The Large Hadron Collider (LHC) is the world’s largest particle physics experiment. Physicists are most interested in observing rare events. Because the events are so rare, the speed at which data can be acquired defines the effectiveness of the science. There is ongoing development to improve the data acquisition capability of the LHC. A large upgrade of the detector is scheduled in the next few years, known as the High Luminosity LHC upgrade. Many of the chips that will be implemented during this upgrade are not finished with development yet. A specific chip, the RD-53A, is integral to the system, and will not be available for some time. In the meantime, an emulator for the chip which has the same function as the chip and can be used in LHC is being developed at the University of Washington. One important feature of the emulator is recovering data from high-speed asynchronous data. Recovered data could contain glitches or be invalid if it is not aligned with the local clock. This project defines the way by which the recovered data will be stabilized. By oversampling input serial data signals and examining the pattern of serial data, the phase of recovered data can be determined. After determining the phase of the data, the data can be safely used. Detecting the correct phase of the data is crucial for the LHC because it needs to accurately decode every bit of data collected from physical events.

The purpose of this research is to generate immersive, natural-looking environments from geoengineering data that can be viewed on hardware-constrained virtual and mixed-reality platforms. Current mixed and virtual-reality technologies, such as the Microsoft HoloLens, are constrained by limited hardware resources. These constraints set limits on the realism and quality of immersion of virtual reality environments. Thus, no software previously existed to intelligently render immersive 3D terrain on hardware-constrained virtual and mixed reality devices. Through research in terrain generation and 3D rendering, the Viewpoint Generator application was created that can accurately and realistically render 3D environments. To render the terrain, 3D environments generated in Unity, a game rendering software, are pre-processed on a host machine. The 3D terrain is sliced into a grid containing individual slices. For each slice of terrain, a set of concentric panoramas and a skybox are generated. These static components require relatively little power to render. Performance was benchmarked through simulations in Unity and on-device with a Microsoft HoloLens, with a minimum frames-per-second (fps) requirement of 60 fps to prevent nausea induced by slow rendering. These components form the Viewpoint Generator application that can be deployed to hardware-constrained devices, which allows users to explore areas of a 3D environment not previously possible on hardware constrained devices. Applications for the Viewpoint Generator include uses in civil engineering and environmental restoration and visualization. Large-scale environmental projects too large to convey through static 3D renderings or by human imagination can now be explored in an accurate and realistic virtual environment. As the Viewpoint Generator is designed to operate on compact devices, it is easily deployed to remote environments. The Viewpoint Generator sets the foundation for development in procedural environment generation based on geoengineering data, allowing new visual insight into civil engineering and environmental restoration projects.

Satellites require intelligent power distribution systems to manage the loads and sources onboard. The UW CubeSat team required a power distribution system to provide overcurrent protection, current monitoring, and current limiting ranging from 500 mA to 8 A for their satellite. Thus, we researched many different types of current limiting switches and current monitoring methods to find the most reasonable, power efficient, and effective way of designing a power distribution system that would be the best for the satellite. We examined many different solutions to this problem, including off-the-shelf chips, operational amplifier current limiting circuits, and metal-oxide semiconductor field-effect transistor (MOSFET) current limiting circuits. In the end, we found that a chip made by Texas Instruments was the best solution. We then researched and designed a printed circuit board that could be used to test the operation of the chip. After testing the chip, we found that it could limit current in the desired range as well as monitor the current and report it to a microcontroller. With this chip, the microcontroller is also able to turn electric subsystems on and off. This chip design could be used to construct the power distribution system for the cube satellite in years to come.

Our Entrepreneurial Capstone project addresses the challenge of detecting and tracking small drones in a dynamic, ever-changing airspace. Over the past decade, the availability and usage of drones has greatly increased. This has raised concerns that drones will eventually be used to infiltrate the airspace over large venues to cause harm. To detect drones, our team will leverage Echodyne’s state of the art Metamaterial Electronically Scanning Array (MESA-DAA) radar. The radar produces high resolution range-velocity maps, capable of distinguishing and tracking moving objects that are as far as three kilometers away. Our team’s primary goal is to develop a network of MESA-DAA radars that can reliably detect objects entering a designated airspace. Furthermore, our team hopes to provide an intuitive user interface able to map the path of objects within the airspace. Our team’s research will focus on four primary areas: (1) developing a graphical user interface to display the location of multiple objects in real time, (2) applying a Kalman filter to estimate the current and future trajectory of detected objects, (3) developing a network of multiple MESA-DAA radars to generate a 360-degree view around an airspace, and (4) optimizing the current constant false alarm rate drone detection algorithm. The project will use the C programming language to achieve high speed/low latency analysis of the data and the Java programming language to create the user interface. Our research has significant implications for providing the first relatively low cost method for detecting and monitoring the location of drones in a large, dynamic airspace.

The University of Washington CubeSat program needs a space environment simulator to test their satellite. This was done by simulating the magnetic field and light environments of low-earth orbit. We have accomplished this through the construction of a 3-axis Helmholtz cage and sun simulator. The cage is used as a testing rig for a small satellite's, DubSat-1, attitude determination and control systems. The cage is large enough to fit a 3U cubesat (30cmx10cmx10cm) inside and fully cancel Earth's magnetic field, in addition to generating an arbitrary magnetic field vector of the magnitude expected to be found in low-earth orbit. The sun simulator generates a sun vector over the entire sphere within 10 degrees of accuracy using a strip of LEDs. The LED strip is mounted on the cage and a motor is used to rotate the strip around the cage to change the angle of the light. The Helmholtz cage is controlled using feedback from a magnetometer placed inside the magnetic field of the cage. Based on the data from the magnetometer a control loop is used to control the current through the coils to adjust the magnetic field strength to its desired value.

