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2022 IEEE MIT Undergraduate Research Technology Conference (URTC)最新文献

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A Novel Approach to Secure Smartwatch Authentication: Structure-Borne Sound Identification and Gesture Recognition 一种安全的智能手表认证新方法:结构声识别和手势识别
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002176
Fadi Farag, Sophia Fu, Aashika Jagadeesh, Aashi Mishra, Andrew Noviello, Yingying Chen, Yilin Yang
{"title":"A Novel Approach to Secure Smartwatch Authentication: Structure-Borne Sound Identification and Gesture Recognition","authors":"Fadi Farag, Sophia Fu, Aashika Jagadeesh, Aashi Mishra, Andrew Noviello, Yingying Chen, Yilin Yang","doi":"10.1109/URTC56832.2022.10002176","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002176","url":null,"abstract":"With the need to conveniently secure devices, manufacturers have pushed to explore new methods of authentication. We propose a smartwatch authentication system based on structure-borne sound emitted from the contact between a user’s wrist and smartwatch. Audio recordings from users in loud and quiet settings, with and without hand movements (‘gestures’) were collected. After extracting relevant features from the data, numerous machine learning models, including Support Vector Machines (SVMs), K-Nearest Neighbors (KNNs), and linear discriminants, were tested for authentication accuracy. Among these models, the linear discriminant model had the highest identification accuracy for recordings without gestures, and the K-Nearest Neighbors model performed the best for gesture-based authentication. Unlike more complex architectures, the relative simplicity and accuracy of linear discriminant models demonstrated the computational efficiency of structure-borne sound authentication.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116943068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine Learning For The Classification And Separation Of E-Waste 电子垃圾分类与分离的机器学习
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002242
Ethan Zhou
{"title":"Machine Learning For The Classification And Separation Of E-Waste","authors":"Ethan Zhou","doi":"10.1109/URTC56832.2022.10002242","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002242","url":null,"abstract":"The amount of global e-waste is growing at a rapid rate and is projected to increase to 74.7 Mt by 2030. However, according to a recent United Nation’s study in 2019, the collection and recycle rate of e-waste is only 17.4%. One of the most challenging barriers in large-scale e-waste recycling is the labor-intensive sorting, dismantling, and hazardous removal process, which incentivized the illegal transfer of large amounts of e-waste from developed countries to Asian and African countries. To protect the environment and the health of workers, an automated method for sorting and separation of e-waste is urgently needed. In this project, a convolutional neural network (CNN) image-recognition algorithm was developed to classify e-waste into different categories with high accuracy. An image database of four different classes of e-waste was created, and a demonstration setup was established. The pre-process of image data, the selection of hyper-parameters and the accuracy of the CNN model were discussed. The developed CNN model exhibited a training accuracy of 96.9% and a validation accuracy of 93.9%. The use of different image sizes, data augmentation by rotation, and background removal were experimented to improve the model performance. Planned future work includes expanding the database to add more diversified classes of e-waste and exploring the creation of a conveyor-belt-based demonstration.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Are Fair Learning To Rank Models Really Fair? An Analysis Using Inferred Gender 公平学习对模型进行排名真的公平吗?使用推断性别的分析
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002233
Alexander Pietrick, Alyssa Romportl, Shailen Smith, O. Olulana, Kathleen Cachel, E. Rundensteiner
{"title":"Are Fair Learning To Rank Models Really Fair? An Analysis Using Inferred Gender","authors":"Alexander Pietrick, Alyssa Romportl, Shailen Smith, O. Olulana, Kathleen Cachel, E. Rundensteiner","doi":"10.1109/URTC56832.2022.10002233","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002233","url":null,"abstract":"Fair Learning To Rank (LTR) frameworks require demographic information; however, that information is often unavailable. Inference algorithms may infer the missing demographic information to supply to the fair LTR model. In this study, we analyze the effect of using a trained fair LTR model with uncertain demographic inferences. We show that inferred data results in varying levels of fairness and utility depending on inference accuracy. Specifically, less accurate inferred data adversely affects the rankings’ fairness, while more accurate inferred data creates fairer rankings. Therefore, we recommend that a careful evaluation of demographic inference algorithms before use is critical.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114055935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Image Dilution using Harris Corner Detection and Geometric Kernels 使用哈里斯角检测和几何核的图像稀释
