2022 Intermountain Engineering, Technology and Computing (IETC)最新文献

{"title":"Laser Assisted Cleaving for Waveguide Facets on Silicon","authors":"Mckay Formica, N. Boehme, Tyler J. Adams, Gracie Richens, A. Hawkins","doi":"10.1109/ietc54973.2022.9796794","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796794","url":null,"abstract":"We have developed a method for facet cleaving of silicon substrates which is applicable to integrated waveguides. The method relies on a femtosecond laser-cut trench on the opposite side of the substrate to the waveguides. Resulting facets produce waveguides with higher optical throughput than those produced with only mechanical cleaving, even when laser cut trenches have minor angle misalignment with the silicon crystal plane.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"26 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133885678","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}

{"title":"A Comprehensive Survey: Cybersecurity Challenges and Futures of Autonomous Drones","authors":"Nyles Durfey, S. Sajal","doi":"10.1109/ietc54973.2022.9796881","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796881","url":null,"abstract":"Unmanned Aircraft Systems (UAS) also known as drones are changing the world [1]. Whether it’s military, medicine, agriculture, city planning, surveillance, package delivery or sports. These machines are useful in ways that haven’t been discovered yet. Making dangerous work safe by putting something between people and potential risks. Increasing the amount of land that can be searched in search and rescues. Drones are making difficult jobs easier. Conversely the danger they pose is also being discovered. Everyday a new danger is presented by the growing number of drones being used, and as we rely more on them the problem grows. This research paper looks into the current security issues that are found in drones and what is being done to lessen the risk that drones pose to countries, businesses, and civilians. Looking to find what works best to protect drones from cyber threats, and how to protect against them. This is done by reading research journals, news articles, watching videos done by professors/news organizations then analyzing the data found. Two frames of mind are used when analyzing the problems found from research. First, will be how to protect the drone from cyber threats. Second will be how to protect from drone cyber attacks. The results of this research found that drones are extremely unsafe against cyber attacks, and are powerful weapons to finding and exploiting holes in a systems defense. Research on defending drones found insufficient authentication, encryption, signal verification, defined access privileges, and threat reporting. These problems exist from hobby pilots to [2]Department of Defense (DOD) drones. The greatest tool a drone has when attacking a system is stealth and mobility. It can attack multiple targets with only a few fly bys. Because of this the best defense against drone cyber threats is detection. Once detected the drone could be dealt with physically or by exploiting security holes commonly found in drones. Resulting from the cybersecurity threat posed both to drones, and from drones [3, 4, 5, 6] laws are being written in multiple countries. These laws are designed to limit their usage or ban them completely. To solve this problem, there are three key steps to eliminating a majority of the threats. [7] Implementing authentication, encryption, and a threat reporting system would allow drones to continue to change the world safely.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123971833","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}

{"title":"IETC Committee Members","authors":"","doi":"10.1109/ietc54973.2022.9796729","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796729","url":null,"abstract":"","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121153508","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}

{"title":"Facial Password Data Augmentation","authors":"Shad A. Torrie, Andrew W. Sumsion, Zheng Sun, Dah-Jye Lee","doi":"10.1109/ietc54973.2022.9796673","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796673","url":null,"abstract":"We present a series of data augmentation methods that utilize noise in a positive test case as multiple negative test cases. These data augmentation methods are utilized to increase the accuracy of a facial authentication system that uses facial motion concurrently with conventional facial identification to verify a person’s identity. We propose using non moving frames from a video of a facial motion, as negative cases to increase the significance of the negative cases used during training. We will also use single frames repeated from the motion to supply more negative samples of non-moving faces. These methods are useful in training the network to distinguish a facial motion from a non moving face. The data augmentation will also be used during evaluation of the network to assign each facial motion password a strength value based on how they compare to the augmented data.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129168390","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}

{"title":"Mineral Precipitation In Utah Lake And Its Effluent Mixing Zones","authors":"Jacob Taggart, T. Miller, A. Navarre‐Sitchler, G. Carling","doi":"10.1109/ietc54973.2022.9796662","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796662","url":null,"abstract":"While public interest has grown in recent years to rehabilitate Utah Lake’s eutrophic condition, restoration efforts imposed on the lake will be most effective when they account for the lake’s internal processes. Mineral precipitation within the effluent mixing zones of Utah Lake was investigated through water, precipitate, and sediment analyses, including geochemical modeling and x-ray diffraction. While it may be possible for apatite to form in-situ, calcite is the only major mineral that actively precipitates in Utah Lake. Quantifying the rate of phosphorus coprecipitation with calcite is likely an essential aspect of characterizing total phosphorus cycling in Utah Lake.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130324337","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}

{"title":"Design and Implementation of a Quadcopter Drone Control System for Photography Applications","authors":"Blake Chamberlain, Waseem Sheikh","doi":"10.1109/ietc54973.2022.9796735","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796735","url":null,"abstract":"Quadcopter drones equipped with onboard cameras are increasingly being utilized in photography to obtain pictures that would otherwise be impossible or too expensive to shoot. The portability and flexibility of quadcopter drones is often utilized by amateur photographers. An important aspect of designing a quadcopter drone for photography applications is ensuring that the drone will automatically stabilize and remain steady to ensure the perfect shot, without needing input on part of the user. To achieve this purpose, a quadcopter drone uses a control system with tuned parameters to remain as steady as possible. This paper describes an implementation of a quadcopter control system using a PID controller and Kalman filter to improve the inputs from the onboard gyroscope, to make the drone as steady as possible for a perfect shot.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"35 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130647305","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}