UW Solar is an interdisciplinary student-led organization focusing on developing solar energy on the UW campus as well as in the greater Seattle area. Our research concentrates on performing feasibility studies for stakeholders interested in integrating solar energy on their property, both for existing buildings and sites. We are involved in the entire process of the solar project: feasibility studies, initial design, grant applications, construction, and commissioning. Throughout several projects, we have been able to extensively explore different development strategies for solar projects with various sizes and restrictions, the vast environmental benefits of solar energy, and how to financially model a solar array and make it feasible. To date we have completed two solar projects, and we are working on multiple projects right now. We would like to highlight our recently completed project: Clean Energy Institute Testbeds installed on UW Residence Halls. This is a 105 kW system distributed on Alder, Maple, and Elm halls. The project is currently completing the commissioning process and will begin gathering data in April. During the design phase of the project, we researched the suitable components of the solar system, the eligibility of applying funding from various sources and helped to coordinate between the stakeholders (HFS) and the contractor (Artisan Electric). In the near future, this testbed will be used for renewable energy and power electronics research on behalf of the Clean Energy Institute and the Pacific Northwest National Laboratory.

The objective of this project is to develop an affordable (optimally less than $200 to manufacture), 4G/LTE touchscreen mobile phone in the shape of a circle. This will be accomplished by learning how to gather and assemble phone parts, design and solder printed circuit boards (PCBs), and program and test a custom phone. We will thereby apply concepts of communications, embedded systems, software programming, and PCB design. So far, we have built three different phones with various types of screens, processors, speakers, microphones, antennae, and more to compare the prices and performance of each phone and part. The ultimate intended outcome of the project is to build a circular phone that has all the features of a rectangular phone and more in terms of hardware, software, appearance, and usability. The desired performance specifications for the phone are that it can make and receive calls, create and receive SMS messages, and provide notifications via a speaker, buzzer, or any combination thereof. The idea for this project was originally conceived by dTOOR’s founders (prior to incorporation of the company) after they had grown frustrated with the bulkiness rectangular phones. They observed that rectangular phones had become the norm, but such phones were impossible to fit comfortably into women’s pockets and they all tended to look the same. As a result, dTOOR’s Cyrcle phone came into development. The uniquely-shaped Cyrcle phone is devoid of those troublesome corners that rectangular phones have, thus making it easier to carry around, much like an accessory. The prototypes for the phone are definitely brighter and more fun to carry around than other phones and they have successfully attracted a non-rectangular market. These prototypes use traditional, rectangular PCBs and so now, the next challenge is to build the Cyrcle with custom, circular PCBs.

With the expansion of the lighting industry, there has been an increase in LEDs being used in new infrastructure. Comparing with incandescent and fluorescent lights, LEDs are more energy efficient, require less maintenance, and are compatible with the internet of things. However, troubleshooting a failing LED is a tedious task for an electrician, and there are not good ways of diagnosing problems with a LED. A probable solution is a handheld device that is capable of measuring multiple lighting parameters such as temperature, luminosity, color temperature and flickering percentage. This project uses the principle of photometric testing and analysis, the theory of Black Body radiation in color temperature measurement to collect data from the luminosity, temperature, and RGB sensors. The data is used to compare with the manufacturer’s performance standards and real time data of the sensors is displayed on LCD screen. Electricians can pinpoint the issues with an LED if one of the lighting parameter does not match with the manufacturer's standards. In the future, this system will expand to other types of smart devices such as switches, dimmers and will allow user access through an application on a smartphone.

Recreational outdoor winter activities on national forest lands are enjoyed by hikers, skiers, snowshoes, and snowmobilers. These activities come with the risk of being caught in an avalanche. It’s the number one cause of death on forest lands in the United States. Recreationalists are highly encouraged to wear avalanche transceivers. These devices transmit a beacon to be used in locating someone caught in an avalanche. Avalanche survival greatly decreases beyond 15 minutes because of asphyxiation and trauma. Professional Search & Rescue (SAR) teams can rarely arrive within this time limit, but locating a victim after an event is necessary. We will design a portable avalanche beacon detection device that can be attached to an Unmanned Aerial System (UAS or Drone) and can be carried by a SAR team into the field to locate victims. The SAR team can designate a search area via a user interface. The UAS will search this area for the victim’s avalanche transceiver frequency (457 kHz). The sensor attached to a UAS will determine signal location. This location information will be sent back to the rescue team. UAS application increases the safety of the SAR team given additional rescuers are not put in a high-risk avalanche path where another avalanche could occur. Our sensor presents challenges in integrating the payload into a UAS embedded system and user interface while maintaining realistic power and flight capabilities. Our initial customer is Seattle Mountain Rescue, a non-profit organization, so our product must be as cost-effective as possible. In the future, we hope the technology can be used on smaller, more portable UAS’s by all outdoor recreationalists such that at the time of accident they can immediately locate their friends, significantly increasing their chance of survival.

Electric vehicles have gained attention in recent years as an environmentally friendly alternative for conventional, gasoline-fueled vehicles. While internal combustion engines power gasoline-fueled vehicles, electric vehicles use electric motors or batteries for propulsion. It is true that electric vehicles produce little to no tailpipe emissions and, overall, produce fewer pollutants than comparable gasoline-powered vehicles. However, when comparing the total environmental impact of electric vehicles to their gasoline counterparts, it is important to consider the associated impacts from the electricity grids from which they glean their power. In the United States, modes of electricity production vary by geographic location and include coal, natural gas, petroleum, nuclear, hydroelectric, and renewable sources. The purpose of this research has been to understand and quantify these environmental impacts and communicate them in an accessible manner to K-16 learners. To date, only the greenhouse gas emissions of electric vehicles have been quantified in such a way, providing equivalent miles to the gallon compared to gasoline vehicles by state. Our research efforts have taken this comparison one step further by capturing equivalent emissions of lead (Pb), land usage, and water usage of electric vehicles for every state in the U.S. While useful in and of itself, this information has been embedded in clickable maps, various multimedia, and exhibits for K-16 audiences using principles of exhibit design that allow a participant of any age to understand and absorb key principles surrounding electric vehicle usage in the United States. Effective exhibit interactives emphasize the engagement of all five senses through physical activity and stimulate visitors both intellectually and emotionally. Our exhibits and presentations have been carefully engineered to convey factual and intuitive information to K-16 students in an inviting, exploratory, and accessible manner.

Quadrature amplitude modulation (QAM) is a form of modulation in which two signals, differing in phase by 90 degrees, are modulated and summed together in order to create a final output wave. QAM is often utilized in radio communication systems to transmit data. The objective of this project is to develop a 16-QAM communications system on an X310 Universal Software Radio Peripheral (USRP). This system would provide a high data rate communication line for the usage of space-ground links. The applications of such a waveform would allow for massive transmissions of data such as ultra-high-definition video or fast internet. The development of the product will begin with developing a simulation of the system using GNU Radio. After the simulation has been successfully developed, work will be begin to implement the design onto the X310 device. This will be accomplished by using GNU Radio or a hardware description language (HDL) such as Verilog. Testing will take place in order to ensure that data is being properly communicated between the motherboard and daughterboard. It is our hope that our communications system will improve the communication between space and ground centers.

