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Articles 421 - 450 of 7037
Full-Text Articles in Computer Engineering
Transmorph: A Transformer Based Morphological Disambiguator For Turkish, Hi̇lal Özer, Emi̇n Erkan Korkmaz
Transmorph: A Transformer Based Morphological Disambiguator For Turkish, Hi̇lal Özer, Emi̇n Erkan Korkmaz
Turkish Journal of Electrical Engineering and Computer Sciences
The agglutinative nature of the Turkish language has a complex morphological structure, and there are generally more than one parse for a given word. Before further processing, morphological disambiguation is required to determine the correct morphological analysis of a word. Morphological disambiguation is one of the first and crucial steps in natural language processing since its success determines later analyses. In our proposed morphological disambiguation method, we used a transformer-based sequence-to-sequence neural network architecture. Transformers are commonly used in various NLP tasks, and they produce state-of-the-art results in machine translation. However, to the best of our knowledge, transformer-based encoder-decoders have …
Learning Term Weights By Overfitting Pairwise Ranking Loss, Ömer Şahi̇n, İlyas Çi̇çekli̇, Gönenç Ercan
Learning Term Weights By Overfitting Pairwise Ranking Loss, Ömer Şahi̇n, İlyas Çi̇çekli̇, Gönenç Ercan
Turkish Journal of Electrical Engineering and Computer Sciences
A search engine strikes a balance between effectiveness and efficiency to retrieve the best documents in a scalable way. Recent deep learning-based ranker methods are proving to be effective and improving the state-of-the-art in relevancy metrics. However, as opposed to index-based retrieval methods, neural rankers like bidirectional encoder representations from transformers (BERT) do not scale to large datasets. In this article, we propose a query term weighting method that can be used with a standard inverted index without modifying it. Query term weights are learned using relevant and irrelevant document pairs for each query, using a pairwise ranking loss. The …
Measuring The Rol Of Digital Engineering: It's A Journey, Not A Number, Tom Mcdermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, Joseph Bradley
Measuring The Rol Of Digital Engineering: It's A Journey, Not A Number, Tom Mcdermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, Joseph Bradley
Engineering Management & Systems Engineering Faculty Publications
Systems engineering as a discipline has long had difficulty providing quantifiable evidence of its value (Honour 2004); DE transformation provides an opportunity to better measure its value. Transitioning from a document-based to a model-based approach is expensive, and organizations want to know if the effort and cost to adopt MBSE is worth it.
One-Bit Algorithm Considerations For Sparse Pmcw Radar, Ethan Triplett
One-Bit Algorithm Considerations For Sparse Pmcw Radar, Ethan Triplett
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Phase Modulated Continuous Wave (PMCW) radar an emerging technology for autonomous cars. It is more flexible than the current frequency modulated systems, offering better detection resolution, interference mitigation, and future development opportunities. The issue preventing PMCW adoption is the need for high sample-rate analog to digital converters (ADCs). Due to device limits, a large increase in cost and power consumption occurs for every added resolution bit for a given sampling rate. This thesis explores radar detection techniques for few-bit and 1-bit ADC measurements. 1-bit quantization typically results in poor amplitude estimation, which can limit detections if the target signals are …
Learning To Automate Follow-Up Question Generation Using Process Knowledge For Depression Triage On Reddit Posts, Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit Sheth
Learning To Automate Follow-Up Question Generation Using Process Knowledge For Depression Triage On Reddit Posts, Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit Sheth
Publications
Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide informational or therapeutic services (e.g., cognitive behavioral therapy) to patients. However, the utility of CAs to assist in mental health triaging has not been explored in the existing work as it requires a controlled generation of follow-up questions (FQs), which are often initiated and guided by the mental health professionals (MHPs) in clinical settings. In the context of ‘depression’, our experiments show that DLMs coupled with process knowledge in a mental health questionnaire …
Actor-Critic Reinforcement Learning For Bidding In Bilateral Negotiation, Furkan Arslan, Reyhan Aydoğan
Actor-Critic Reinforcement Learning For Bidding In Bilateral Negotiation, Furkan Arslan, Reyhan Aydoğan
Turkish Journal of Electrical Engineering and Computer Sciences
Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is a conflict of interests. Instead of designing a hand-crafted decision-making module, this work proposes a novel bidding strategy adopting an actor-critic reinforcement learning approach, which learns what to offer in a bilateral negotiation. An entropy reinforcement learning framework called Soft Actor-Critic (SAC) is applied to the bidding problem, and a self-play approach is employed to train the model. Our model learns to produce the target utility of …
On The Performance Analysis Of Flexible Pairing Between Uav And Gu In Noma, Man Hee Lee, Soo Young Shin
On The Performance Analysis Of Flexible Pairing Between Uav And Gu In Noma, Man Hee Lee, Soo Young Shin
Turkish Journal of Electrical Engineering and Computer Sciences
The wireless communications regarding unmanned aerial vehicles (UAVs) have been investigated for the usage of base stations (BS) to provide Internet access. This paper presents the usage of a UAV as a pairing user to enhance the sum capacity by flexible pairing in nonorthogonal multiple access (NOMA). In the proposed scheme, the UAVs and the ground users (GUs) get paired to promote the line-of-sight (LoS) characteristics. The performance of flexible pairing is presented in terms of sum capacity, outage probability, and throughput with the LoS path loss. Channel modeling is necessary to apply flexible pairing by utilizing the LoS characteristic …
Content Loss And Conditional Space Relationship In Conditional Generative Adversarial Networks, Enes Eken
Content Loss And Conditional Space Relationship In Conditional Generative Adversarial Networks, Enes Eken
Turkish Journal of Electrical Engineering and Computer Sciences
In the machine learning community, generative models, especially generative adversarial networks (GANs) continue to be an attractive yet challenging research topic. Right after the invention of GAN, many GAN models have been proposed by the researchers with the same goal: creating better images. The first and foremost feature that a GAN model should have is that creating realistic images that cannot be distinguished from genuine ones. A large portion of the GAN models proposed to this end have a common approach which can be defined as factoring the image generation process into multiple states for decomposing the difficult task into …
Using A Static Naming Approach To Implement Remote Scope Promotion, Ayşe Yilmazer
Using A Static Naming Approach To Implement Remote Scope Promotion, Ayşe Yilmazer
Turkish Journal of Electrical Engineering and Computer Sciences
GPUs employ simple coherence mechanisms and require explicit use of costly synchronization operations for data integrity. Local-scoped synchronization can be utilized to lower the performance penalty of synchronization when sharing is within a subgroup of threads. Unfortunately, in asymmetric sharing (which is an important dynamic sharing pattern), it is necessary to use global-scoped synchronization due to possible accesses by remote sharers. Remote Scope Promotion (RSP) was introduced to take advantage of local-scoped synchronization at regular accesses while using scope promotion at occasional remote accesses. First implementation of RSP makes use of a simple approach that performs costly cache operations on …
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Turkish Journal of Electrical Engineering and Computer Sciences
The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …
Degree-Based Random Walk Approach For Graph Embedding, Sarmad N. Mohammed, Semra Gündüç
Degree-Based Random Walk Approach For Graph Embedding, Sarmad N. Mohammed, Semra Gündüç
Turkish Journal of Electrical Engineering and Computer Sciences
Graph embedding, representing local and global neighbourhood information by numerical vectors, is a crucial part of the mathematical modeling of a wide range of real-world systems. Among the embedding algorithms, random walk-based algorithms have proven to be very successful. These algorithms collect information by creating numerous random walks with a predefined number of steps. Creating random walks is the most demanding part of the embedding process. The computation demand increases with the size of the network. Moreover, for real-world networks, considering all nodes on the same footing, the abundance of low-degree nodes creates an imbalanced data problem. In this work, …
Automated Question Generation And Question Answering From Turkish Texts, Fati̇h Çağatay Akyön, Ali̇ Devri̇m Eki̇n Çavuşoğlu, Cemi̇l Cengi̇z, Si̇nan Onur Altinuç, Alpteki̇n Temi̇zel
Automated Question Generation And Question Answering From Turkish Texts, Fati̇h Çağatay Akyön, Ali̇ Devri̇m Eki̇n Çavuşoğlu, Cemi̇l Cengi̇z, Si̇nan Onur Altinuç, Alpteki̇n Temi̇zel
Turkish Journal of Electrical Engineering and Computer Sciences
