San Jose State University
Implementing Tontinecoin, Prashant Pardeshi
One of the alternatives to proof-of-work (PoW) consensus protocols is proof-of- stake (PoS) protocols, which address its energy and cost related issues. But they suffer from the nothing-at-stake problem; validators (PoS miners) are bound to lose nothing if they support multiple blockchain forks. Tendermint, a PoS protocol, handles this problem by forcing validators to bond their stake and then seizing a cheater’s stake when caught signing multiple competing blocks. The seized stake is then evenly distributed amongst the rest of validators. However, as the number of validators increases, the benefit in finding a cheater compared to the cost of ...
Using Network Modeling To Understand The Relationship Between Sars-Cov-1 And Sars-Cov-2, 2020 Florida State University
Using Network Modeling To Understand The Relationship Between Sars-Cov-1 And Sars-Cov-2, Elizabeth Brooke Haywood, Nicole A. Bruce
Biology and Medicine Through Mathematics Conference
No abstract provided.
Exploring Usage Of Web Resources Though A Model Of Api Learning, 2020 Washington University in St. Louis
Exploring Usage Of Web Resources Though A Model Of Api Learning, Finn Voichick
Engineering and Applied Science Theses & Dissertations
Application programming interfaces (APIs) are essential to modern software development, and new APIs are frequently being produced. Consequently, software developers must regularly learn new APIs, which they typically do on the job from online resources rather than in a formal educational context. The Kelleher–Ichinco COIL model, an acronym for “Collection and Organization of Information for Learning,” was recently developed to model the entire API learning process, drawing from information foraging theory, cognitive load theory, and external memory research. We ran an exploratory empirical user study in which participants performed a programming task using the React API with the goal ...
Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, 2020 Washington University in St. Louis
Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, Nicholas Deily
Engineering and Applied Science Theses & Dissertations
Many industries are rapidly adopting additive manufacturing (AM) because of the added versatility this technology offers over traditional manufacturing techniques. But with AM, there comes a unique set of security challenges that must be addressed. In particular, the issue of part verification is critically important given the growing reliance of safety-critical systems on 3D printed parts.
In this thesis, the current state of part verification technologies will be examined in the con- text of AM-specific geometric-modification attacks, and an automated tool for 3D printed part verification will be presented. This work will cover: 1) the impacts of malicious attacks on ...
Csp-Completeness And Its Applications, 2020 Washington University in St. Louis
Csp-Completeness And Its Applications, Alexander Durgin
Engineering and Applied Science Theses & Dissertations
We build off of previous ideas used to study both reductions between CSPrefutation problems and improper learning and between CSP-refutation problems themselves to expand some hardness results that depend on the assumption that refuting random CSP instances are hard for certain choices of predicates (like k-SAT). First, we are able argue the hardness of the fundamental problem of learning conjunctions in a one-sided PAC-esque learning model that has appeared in several forms over the years. In this model we focus on producing a hypothesis that foremost guarantees a small false-positive rate while minimizing the false-negative rate for such hypotheses. Further ...
How Do Video Games Affect The Brain?, 2020 San Jose State University
How Do Video Games Affect The Brain?, Kenneth Lee
ART 108: Introduction to Games Studies
Video games are a wildly popular past time in not only America, but other countries as well. Its popularity has done nothing but increase in an exponential fashion, engulfing more and more members of society in its reach; however, its gaining traction in combination with behavioral observations and frequent violent events compelled many to question its effects on those who play them. Some attribute tragedies like recent school shootings to the vast array of First Person Shooter(FPS) games, blaming it for engraining in adolescents’ and adults’ brains a sense of increased aggression and violence. Others praise educational games for ...
Benchmarking Mongodb Multi-Document Transactions In A Sharded Cluster, 2020 San Jose State University
Benchmarking Mongodb Multi-Document Transactions In A Sharded Cluster, Tushar Panpaliya
Relational databases like Oracle, MySQL, and Microsoft SQL Server offer trans- action processing as an integral part of their design. These databases have been a primary choice among developers for business-critical workloads that need the highest form of consistency. On the other hand, the distributed nature of NoSQL databases makes them suitable for scenarios needing scalability, faster data access, and flexible schema design. Recent developments in the NoSQL database community show that NoSQL databases have started to incorporate transactions in their drivers to let users work on business-critical scenarios without compromising the power of distributed NoSQL features .
MongoDB is ...
Land Registry On Blockchain, 2020 San Jose State University
Land Registry On Blockchain, Mugdha Patil
Understanding Impact Of Twitter Feed On Bitcoin Price And Trading Patterns, 2020 San Jose State University
Understanding Impact Of Twitter Feed On Bitcoin Price And Trading Patterns, Ashrit Deebadi
‘‘Cryptocurrency trading was one of the most exciting jobs of 2017’’. ‘‘Bit- coin’’,‘‘Blockchain’’, ‘‘Bitcoin Trading’’ were the most searched words in Google during 2017. High return on investment has attracted many people towards this crypto market. Existing research has shown that the trading price is completely based on speculation, and its trading volume is highly impacted by news media. This paper discusses the existing work to evaluate the sentiment and price of the cryptocurrency, the issues with the current trading models. It builds possible solutions to understand better the semantic orientation of text by comparing different machine learning techniques ...
Voxel Optimization, 2020 Minnesota State University Moorhead
Voxel Optimization, Scott Bengs
Student Academic Conference
Voxel Optimization This poster presentation covers optimization for voxels. They can be thought of as three dimensional pixels. Vo coming from volume and xel from pixel. Voxels are just values placed in a 3D grid. Voxels have many interesting uses in the medical and scientific field, especially in geology. One use in computer science is storing world information for video games or graphical applications. One very popular example is Minecraft, a game that allows all of the world to be changed, that uses cube shaped voxels. The first topic will be on the naive approach of building a model from ...
Smart Raspberry Pi Puppy, 2020 Minnesota State University Moorhead
Smart Raspberry Pi Puppy, Vy Dao
Student Academic Conference
Many people use computers and smart devices on the Internet of Thing (IoT) networks without truly understanding how they work or what they can do. Therefore, the purpose of this project was to demonstrate how edge devices used gateways to connect to the Amazon Web Services (AWS) IoT platform and show what the AWS IoT platform can do. For this project, a Raspberry Pi 4 will act as a Gateway for the robot that connects all the camera sensors, motion sensors, and temperature sensors to transfer those data to the AWS IoT platform for analytic purposes. The robot will have ...