We are UW Smart USB Charger Team supervised by Plugable Technology and a UW EE faculty mentor. The main objective of this project is to design and implement a Smart USB charger that has five USB ports. It is called “smart” because the charger will be able to charge the higher priority phones at almost full rate before moving on to lower priority phones. With that function, this USB charger will fully charge several phones much faster than traditional USB chargers having only a 5V 3A power supply. However, there is no such five ports USB charger in the current electronic device market, so we see the important implications of solving this problem. What our team will have done by the day of our Symposium presentation is to implement the priority charge behavior module using C language and an Arduino Mega Board which has a microcontroller inside. The challenges of the task are that the actual charging behavior of different devices is often unpredictable or sometimes disappointing and the devices themselves decide how much current to draw and manufacturers have not settled on a single standard. Therefore, our module should be able to select the best charging mechanism for each of different devices while supporting priority charge. To do this, it requires us to test our module with as many different devices as possible and to collect data for future references. The other goal is to make the product as low-cost as possible: We will use lowest-cost microcontroller with sufficient I/Os to control all ports and lowest-cost external components for port power control. Finally, if more time is allowed, we will try to design and implement a PCB.

In collaboration with Booz Allen Hamilton (BAH), our Entrepreneurial Design capstone project addresses the challenge of providing continuous operation to an underwater remotely operated underwater vehicle (ROV), utilizing wind power. The main goal of this project is to study the feasibility of powering ROVs with renewably generated power. The project consists of system integration of wind turbine, generator, battery and control system with a buoy platform which will be connected to an underwater ROV through a tether. Our team’s role is to (1) Identify generator and battery options to connect to the wind turbine prototype provided by BAH. (2) Determine power storage requirements for an 8 hour operation of the ROV. (3) Develop and build prototype power management system to use harvested wind energy to support the battery. (4) Develop softwares packages that collect data on turbine and battery performance, and power consumption during operation. Our current research has been focusing on determining desired power requirements, designing individual subsystems circuits, and selecting off-the-shelf components accordingly. The project will be able to produce a on-buoy wind power system prototype that delivers 200 W average output power to the underwater ROV. This ROV will be at least at a 100 ft of depth along with a 5 V and a 9 V output rail for micro-controllers that enable control system packages to monitor power consumption and give data for onshore analysis. Our research has potential implications for improving access to the underwater domain for a prolonged period of time, including low-cost maritime sensing and deployment applications and military training and simulation applications.

The purpose of this study is to effectively measure and estimate the health impact of common sources of artificial lighting that humans are exposed to at night. To compare the impact of many different types and intensities of artificial light, we have developed an approach for analyzing the profiles of these light sources that evaluates them in terms of the full moon and the way in which the melanopsin photoreceptors in the human eye respond to a full moon. Melanopsin photoreceptors play a key role in regulating circadian rhythms and biological timing in all systems of the body. At an evolutionary scale, natural moonlight is what humans are adapted to, and by comparing full moon exposure (FME) to artificial light source exposure in the context of how much is absorbed by melanopsin photoreceptors, we can understand how unnatural different devices and light sources are at night and compare their relative impact on circadian rhythms and sleep health. The results of this study show that many common electronic devices easily exceed 5X a full moon exposure and can reach as high as 100X. Ambient lighting in the home, from light sources ranging from incandescent to LED deliver well over 100 full moons of exposure at recommended ambient lighting conditions. The implication of these results is that most devices and light sources disrupt normal sleep rhythm in some way and could lead to a variety of health concerns if not properly managed. Individuals can use this data to adjust their light exposure at night, to make adjustments to urban lighting in cities, and to inform architects and designers to light residential spaces in a way that minimizes health risk.

Safety precautions are only effective when implemented properly. This is a major obstacle when using wearable devices to promote workplace health and safety. User compliance is a serious concern: Is the user using the device and is it worn as intended? Monitoring user compliance using electronic sensing systems faces limitations. The systems must be cost effective, small, and fit the form of the wearable device all while maintaining enough power to be beneficial. This research monitors compliance in the proper wear of safety eyeglasses within these limitations and constraints. Specifically, information on safety eyeglass orientation and location on the head is gathered continuously using a hall effect sensor mounted on the glasses themselves and a magnet mounted on the user’s ear. Tests on six different users (including both male and female adults) show that four different positions (on the bridge of the nose, on the tip of the nose, on the forehead, on the top of the head) of the glasses can be detected for each user and four different motions, all beginning in the proper ‘on’ position on the bridge of the nose, can also be detected. The overall error rate for data sets collected among six different users is less than 10% and error rates within any one user did not exceed 25%. Collecting both transient motion and steady-state position data minimizes error rates for understanding user compliance. These preliminary tests demonstrate the viability of using these safety glass monitoring systems for not only understanding where the glasses are at any point in time but also how they got there. This information is useful to not only capture non-compliance but also to understand behavior well enough to support effective measures to increase compliance (of wearing safety glasses when they are needed).

For more than three decades, the innovation of cochlear implants (CI) has improved the lives of patients who have trouble hearing sounds. Using the technology of signal processing, the device can provide electric sound to patients at various frequencies. One thing cochlear implant patients have trouble with is the ability to perceive music. Cochlear implants can provide good speech performance but lack the ability to encode music in a better way. Our research is designed to provide the ability for patients to enjoy music through its three facets: rhythm, pitch, and timbre. The purpose of our study is to investigate pitch coding in cochlear implants which is important for music and speech and the quality of life for CI patients. The ultimate goal of our research is to improve sound-processing in deaf or hard-hearing patients all over the world. We will have determined how to deliver the best acoustic simulations of cochlear implants to study pitch coding and identify the ideal combination of carrier type frequency, channel and envelope that will deliver optimal music perception of any sound entering the cochlear implant. Features will be extracted from the simulated sounds to investigate spectral and temporal coding in cochlear implants. This will help in finding new ways of processing music and speech in cochlear implants for the benefit of its users.