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience and resources. Automatic question generation (QG) techniques can be utilized to satisfy the need for a continuous supply of new questions by streamlining their generation. However, compared to automatic question answering (QA), QG is a more challenging task. In this work, we fine-tune a multilingual T5 (mT5) transformer in a multitask setting for QA, QG and answer extraction tasks using Turkish QA datasets. To the best of our knowledge, this is the first academic work …
Packet-Level And Ieee 802.11 Mac Frame-Level Analysis For Iot Device Identification, Rajarshi Roy Chowdhury, Azam Che Idris, Pg Emeroylariffion Abas
Packet-Level And Ieee 802.11 Mac Frame-Level Analysis For Iot Device Identification, Rajarshi Roy Chowdhury, Azam Che Idris, Pg Emeroylariffion Abas
Turkish Journal of Electrical Engineering and Computer Sciences
In cyberspace, a large number of Internet of Things (IoT) devices from different manufacturers with hetero-geneous functionalities are connected together. It is challenging to identify all these devices in an IoT ecosystem. The situation becomes even more complicated when the devices come from the same manufacturer and of similar types due to their analogous network communication behaviour. In this paper, a device fingerprinting (DFP) approach based on a set of combined features from packet-level and frame-level has been proposed. A large number of features has been studied, and consequently, a suitable subset of features has been selected according to gain-ratio …
Design And Implementation Of A Bioinspired Leaf Shaped Hybrid Rectenna As A Green Energy Manufacturing Concept, Kayhan Çeli̇k, Erol Kurt
Design And Implementation Of A Bioinspired Leaf Shaped Hybrid Rectenna As A Green Energy Manufacturing Concept, Kayhan Çeli̇k, Erol Kurt
Turkish Journal of Electrical Engineering and Computer Sciences
In this communication, the novel low cost hybrid energy harvester combining rectifying antenna with the solar cell for feeding the low power energy systems are reported. The bioinspired leaf shaped monopole antenna is designed to work in the most used communication frequency bands such as GSM-1800, UMTS-2100, WIFI-2.45 and LTE-2.65 GHz for the energy harvesting purposes and microstrip low pass filter is also added on the feeding line for the second harmonic rejection for increasing the efficiency of the harvester. The solar cell is placed on the ground plane of the designed leaf shaped antenna for using volumetric space efficiently …
A Novel Hybrid Algorithm For Morphological Analysis: Artificial Neural-Net-Xmor, Ayla Kayabaş, Ahmet Ercan Topcu, Özkan Kiliç
A Novel Hybrid Algorithm For Morphological Analysis: Artificial Neural-Net-Xmor, Ayla Kayabaş, Ahmet Ercan Topcu, Özkan Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a novel algorithm that combines a rule-based approach and an artificial neural network-based approach in morphological analysis. The usage of hybrid models including both techniques is evaluated for performance improvements. The proposed hybrid algorithm is based on the idea of the dynamic generation of an artificial neural network according to two-level phonological rules. In this study, the combination of linguistic parsing, a neural network-based error correction model, and statistical filtering is utilized to increase the coverage of pure morphological analysis. We experimented hybrid algorithm applying rule-based and long short-term memory-based (LSTM-based) techniques, and the results …
Automatic Keyword Assignment System For Medical Research Articles Using Nearest-Neighbor Searches, Fati̇h Di̇lmaç, Adi̇l Alpkoçak
Automatic Keyword Assignment System For Medical Research Articles Using Nearest-Neighbor Searches, Fati̇h Di̇lmaç, Adi̇l Alpkoçak
Turkish Journal of Electrical Engineering and Computer Sciences
Assigning accurate keywords to research articles is increasingly important concern. Keywords should be selected meticulously to describe the article well since keywords play an important role in matching readers with research articles in order to reach a bigger audience. So, improper selection of keywords may result in less attraction to readers which results in degradation in its audience. Hence, we designed and developed an automatic keyword assignment system (AKAS) for research articles based on k-nearest neighbor (k-NN) and threshold-nearest neighbor (t-NN) accompanied with information retrieval systems (IRS), which is a corpus-based method by utilizing IRS using the Medline dataset in …
A New Automatic Bearing Fault Size Diagnosis Using Time-Frequency Images Of Cwt And Deep Transfer Learning Methods, Yilmaz Kaya, Fatma Kuncan, Hüseyi̇n Meti̇n Ertunç
A New Automatic Bearing Fault Size Diagnosis Using Time-Frequency Images Of Cwt And Deep Transfer Learning Methods, Yilmaz Kaya, Fatma Kuncan, Hüseyi̇n Meti̇n Ertunç
Turkish Journal of Electrical Engineering and Computer Sciences