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002246
Aiden James, Xingjie Li
{"title":"Image Dilution using Harris Corner Detection and Geometric Kernels","authors":"Aiden James, Xingjie Li","doi":"10.1109/URTC56832.2022.10002246","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002246","url":null,"abstract":"Image files contain large amounts of data. An image is essentially a matrix of values, often represented as ARGB (alpha, red, green, blue) arrays. A large three dimensional matrix with a height and width likely in the hundreds can take long for a program to read. However, many applications may only require specific key features to understand an image. The majority of pixel data is relatively unimportant when determining the contents of the image file. In fact, such extra data can sometimes deceive the machine, or in the case of a hybrid image [1], the human viewer. Using only basic matrix calculations and matrix convolution, specifically Harris Corner Detection and Edge Detection kernels, we have extracted the key features of an image in order to dilute its data. The results show that any confusion, such as noise or the low frequencies of a hybrid image, becomes weaker, and that the computation is very efficient and robust.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125120704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development of Motor-assisted Therapy Bike for Patients with Parkinson’s Disease 帕金森病患者电动辅助治疗自行车的研制
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002182
Emma Lokey, Anna Cetera, Demetrios Petrou, Kellen Waters, K. Mankodiya, Dhaval Solanki
{"title":"Development of Motor-assisted Therapy Bike for Patients with Parkinson’s Disease","authors":"Emma Lokey, Anna Cetera, Demetrios Petrou, Kellen Waters, K. Mankodiya, Dhaval Solanki","doi":"10.1109/URTC56832.2022.10002182","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002182","url":null,"abstract":"In this paper, Theracycle – a rehabilitation exercise bicycle company that specializes in motor-assisted ergometers designed for users with Parkinson’s Disease – aims to increase the functionality of one of their current bicycle designs for their patients. The updated motor-assisted exercise bicycle has increased functionality with advanced safety features, an implemented heart rate detection system, a new touchscreen user interface, and various cycle modes. Since the core functionality of the Theracycle 200 is a motor assisted bicycle, an additional mode was added that includes a resistive training version in order to increase versatility. The integrated touchscreen tablet displays and records live data during the bicycle usage such as their heart rate data, pedaling rate, time duration, speed, and resistance. The updated exercise bicycle continues to function as a rehabilitation device for the users and additionally collects necessary data to observe their improvement which can be further used by clinicians to track user’s progress.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116494925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
URTC 2022 Copyright Page URTC 2022版权页面
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/urtc56832.2022.10002178
{"title":"URTC 2022 Copyright Page","authors":"","doi":"10.1109/urtc56832.2022.10002178","DOIUrl":"https://doi.org/10.1109/urtc56832.2022.10002178","url":null,"abstract":"","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Role of SysML in Integrating an Interdisciplinary Team SysML在整合跨学科团队中的作用
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002249
Kleo Golemi, Arsalan Akhter, S. V. Bhada
{"title":"Role of SysML in Integrating an Interdisciplinary Team","authors":"Kleo Golemi, Arsalan Akhter, S. V. Bhada","doi":"10.1109/URTC56832.2022.10002249","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002249","url":null,"abstract":"Most engineering projects require a team of various disciplines to work together. Although with different disciples there can be issues in communication between disciplines due to jargon and a lack of understanding each role’s capabilities. [1] This is especially true during the early stages of the project. Systems engineers have used SysML as a model-based systems engineering tool to compose and articulate tasks as well as display the collaboration of each discipline towards a goal unifying communication and setting a clearly defined purpose. This paper shows how SysML and UML is used in organizing and articulating the tasks of an interdisciplinary research team, consisting of: robotics, communication, and system engineers toward the goal of fire detection.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130234142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quantum Algorithm for the Simulation of Squamous Cell Lung Carcinoma tested through IBM Quantum Composer 通过IBM Quantum Composer测试的用于模拟鳞状细胞肺癌的量子算法