Many embedded systems employ the use of dedicated programming hardware called a programmer, or run on top of an operating system that can support many ways of accepting new programs. However, wireless programmer support is uncommon and an operating system introduces overhead. This presentation describes the design of an embedded system with wireless programming capabilities without the use of a programmer or operating system. New code is sent to an on-system wifi transceiver and then via a serial port to the microprocessor, which writes to its own flash memory and stores the program, resets, and runs. The wifi connection is also used for general communication to a host computer or other systems, depending on the application. A secure handshake method was also needed to ensure the device is never unintentionally reprogrammed by regular data packets. The wireless system was then used to control a robot platform with a skid steer drive and motor encoders for a mobile robot that can be reprogrammed without any wired connection to a PC. This wireless programming solution enables developers to test autonomous code with quick code testing cycles, minimal overhead, and requires no conventional programmer.

The goal of this project is to design a faster and more efficient motion controller for the leaf collimator that is used to shape a neutron beam around a tumor for use in intensity modulated neutron radiation therapy. The system currently in operation was developed in the 80’s and is too slow for new treatment techniques we plan to support. We started with familiarizing ourselves with the Galil motion controller and the Experimental Physics and Industrial Control System (EPICS) software to control 40 motors that will adjust the position of the collimator leaves within an accuracy of 2 mm. Because we augmented an existing system, there are some system aspects that could not change and needed to be worked into our design: the 40 motors need to be driven manually with analog feedback and the overall mechanical setup should remain mostly the same. Additionally, we rewired the system to accommodate bipolar power supplies in order to half the number of wires used in the gantry, allowing us to save on space and increase the ease of future system maintenance. This was accomplished by configuring diodes in parallel with relays that allows us to control the direction of the current, which in turn controls the rotation of the motors. Since our system’s internal components are heavily exposed to radiation, we implemented the diodes on a printed circuit board to ensure that the system upkeep and component replacement is manageable. Finally, we updated the existing Extensible Display Manager (EDM) user interface so the radiation therapists and technicians can see real-time leaf locations and interact with our motion control system. The final deliverable is a complete installation of our new fully tested system inside the the gantry.

Progress in genomics research has led to increasing demands in scientific computing, especially in the field of DNA sequencing. As sequencing technologies have matured over the past decade, the rate of growth in data has outpaced the advancement of sequential processing devices such as CPU-based systems. Field-Programmable Gate Arrays (FPGAs) are reconfigurable computing devices that can be highly customized to suit specific applications, including genomic data processing. In contrast to CPU-based systems, FPGAs are parallel processing devices capable of carrying out computations more efficiently. Additionally, newly emerged memory architectures have greatly improved the random-access performance in genomics applications. One of these is the Hybrid Memory Cube (HMC), whose internal architecture incorporates fast serial communication links and efficient controllers that raise the memory bandwidth limit of the FPGA when compared to traditional DDR DRAM. In our research, we harness the high random-access rate of the HMC and the parallel computing ability of the FPGAs to establish a Bloom filter, an efficient data structure used to confirm membership in a group. The Bloom filter can be utilized to discard erroneous reads generated by normal sequencing techniques and can further relieve the need to account for false information in downstream systems. We constructed a filtering pipeline on the development board that houses a Xilinx Kintex FPGA and the HMC, using only one interface port and 2 GB storage of the HMC. The system is capable of processing 1 billion DNA segments with a maximum length of 64 base pairs. The computing ability of the FPGA along with the high random-access rate of the HMC are highly desirable when processing large amounts of genomic data.

Zinc pollution is a large problem in underdeveloped countries with mining industries. Leaching of brass and galvanized iron can add substantial amounts of zinc into water resources. Furthermore, high zinc concentration is usually indicative of lead and cadmium, which, when once accumulated in the human body, can negatively affect the immune system. Currently, there are no rapid, inexpensive methods to determine the concentration of zinc in water. The sample is usually sent to a lab and analyzed using sophisticated and prohibitively expensive instruments. Our goal is to create an affordable and easy-to-use diagnostic tool using Saccharomyces cerevisiae—a yeast commonly used in industry. By designing a gene circuit that connects a zinc-sensitive promoter for Green Fluorescent Protein (GFP), we hope to engineer a strain of yeast that will give a green fluorescent output of different intensities when grown in different concentrations of zinc. After building and testing different strains of yeasts-- each using a different zinc sensitive promoter, we found that there was no significant variation in GFP output between different concentrations of zinc and between different yeast strains. In addition, after comparing the results with a wild-type control, we also found that our recombinant strains are not much better at detecting zinc than the wild type strain. For the next steps of this project, we will continue to build gene circuits involving other zinc sensitive genes. Once a few genes are identified as being suitable for our purposes, we will focus on amplifying and fine-tuning GFP expression as well as replacing the GFP with that a color output that can be detected by the naked eye.

Quantum information research often require lasers to deliver energy to devices and to acquire data. The goal of this project is to create an inexpensive and easy-to-build tool to measure and control laser power to support our lab’s quantum information research. The tool interfaces with our lab’s existing data collection and analysis modules. A standalone module is also present for adoption outside of our lab. Some of the intended applications of this tool are the generation of saturation curves for quantum emitters, and performing photoluminescence excitation spectroscopy on samples, both of which require precise control of laser power. The system uses a National Instruments data acquisition device to record a voltage generated by a laser power sensor. The software module also interfaces with an Arduino microcontroller, which can be used to adjust the laser’s power. The software module allows the user to set, monitor in real-time, and record laser power from a graphical user interface. The data taken utilizing the developed power controller will advance the development of quantum computation hardware based on single photons and quantum spins. Quantum computers are theoretically predicted to solve certain classes of problems that are currently unsolvable on today's computers, including the factoring of large numbers which is at the heart of current secure communication protocols.

Diamond magnetometry enables the measurement of small-scale magnetic fields using nitrogen vacancy (NV) defect centers in diamond. Nanoscale magnetic field detection has a range of applications in biology and chemistry, such as imaging of magnetically-tagged molecules for the study of biological processes. Diamond magnetometry uses optically detected magnetic resonance (ODMR), a technique which combines radio frequency (RF) magnetic fields with optical excitation to control the defect spin. To detect DC magnetic fields, typically continuous wave RF and optical fields are used. However it is well-understood that continuous optical excitation limits the sensitivity of the technique. This project demonstrates a pulsed ODMR system executed in LabVIEW, in which optical initialization and radio-frequency spin control are staggered in time and compares the performance against the continuous wave execution. This program will enable more sensitive measurements of biological systems where orientation matters.