Bearings are generally used as bearings or turning elements. Bearings are subjected to high loads and rapid speeds. Furthermore, metal-to-metal contact within the bearing makes it sensitive. In today?s machines, bearing failures disrupt the operation of the system or completely stop the system. Bearing failures that can occur can cause enormous damage to the entire system. Therefore, it is necessary to anticipate bearing failures and to carry out a regular diagnostic examination. Various systems have been developed for fault diagnosis. In recent years, deep transfer learning (DTL) methods are often preferred in current bearing diagnosis models, as they provide time …
A Deep Learning Based System For Real-Time Detection And Sorting Of Earthworm Cocoons, Ali̇ Çeli̇k, Si̇nan Uğuz
A Deep Learning Based System For Real-Time Detection And Sorting Of Earthworm Cocoons, Ali̇ Çeli̇k, Si̇nan Uğuz
Turkish Journal of Electrical Engineering and Computer Sciences
Vermicompost, created by earthworms after eating and digesting organic waste, plays an important role as an organic fertiliser in sustainable agriculture. In this study, a deep learning-based smart system was developed to separate earthworm cocoons used in the production of vermicompost from the compost and return it to production. In the first stage of the study, a dataset containing 1000 images of cocoons was created. The cocoons in each image were labeled and training was performed using a deep learning architecture, one-stage and two-stage models. The models were trained over 2000 epochs with a learning rate of 0.01. From the …
The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim
The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim
Future Engineering Journal
From the time when the first narrated infections in Wuhan China, in late 2019, COVID-19 has had a substantial peal on human life and health. By the early of 2020, the World Health Organization (WHO) announced the eruption of COVID-19, a public health crisis of international concern. On 11 March 2020, the World Health Organization officially announced COVID-19 a pandemic. The first case was infected in Egypt of covid-19 on Feb 14, 2020 (Gilbert et al., 2020). On 16 March 2020, the Egyptian Government began issuing decisions as preventative courses as part of the country's inclusive plan to cope with …
Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr.
Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr.
Future Engineering Journal
The recent booming in the power network industry inspired a lot of researchers to develop models to estimate the optimum cost of transmission towers. Unlike previous researches which depended on design the tower from scratch, this research depends on collecting actual database from several projects around the globe and applying the well-known (GP) technique to develop a model to predict the tower weight. The accuracy of the developed formula was about 84%. The developed model could be used in early tender stage or to check design economy.
Can Language Models Capture Graph Semantics? From Graphs To Language Model And Vice-Versa, Tarun Garg, Kaushik Roy, Amit Sheth
Can Language Models Capture Graph Semantics? From Graphs To Language Model And Vice-Versa, Tarun Garg, Kaushik Roy, Amit Sheth
Publications
Knowledge Graphs are a great resource to capture semantic knowledge in terms of entities and relationships between the entities. However, current deep learning models takes as input distributed representations or vectors. Thus, the graph is compressed in a vectorized representation. We conduct a study to examine if the deep learning model can compress a graph and then output the same graph with most of the semantics intact. Our experiments show that Transformer models are not able to express the full semantics of the input knowledge graph. We find that this is due to the disparity between the directed, relationship and …
Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona
Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona
Doctoral Dissertations
The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …
Improving The Programmability Of Networked Energy Systems, Noman Bashir
Improving The Programmability Of Networked Energy Systems, Noman Bashir
Doctoral Dissertations
Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …
Halide Perovskites Enable Polaritonic Xy Spin Hamiltonian At Room Temperature, Renjie Tao, Kai Peng, Louis Haeberlé, Quanwei Li, Dafei Jin, Graham R. Fleming, Stéphane Kéna-Cohen, Xiang Zhang, Wei Bao
Halide Perovskites Enable Polaritonic Xy Spin Hamiltonian At Room Temperature, Renjie Tao, Kai Peng, Louis Haeberlé, Quanwei Li, Dafei Jin, Graham R. Fleming, Stéphane Kéna-Cohen, Xiang Zhang, Wei Bao
Department of Electrical and Computer Engineering: Faculty Publications