{"title":"Automated Hearing Impairment Diagnosis Using Machine Learning","authors":"Kyra S Taylor, Waseem Sheikh","doi":"10.1109/ietc54973.2022.9796707","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796707","url":null,"abstract":"Approximately 700 million people will suffer from disabling hearing loss by 2050. Underdeveloped and developing countries, which encompass a considerable proportion of people with incapacitating hearing impairment, have a sparse number of audiologists and otolaryngologists. The lack of specialists leaves most hearing impairments undiagnosed for a long time. In this paper, we propose an automated hearing impairment diagnosis software—based on machine learning—to support audiologists and otolaryngologists in accurately and efficiently diagnosing and classifying hearing loss. We present the design, implementation, and performance analysis of the automated hearing impairment diagnosis software, which consists of two modules: a hearing test Data Generation Module and a Machine Learning Model. The Data Generation Module produces a diverse and exhaustive dataset for training and evaluating the Machine Learning Model. By employing multiclass and multi-label classification techniques to learn from the hearing test data, the model can instantaneously predict the type, degree, and configuration of hearing loss with high accuracy. Our proposed Machine Learning Model demonstrates propitious results with a prediction time of 634 ms, a log-loss reduction rate of 98.48%, and macro and micro precisions of 100%—showing the model’s applicability to assist audiologists and otolaryngologists in rapidly and accurately classifying the type, degree, and configuration of hearing loss.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"112 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133848613","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}

{"title":"A Time-Series Analysis of Traffic Crashes in New York City","authors":"Khaled Shaaban, M. Ibrahim","doi":"10.1109/ietc54973.2022.9796728","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796728","url":null,"abstract":"In New York City, traffic crashes are one of the main causes of fatalities in the city. This study presents a comprehensive time series analysis of road crashes in the city from 2013 to 2019. The crash data were collected, organized, and analyzed at different time levels: yearly, seasonally, monthly and hourly bases. Forecasting of the total number of crashes in the years 2020 to 2025 was conducted using the Box-Jenkins method based on the autoregressive integrated moving average (ARIMA) model. The model was statistically validated using a modified Box-Pierce (Ljung-Box) Chi-Square test. The proposed model was also used for backward prediction of the year 2019 to compare with actual observations. The predicted results showed a good agreement with the actual observed results. The results also showed a strong potential of having a reduction in the total number of crashes in the future.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134313727","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}

{"title":"What Twitter is saying about Women in Technology","authors":"Kelsey M Stephens, Kodey Crandall","doi":"10.1109/ietc54973.2022.9796681","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796681","url":null,"abstract":"As technology continues to evolve and expand, the number of women in technology-related fields remains devastatingly low. Consequently, it is vital to determine the reasons why women are hesitant to enter these fields or leave upon entering. In addition to this, it is essential to understand the current experiences and conversations surrounding women in technology to determine what changes are needed. This paper analyzes Twitter data, including tweets and Twitter profile information. Tweets containing hashtags related to women in technology to answer the research questions, “What are the current perceptions of women in technology?” and “Are the conversations about women in technology negatively or positively influencing women to enter this field?” Approximately 200 tweets containing user profile information and hashtags were collected and analyzed to determine the diverse interests, skills, and views of women in the industry and their experiences within the field of technology. The results of this study may allow for industry stereotypes to be diminished and provide insight into the challenges and successes of women in the field.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132481364","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}

{"title":"Human Cognition Aware QoE For NOMA Pricing: A Prospect-Theoretic Augmentation To Non-Orthogonal Wireless Multiple Access","authors":"K. Ramamoorthy, Wei Wang","doi":"10.1109/ietc54973.2022.9796780","DOIUrl":"https://doi.org/10.1109/ietc54973.2022.9796780","url":null,"abstract":"Human cognition has become a fundamental metric to evaluate the Quality of Experience (QoE) and service provided in modern day communication systems. Expected Utility Theorem (EUT) is widely used to mathematically model human behavior and analyze decision-making process. However, studies carried out in literature reveal that the decision-making ability of users under certain circumstances, violate the precepts of EUT and proposed an alternative model called Prospect Theory (PT). On the other hand, Non-Orthogonal Multiple Access (NOMA) has been advocated as a new promising technique to improve network capacity performance. In NOMA research, issues such as congestion control and power allocation have been the primary focus and end-user QoE has largely been ignored. In the past, we have designed a NOMA pricing framework to simultaneously boost user QoE and base station profits while addressing the other issues of power selection and resource allocation. The primary focus of this paper is to introduce the new prospect-theoretic postulates to the NOMA pricing framework to further study the user QoE in wireless multimedia services. The prospect-theoretic QoE model for NOMA communication has been derived using the weighting function and value function. Further, we have simulated a NOMA network to evaluate the efficacy of the developed prospect-theoretic QoE model. Simulation results exemplify the potentials of prospect-theoretic QoE modeling of NOMA pricing framework in wireless multimedia communications.","PeriodicalId":251518,"journal":{"name":"2022 Intermountain Engineering, Technology and Computing (IETC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116202436","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}