The purpose of this project is to develop an automotive “head unit” entertainment system which can be installed into existing vehicles. It employs several connectivity technologies such as bluetooth, Wi-Fi, cellular, USB, and radio. It is also integrated with the vehicle’s data bus for indoor temperature and fan speed control. It includes features for sending or receiving texts and calls from a bluetooth connected phone, playing music from multiple sources, Point of Interest search and navigation around local areas or to a specified location. In addition, it has over the air update and upgrade capabilities, allowing additional content to be added to the system after deployment. Users can interact with the system through both voice and touch inputs. This system is being built with a Dragonboard 410C at the heart, running a modified version of Android. Connected to this board will be a 7" touchscreen, a CAN bus controller, a software-defined radio, and a cell modem. Included inside the board is a bluetooth module, a WiFi module, and adequate internal storage. The voice recognition technology is supported by VoiceBox’s cloud platform - VIBE. This project was developed in collaboration with VoiceBox Technologies.

Fizikl is a company that uses UAVs to count inventory in warehouse. The goal of the company is to replace the manual inventory counting method that most of the companies uses. Our team worked on the barcode detection and scanning process, as well as the centering of the UAV. The first step to achieve autonomous warehouse is to pinpoint the UAV's waypoints and designate its flight plan. Then, the UAV will take pictures upon arrival at each destination point after centering itself according to the Aruco codes. The distance between the camera and the shelf is carefully set to a fixed value to capture all the items on the shelf. The pictures will then be sent to a ground station where barcode extraction and counting will happen. Th barcode scanner algorithm will also output the location on the pictures where it finds barcodes. We have optimized the barcode detection process by testing the barcode detection algorithm with different qualities of barcodes. We have experimentaly determined how many pictures the UAV should take at a certain destination. We have successfully built a inventory counting system to achieve autonomous warehouse.

Variation in gene expression can be used as a way to test for or track the progression of large scale diseases. Although existing methods to evaluate expression such as RNA sequencing or microarrays are widely used in medical research, clinical application is limited because of time and cost. By monitoring gene expression levels clinicians could perform earlier diagnosis, evaluate therapeutic efficacy and predict recurrence of disease. Gene profiling by a linear DNA-based molecular circuit to classify samples with varying gene expression patterns would provide a novel approach resulting in a rapid, cost-efficient and reliable alternative to existing gene expression diagnostics. Previous work done on the project shows that multi-stage strand displacement cascades can be engineered to perform catalytic signal amplification with high sensitivity, amplification and specificity. In the Seelig lab, already a linear DNA molecular classifier has been engineered to distinguish between bacterial and viral infections and could correctly label 94.0% and 80.5% samples respectively. Although the previous experimental data supports the mythology of the classifier, it is not an ideal representation of clinical use. For that reason, I am working to scale up the molecular circuit by using RNA derived directly from human cancer cell lines to see if the classifier can robustly identify the originating cell line. I will take amplified RNA from each cell and add it to the classifier. The accuracy of initial binding will be analyzed by a fluorescent readout measured across both channels, corresponding to successful strand displacement. Upon demonstration of rapid, cost-effective and accurate classification of human cancer cell lines I then hope to translate this research into classification of clinical samples with the goal to adapt the current methodology into a point of care diagnostics device.

An organism’s ability to sense, interpret, and respond to its environment is an essential requirement of life itself. At the cellular level, this process of connecting signals to behaviors is governed by a diverse set of mechanisms such as mitogen activated protein (MAP) kinase cascades, which are broadly conserved across animals, plants and fungi. Alterations to these connections that arise from evolution or disease can have significant phenotypic effects. MAP kinases transmit signals by colocalizing with a target protein and altering its structure through phosphorylation and thereby producing downstream behavioral changes in the cell. Engineering novel phosphorylation triggered interaction domains will allow MAP kinase signaling networks to be rewired to correct pathological dysfunction or to generate novel responses to environmental signals. We intend to use an engineered protein scaffold with a phosphorylatable motif and an occluded binding motif, which was designed by collaborators in the Baker lab, to create a phosphorylation triggered interaction motif in Saccharomyces cerevisiae. By rewiring the S. cerevisiae mating MAP kinase cascade to phosphorylate this scaffold and incorporating a yeast three hybrid output, we hope to demonstrate the function of this new class of interaction domains in vivo. We hypothesize that upon phosphorylation, the scaffold will undergo a conformational change revealing the previously occluded binding motif, allowing another protein to bind and produce downstream effects. Such novel interaction domains will serve as a “toolbox” to allow the rewiring of MAP kinase cascades in any context in which they naturally occur. This approach could be used to fix pathological miswiring of MAP kinase cascades that contribute to anomalies of development or diseases such as cancer. Additionally, the creation of new connections using these interaction domains could be utilized to engineer organisms or cells with useful functions such as plants with enhanced defensive traits or cancer targeting T-cells.

The nitrogen-vacancy (NV) center is a defect in diamond formed by replacing two carbon atoms by a nitrogen atom and a vacant lattice site. The NV center is a promising qubit candidate for quantum information, and its sensitivity to magnetic fields allows it to measure these fields. Due to the lattice structure of diamond, the NV center can have one of four possible orientations. For quantum information and sensing applications, control over this orientation is desirable, and would enable the production of better quality devices. Ab initio models predict that the NV orientation can be controlled through annealing, however the model depends critically on the barrier heights for defect diffusion which are difficult to calculate quantitatively. Preliminary data from our group demonstrated that heating the diamond up to high temperatures (> 1000 C) can sometimes cause single NV centers to appear, disappear, or change orientations. However, information on the frequency at which these changes occur, and thus information on barriers for diffusion, were unknown. Here we conduct thousands of single defect studies to determine these relevant rates as a function of the annealing temperature and time. While NV centers fluoresce under green laser light, restricting the polarization of this light only allows NV centers in that direction to fluoresce. By taking multiple confocal images at several polarizations, two families of orientations can be distinguished. These images are taken before and after the annealing process and then are compared using customized computer software to gather statistical data on the dynamics of single NV centers.