Exciton polaritons, the part-light and part-matter quasiparticles in semiconductor optical cavities, are promising for exploring Bose–Einstein condensation, non-equilibrium many-body physics and analogue simulation at elevated temperatures. However, a room-temperature polaritonic platform on par with the GaAs quantum wells grown by molecular beam epitaxy at low temperatures remains elusive. The operation of such a platform calls for long-lifetime, strongly interacting excitons in a stringent material system with large yet nanoscale-thin geometry and homogeneous properties. Here, we address this challenge by adopting a method based on the solution synthesis of excitonic halide perovskites grown under nanoconfinement. Such nanoconfinement growth facilitates the synthesis …
Wage Wizard, Jack Davey, Kyle Felip Mondina, Brett Rimmer
Wage Wizard, Jack Davey, Kyle Felip Mondina, Brett Rimmer
Interdisciplinary Design Senior Theses
Wage theft is a severe problem in Santa Clara County, with the Santa Clara Wage Theft Coalition identifying more than 25,000 local wage theft cases as of 20211. In this study we will be addressing the issue of wage theft particularly in the Santa Clara County caregiving industry. Wage theft is prevalent in the caregiving industry for several reasons. First, the industry employs many migrant Filipino workers who are unaware of their legal rights and protections or even the fact if they are experiencing wage theft or not. Second, the sizable undocumented portion of these workers are coerced to lower …
Knowledge-Driven Drug-Use Namedentity Recognition With Distant Supervision, Goonmeet Bajaj, Ugur Kursuncu, Manas Gaur, Usha Lokala, Ayaz Hyder, Srinivasan Parthasarathy, Amit Sheth
Knowledge-Driven Drug-Use Namedentity Recognition With Distant Supervision, Goonmeet Bajaj, Ugur Kursuncu, Manas Gaur, Usha Lokala, Ayaz Hyder, Srinivasan Parthasarathy, Amit Sheth
Publications
As Named Entity Recognition (NER) has been essential in identifying critical elements of unstructured content, generic NER tools remain limited in recognizing entities specific to a domain, such as drug use and public health. For such high-impact areas, accurately capturing relevant entities at a more granular level is critical, as this information influences real-world processes. On the other hand, training NER models for a specific domain without handcrafted features requires an extensive amount of labeled data, which is expensive in human effort and time. In this study, we employ distant supervision utilizing a domain-specific ontology to reduce the need for …
Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis
Barrier Knockdown Test Control System For The Cal Poly Kinesiology Department, Regina M. Chapuis
Computer Engineering
The goal of this project is to design and implement a new control system for the LEDs and buttons on an existing Barrier Knockdown setup in the Cal Poly Kinesiology department. The Barrier Knockdown test is a testing apparatus in which subjects knock down a series of mechanical barriers in one of three patterns. The computer system times their reaction and movement time, and the test as a whole provides students with data to study the phenomenon of Contextual Interference. This system was previously controlled by an old computer setup that ultimately crashed. This project recreates the logic and user …
Dual-Axis Precision Imager, Gary Huarng
Dual-Axis Precision Imager, Gary Huarng
Computer Engineering
The Dual-Axis Precision Imager (DAPI) is a drawing robot that processes images and draws them on a whiteboard. The system has two modes: a Sobel filter mode that finds the edges of the input image with a Sobel filter, and a tri-tone grayscale mode that approximates the shading of the input image with the colors white, gray, and black. The DAPI consists of an Arduino-controlled XY gantry system with a pen mounted on the gantry head, and a Processing IDE program that processes the original image, converts the processed image into gantry instructions, and sends them to the Arduino for …
Mars Prototype Rover Environmental Measurement System, James A. Renick
Mars Prototype Rover Environmental Measurement System, James A. Renick
Computer Engineering
In my senior project, the problem I am trying to solve is how to efficiently design, create, and install an original library onto a Mars prototype rover operating system and to further use that library to integrate a new weather measurement sensor device into the rover system with the necessary software and hardware implementations. This is an important and highly valued problem as many aerospace and other engineering companies utilize rovers and other autonomous systems for important research, explorations, and reconnaissance missions and goals. In solving this problem, I utilized many resources that were available to me such as advisors, …
Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg
Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg
Computer Engineering
This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.