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002180
Akshita Tiwari
{"title":"Quantum Algorithm for the Simulation of Squamous Cell Lung Carcinoma tested through IBM Quantum Composer","authors":"Akshita Tiwari","doi":"10.1109/URTC56832.2022.10002180","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002180","url":null,"abstract":"Classical algorithms for lung cancer exist based on immunotherapy but are quite prone to error. Non-small cell is a major type of lung cancer, frequently caused by smoking. A classical algorithm to treat non-small-cell lung cancer is compared to a quantum algorithm created. Using superposition of qubits, Born’s rule, and the general qubit rule, an algorithm simulates the pathway of certain driver genes, by finding the angle required of the qubit to be able to result in the probability needed to simulate the pathway, tested in IBM Quantum Composer.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132987016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An EEG-Based Diagnostic Framework for Strokes Using Spectral Analysis and Deep Learning 使用谱分析和深度学习的脑电图中风诊断框架
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002236
Rohan Kalahasty, Lakshmi Sritan Motati
{"title":"An EEG-Based Diagnostic Framework for Strokes Using Spectral Analysis and Deep Learning","authors":"Rohan Kalahasty, Lakshmi Sritan Motati","doi":"10.1109/URTC56832.2022.10002236","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002236","url":null,"abstract":"Strokes affect over 15 million people annually, and treatment must be given within one hour to prevent brain damage. CT and MRI scans are used for stroke diagnosis but are time-consuming and expensive. Electroencephalograms (EEG) solve both problems but are not used due to their complexity. This paper presents a novel application for the automated detection of ischemic and hemorrhagic strokes using EEGs. We propose using the averaged power spectral density to extract important features. We use deep neural networks to respectively detect and classify the stroke type, location, and severity with accuracies of 97.5%, 94.4%, and 99%. Additionally, to allow for easier EEG interpretation and detection of abnormalities, we use azimuthal projection and spline interpolation to reshape 3D electrodes onto 2D contour maps showing the power of frequency bands around the brain. This research could represent a step towards increasing the speed and decreasing the cost of comprehensive stroke diagnosis.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115349489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling the Effects of Engagement Methods in Online Crowd-sourcing Platforms 参与方法在在线众包平台中的影响建模
2022 IEEE MIT Undergraduate Research Technology Conference (URTC) Pub Date : 2022-09-30 DOI: 10.1109/URTC56832.2022.10002175
Rajoshi Basu, Bryan Braga, Hammad Farooqi, Yechan Lee, Aaron Mazzeo
{"title":"Modeling the Effects of Engagement Methods in Online Crowd-sourcing Platforms","authors":"Rajoshi Basu, Bryan Braga, Hammad Farooqi, Yechan Lee, Aaron Mazzeo","doi":"10.1109/URTC56832.2022.10002175","DOIUrl":"https://doi.org/10.1109/URTC56832.2022.10002175","url":null,"abstract":"Crowd-sourcing websites provide accessible platforms to collect and provide information, and their capabilities are growing in the field of education technology. However, most educational crowd-sourcing platforms lack any prioritized features to improve reader engagement. Because of engagement’s beneficial role in accelerating the information absorption process, the research involved developing a model crowd-sourcing platform dubbed “Interactpedia” to test the effects of online engagement features on information retention. Interactpedia included three online features, each modeling one engagement method – formative assessment, cognitive scaffolding, and instant feedback. Efficacy surveys conducted on both Interactpedia and Wikipedia show that content retention improved on average due to the engagement features. Interactpedia serves as a guide for all educational crowd-sourcing platforms to prioritize online engagement features without compromising the streamlined contributor process.","PeriodicalId":330213,"journal":{"name":"2022 IEEE MIT Undergraduate Research Technology Conference (URTC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129909792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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