Many mainstream video games involve difficult game levels and challenges such as boss-battles and puzzles, leading some gamers to become frustrated as they struggle to advance to the next game level. In some cases, this frustration may lead gamers to give up on playing the game entirely. Although walkthroughs for video games are available online to help gamers when they get stuck, the gamers need to manually locate where they are in the game to obtain appropriate hints. Not only can manually looking for hints be inconvenient and time consuming, but it can also expose gamers to spoilers. We hypothesize that we can improve the gaming experience by providing gamers with a system that can automatically determine their current location in a game and serve up a link to a walkthrough video that demonstrates how to proceed. The goal is to queue up a video from the spot where gamers are stuck without the gamer having to know the level, scene, and time in the walkthrough for the hint. Our proposal is to use Deep Neural Networks (DNN) to learn the association of location and appearance pattern in the game(s) in order to locate the current game level. We will use recorded game play to train a DNN classifier for the games INSIDE and Portal, and evaluate the performance of the classifiers with gamers. Our goal is to design a system for NVIDIA Shield™ that provides gamers with help when needed. We hope by providing gamers with such a system, we improve the overall gaming experience and fewer players will give up on a game.

Companies care of their image in the customers’ mind, then offer customer service to understand and take care of customers’ need. However, customer services seem to be overwhelmed, while they have to serve an increasing huge number of customers. Companies have to pay a lot of expenses for employing labor, while customers are not taken care of well enough. Customer Ticket Classification project offered by Tupl Inc. delivers an algorithm that takes in customer queries, then categorizes and generates responses to those queries. In detail, the algorithm classifies thousands of customers’ messages into different categories and automatically responds to these messages based on the detected categories by using data science and machine learning. In detail, the project employs new data science tools such as Spark and Zeppelin to improve effectiveness. Thus, this algorithm can help companies save man power or labor hours and expenses in operating customer services.

Real-time quantification of pollutants in urban and non-urban environments has far-reaching prospective benefits for our society. Such a possibility could provide instantaneous detection of hazardous chemicals, identification of areas that require air quality restoration, or estimation of agricultural effectiveness. However, currently dynamic and efficient platforms to perform quantification do not exist and only a few static sensors are deployed in sparse locations. While several mobile devices have been constructed, they are typically large, expensive and imprecise. In our project, we address this problem by building inexpensive, mobile multi-sensor devices. Each of these devices was designed to support an array of inexpensive sensors that measure the surrounding air quality and send the information in real-time to either a mobile phone or server-side application. We designed the device such that all the parts are of the lowest cost and least energy consuming as possible. To enhance the reading performance of the device, we are implementing a neural network, based on the insect olfactory system, to calibrate, recognize, track and learn signatures of scents. Early experiments show that the neural network is capable to discriminate and track more precise values of contaminants, and we are currently working on integrating sensor data from multiple devices to show the quantification of pollutants on a heat map. Overall, this project showed many possible ways to make air quality data useful and accessible. It is expected that the scale of this project can be increased by increasing the number of deployed devices such that more data can be obtained and used to train the neural network while more communities can be informed about their surrounding air quality.

Hypertension is a life-threatening issue affecting 31% of American adults and demands close monitoring. All conventional blood pressure (BP) devices are cuff based and are inconvenient to wear and fail to provide continuous BP. There is a need for a convenient, miniaturized, and cuff-less blood pressure (BP) monitoring device. During the past several years, studies have shown that BP is correlated to pulse transit time (PTT) obtained from electrocardiogram (ECG) and photoplethysmogram (PPG) or radial pulse. This project has successfully demonstrated that same side ECG and PPG can be used to obtain PTT that correlates inversely with BP, hence paving the way for a continuous device. We have shown two possible configurations for our device which differs in placement of sensors. The first device is designed with contact-electrode ECG and PPG sensors, located on the bicep and the ear; while the second one, which is a wrist-worn device, consists of a noncontact ECG circuit and a piezoelectric pulse sensor. The measured PTT is regressively correlated with BP and a regression coefficient between 0.3-0.9 is obtained. To further improve the accuracy of the BP device, the research work also investigates different algorithms that can be used to estimate BP. Online data available in Physionet database has been used to verify accuracy of popular regressive algorithms and effect of inclusion of other physiological factors like heart rate (HR) and artery thickness in the relationship. Our results indicate that inclusion of HR improves the correlation between PTT and BP. Results of device configuration and algorithm improvement obtained can enable next-generation devices, providing essential continuous BP monitoring off-the-clinic for hypertension patients as well as healthy people.

The smart parking group has developed an Application Program Interface, or API, with analytics tools to support analysis, policy development, and innovation by Seattle Department of Transportation, or SDOT, and third party solution providers. An API is a set of routines, protocols, and tools for building software applications. It specifies how software components should interact and is also used when programming graphical user interface components. Python computer code is used to make calculations and place relevant data in a public database, where it can be remotely accessed for applications by the API. To demonstrate our API’s functionality, the team is currently developing a visualization tool that overlays analytics produced by the API on a map. The analytics algorithms we will implement integrate a wide variety of data streams available through our collaboration with SDOT. The API will provide the needed support for apps that deliver a dynamic summary of information that can help citizens determine the best and worst places to find parking in Seattle metro area, at specific times and dates.

We live in a world driven by efficiency, optimized by technology. In this project, our team is developing specialized commercial smart home products as we investigate their efficacy. With the industry’s unprecedented growth over the past several years, we believe that smart home technology will quickly become a cornerstone of today’s automation paradigm. To focus our scope, we are working with an industry leader: Wally, who has already launched a successful commercial package. Our job is to ideate, design, and create prototypes for new sensors that will augment and enhance their existing product. We are focusing on utilitarian applications of smart sensors. As such, the first product we are developing is a sensor that detects various gas leaks, ranging from volatile organic compounds to natural gases. The second product we are developing is a water pressure sensor that measures flow rate throughout a house. Both sensors will connect to a cloud infrastructure and data is sent to a mobile application where users will be alerted in real-time and can view analytics. Additionally, both sensors will interface with other automated products such as shutoff valves. If our research and development goes as planned, we hope to add both products to the existing Wally line and release them commercially.

Exposure to abnormally high levels of estrogenic compounds can trigger dramatic developmental and sexual deformities in fish and wildlife. For instance, bisphenol A (BPA), found in plastics, is a common pollutant that threatens the natural environment and human consumers by acting as an endocrine disrupter. However, testing for these estrogenic chemicals requires samples to be processed at a laboratory with expensive equipment. Cell biosensors that are engineered to detect pollutants and produce a visual response are a low-cost, tunable, and highly sensitive alternative. Here, we show our work to expand access to estrogenic pollution detection by genetically engineering Saccharomyces cerevisiae, brewer’s yeast, to produce green fluorescent protein (GFP) until it detects ß-estradiol, a human estrogen. Our biosensor expresses a CRISPR transcription factor (CTF) which includes an estrogen receptor and mxi1 repression domain, coupled with a guide RNA that targets the promoter for GFP. We observed with a cytometer that upon ß-estradiol induction, the CTF-expressing yeast demonstrated heightened GFP expression and larger, possibly un-dividing cells. We hypothesize that our CTF is reducing cell growth and division rates, thus increasing the concentration of GFP molecules per cell, and show our work to investigate this prediction. In the future, we plan to tune the sensor to repress fluorescence only when reaching a hazardous concentration of  ß-estradiol. In addition, we will measure our biosensor’s ability to detect similar estrogens such as BPA, in the hopes that it can function as a universal estrogenic sensor.

We have evaluated the viability of a system for detecting auxin with a yeast culture using the red buildup of P-ribosylformyl glycinamidine as a reporter that can be used to reliably identify auxin in water without the need for advanced equipment. To accomplish this we have fused an IAA17 protein to an ADE2 enzyme with a linker that preserves function, then transformed that into a yeast strain that lacks native ADE2 and has an Fbox AFB2. We plated these on adenine deficient agar with various concentrations of auxin to test for sensitivity. As controls, we plated basic strains w303a and w303alpha and found that the ADE2-lacking w303alpha still needs a little bit of adenine or it will not grow at all. We tested two different types of media, YPD and SC with minimal adenine concentration, both of these have just enough adenine to keep the yeast alive but still induce the red color. We conclude that the method of detecting auxin via the degradation of an IAA17 tagged protein is a viable strategy, but that using ADE2 as our target enzyme presents complications when considering the ultimate goal of our project. The reporter is not simple to use as a very specific concentration of supplemental adenine is required to allow growth but still induce the ADE pathway. To mix this media would require high-precision equipment usually available only in a lab. This problem can be solved by changing the reporter to allow the yeast to be functional in any media, which will be our next project.

Our group built a drone that will unfoul utility lines. In other words, it removes shoes tossed over and around power cables. The current method of removing shoes of powerlines is expensive and dangerous for the workers involved. This is why we see so many shoes polluting our lines. We built a quad-rotor drone aircraft fitted with a special cutting device that is encapsolated in a specially engineered shell. Our main sensor is a camera and the visual inputs are used to identify the shoes on the utility line. The drone also has an extendable arm that cuts the shoelace. At the end of the arm is the boom which is a shelled device with a cutter inside. This project involved robotics, control systems, and computer vision. There are different versions of the drone, each one differing in the level of autonomy. The first version is human pilot operated:; the user controls the drone’s altitude, orientation, and cut. The other version is semi-automatic; the human takes the drone to the shoe's location. The drone's computer vision system which recognize the shoes and laces. It will then cut the laces itself and fly back to the user. 

The characterization of a genetically modified strain of yeast is a tedious and laborious process, which in standard cases, may require upwards of one hundred twenty hours of regular attendance to a single characterization experiment. This is common when developing a novel genetic circuit with several distinct parameters and states. The state-of-the-art method involves loading the yeast strain into a proprietary lab-on-a-chip to perform the strain characterization. Our method, however, improves upon the state-of-the-art method by being cheaper, more flexible, and more integrated into existing lab equipment. We employ a CNC-milled polycarbonate microfluidic chamber with mix, temperature, and inducer and sampling controls. This chamber connects directly to a flow cytometer while running, affording real-time, fully automated strain characterization. We have found this apparatus, the affectionately-titled Cytopendix, to be suitable for sustaining yeast cultures and permitting real-time chamber sampling with the flow cytometer. The nature of its simple design and the speed of CNC milling has granted us significantly shorter design iteration periods than current lab-on-a-chip methods. Furthermore, its mixing, temperature, and sampling controls are robust and easy to reprogram. We encountered particular difficulty in accurately dispensing discrete sample volumes, but we have discussed viable and actionable solutions to this problem. Through a multitude of design iterations, we have vastly improved the functionality, usability, and reliability of the system and expect it to develop into a significant improvement over the state-of-the-art methods in this field. The Cytopendix has, overall, proved to bear significant potential as a flexible and extensible instrument for fully automated yeast strain characterization.

Our goal is to create an inverted pendulum in the form of a cube. An inverted pendulum is an object with a center of mass above its pivot point. Having the center of mass above the pivot point makes for an unstable system. The object will tend to fall over when it is not perfectly balanced, or when no external force is applied. To balance the object and keep it stable, a controlled counter force must be applied. Generating the counter force for our cube will be accomplished by using angular momentum. Controlling the angular momentum will be achieved through counter-torque generated by the three internal motors, each spinning on an axis perpendicular to the others. These motors will spin flywheels in order to store angular momentum. The stored angular momentum can be utilized by controlling the torque and direction of the motors. This will ultimately cause a net force to be applied to the cube in a direction determined by the sensor feedback and control algorithm. This project has its significance in the field of aerospace. For instance, having an object fixed in a certain angular position in the outer space. Moreover, the control system, which takes input of gyroscopes and accelerometers to control flywheels and motors, has various applications in the field of automobiles and construction machinery.  

The advancements of microelectronic structures for high performance electronics are now turning to 3D chip integration technology. The use of vertical connections with high aspect ratios, called Through-Silicon Vias (TSVs), is becoming a popular method for fabricating electronic multi-chip systems and devices. Since these vias do not run along the surface of the wafer, the high density of the vertical vias allows for more interconnections to be made between chips in a stacked system. The goal of this research was to establish the procedure in which TSVs are produced to maximize the highest quantity of connections (maximum packing of number of number of usable vias per unit area). The experiments that were performed involved the fabrication of TSVs while addressing possible reasons for error in each step. The steps that were improved upon and are discussed include best photoresist spinning techniques, minimizing time between exposure and development, and best development techniques. These improvements offer a higher repeatability of the procedure to result in the same yield and quality of TSVs for future production.

Current research in microelectronic devices made of semiconducting silicon wafers focuses on developing high aspect ratio vertical connections between stacked wafers, known as through-silicon vias (TSV), which result in 3D integrated circuits. These 3D integrated circuits are used to increase density of memory chips, enhance performance, and reduce power requirements, resulting in smaller and more efficient electronic devices. After processing silicon wafers with preliminary photolithography, a dense pattern of high-aspect ratio TSV “holes” is achieved with a deep reactive ion etching (DRIE) tool which utilizes the Bosch process. When a hardware change in the electrostatic chuck of the DRIE tool used for this project resulted in poor etch quality and inconsistent sidewall profile, this experiment attempted to develop a new sequence of steps, or “recipe,” for the DRIE tool in order to correct the new issues. Etching parameters were refined in order to achieve the primary goal, to improve sidewall conditions which were not consistently 90 degrees, as well as secondary goals, to obtain the tool’s etch rate and selectivity towards photoresist against silicon. Sidewall profile, etch rate, and selectivity were determined by sample analysis via scanning electron microscopy. The conclusion of this experiment was a process recipe which could reliably achieve the desired high aspect ratio vias and continue downstream processing of TSV development.

Exploring the ocean always requires human divers going undersea. Due to the complicated environment, undersea human activity is normally dangerous. Additionally, there are limits to what human operators can collect in terms of underwater data, often relying on larger, more expensive manned vehicles to acquire the desired data. We want a remotely-operated device that captures the undersea views, with geological data attached. Thus, we are presenting a submersible ROV, tethered to a clean-energy, self-sustained buoy for power and user communication, that carries cameras and positioning sensors to explore the ocean.The ROV can capture video and images that are transmitted to a host computer, which will interface with Booz Allen Hamilton’s Ocean Lens VR platform to create a user-friendly 3D environment. Based on the design requirements stated above, we built a system block diagram of the project, showing the planned system component hierarchy. From that, we assigned design subtasks according to each team member’s expertise. The primary design sections are as follows: power (conversion and distribution of power from buoy), controls (physical operation and movement of ROV), sensors (video, temperature, positioning, etc.), and mechanics (ROV chassis design, construction, and hydrodynamics). The ROV comes with an inertial measurement unit to track vehicle orientation, as well as a GPS, to provide accurate positioning data. The ROV will operate up to 100 meter clear- and salt-water depths and will collect pressure, ambient light, pH, and temperature data while giving the user near-real-time control. The ROV comes in a watertight acrylic chassis with 3 thrusters to control forward, backward, and vertical movement while in motion and idle. Receiving power from the buoy, the ROV will charge up internal batteries that will allow it to operate for 1.5 hours.

Photolithography is a process used in nanofabrication to create patterns on different types of substrates. These patterns are used to define structures that are either built up (additive) or etched (subtractive) to form functional layers. These functional layers allow for the creation of different kinds of electronics, such as resistors and semiconductors on an incredibly small scale. The process of photolithography involves the use of light to expose a pattern on a substrate. In order to expose a pattern on a substrate or wafer, the use of photoresist is essential. Photoresist is a viscous solution, which is deposited on wafers. The wafer then goes through a process called spin coating which rapidly spins the wafer to create an even surface. This even surface is crucial in order to properly expose a pattern on the wafer. In order to have an even coating and minimize the discrepancies across a wafer’s surface, there are many processes that a wafer must go through in order to ensure the best quality for exposure. This poster discusses techniques including the storage of the wafer, the handling of the wafer and the depositing of photoresist. Analyses of these techniques are discussed as well as critical parameters for the environment in which they are kept.

According to the World Health Organization, an estimated, 780 million people do not have access to clean water sources. Disasters are another potential cause of disruption to the supply of clean water. When the safety of a water source is unknown, a cost effective method to determine water safety is necessary to reduce unsafe water related disease and death. Prior synthetic biology research has been conducted utilizing transgenic yeast as a biosensor for heavy metal detection, such as using plasmids expressing Green Fluorescent Protein (GFP) which are promoted by heavy metal binding transcription factors. While able to detect copper ions in a dose dependent fashion, the relative instability of the plasmid, reporters which are difficult to detect in situ, and limited targeting to copper and silver ions make the efficacy of the designs impractical. Using modern methods of plasmid integration and the modulation of the copper sensitive pCUP1 promoter expression we sought to produce a stable and more sensitive biosensor for the detection of copper ions in water. We successfully integrated the genetic cassette pCUP1-yeGFP into the yeast genome and produced a viable biosensor for the detection of aqueous copper. We tested this yeast strain via a cytometer after exposure to copper of varying concentrations at varied time intervals. The results showed a dose response curve that positively correlated with copper concentration in a semi-linear fashion, which indicated the pCUP1-yeGFP transgene was a viable sensitive reporter for the detection of copper. Currently, variable constitutive promoters are being altered to increase copper detection sensitivity by modulation of the expression of the metal binding transcription factor Ace1. The team is currently exploring the effect of Ace1 upregulation on the sensitivity of copper sensing. After investigating sensitivity modulation, an exploration of practical field detectable reporters, such as violacein, will be undertaken.

Though the rising popularity in hybrid vehicles comes as a benefit to the environment, it has proven to be a detriment to the tax revenue raised at the gas pump. The state of Washington projects to not meet the fiscal needs for civil infrastructure repair in the foreseeable future because of this shift in the market. In preparation for a future dominated by electric vehicles, Washington State has proposed implementing a tax program that charges according to the number of miles driven on Washington roads. Our team’s mission is to develop a mobile app that can dynamically track the miles driven by a vehicle. This app will be able to extract a baseline mileage count from a picture the taxpayer takes of their car’s odometer reading. It will also be able to track nontaxable miles driven out of state by using the car’s on board diagnostic system and GPS data. These nontaxable miles will qualify for a tax rebate at the end of a billing period. Our app will not only sufficiently support government’s road charge policy and help recover the lost gas tax caused by increasing amount of hybrid vehicles, but will also provide drivers in the state with the convenience to obey the policy and save money while travelling out of the state.