https://engineering.wustl.edu/news/Pages/When-WiFi-is-weak-send-noise-instead.aspx1200When WiFi is weak, send noise instead<img alt="" src="/news/PublishingImages/silent%20send%20noise.jpg?RenditionID=1" style="BORDER:0px solid;" /><div id="__publishingReusableFragmentIdSection"><a href="/ReusableContent/36_.000">a</a></div><p>​When WiFi was designed, it was intended for high speed data communications. The Institute of Electrical and Electronics Engineers (IEEE) set the standards for communications — that’s the 802.11 protocol, a familiar number on many wireless routers.</p><p>According to the protocol, once a device is unable to send at least one megabit per second (Mbps), it is “out of range.” Even if it were physically possible to send, say, a half megabit per second, the protocol won’t allow it.</p><p>Electrical and systems engineer and computer scientist <a href="/Profiles/Pages/Neal-Patwari.aspx">Neal Patwari</a> of the McKelvey School of Engineering at Washington University in St. Louis has been working with a group using sensors to continuously collect indoor air quality data from the homes of volunteers, in a project sponsored by the National Institute of Biomedical Imaging and Bioengineering (NIBIB).</p><p>But when researchers stopped receiving data, there wasn’t a way to determine whether a sensor had been unplugged, or if something was interfering with the WiFi signal. They just needed to send a small ping, a tiny bit of data, but that was the problem — the protocol wouldn’t allow it.<br/></p><p></p><p>“We were trying to figure out, can we send lower rate data from a WiFi device even though it’s not part of the protocol, using the same hardware?” said Patwari, professor of electrical and systems engineering and of computer science and engineering.</p><p>Indeed, they found a way.</p><p>Patwari and the team presented <a href="https://span.engineering.wustl.edu/pub/lundrigan2019onoff.pdf">the results of their research</a> Oct. 22 at ACM MobiCom 2019, the 25th International Conference on Mobile Computing and Networking.</p><p>For their study regarding how indoor air quality affected asthma rates, the researchers needed lots of data from lots of homes with asthmatic children over a long period of time.</p><p>Research participants agreed to have air quality sensors in their homes. The sensors transmitted data to the researchers via WiFi, and were expected to do so for a year.</p><blockquote>“This is a problem,” Patwari said. “If you’ve ever had to set up and maintain a wireless network, you know that it requires some work every once in a while if something goes wrong.”</blockquote><p>Something will always go wrong, and, after lots of communication back and forth with participants to fix things, researchers were worried the challenges would cause participants to drop out.</p><p>Patwari experienced this frustration himself, when he put a sensor in his bedroom, across the house from his wireless router. His own student, Philip Lundrigan, also an author of the study, called when the link went down. When he went to check on the router, he had to move a basket of laundry out of the way.</p><p>Suddenly, the connection to the sensor was restored.</p><p>“It was the laundry basket,” he said, “and it was clean laundry!”</p><p>It wasn’t that the laundry had formed an impenetrable wall and the WiFi signal was stopped dead in its tracks. Rather, since the sensor was far away from the router, any small perturbation kicked the data transfer rate below 1 Mbps — the lowest transfer rate allowed by the protocol. So communication was cut off.</p><p>The situation the researchers were trying to address didn’t require that much data, though. They were just trying to find a way to figure out if the connection had been terminated, or if the sensor had been unplugged. For this purpose, instead of treating the transmitter as something that sent data, Patwari decided to consider it as something that sent noise.</p><p>Modern homes are awash in wireless noise — from computers to televisions to stereos to cell phones — the signals are everywhere. The team, led by Phil Lundrigan, assistant professor at Brigham Young University, thought they could use this to their advantage. They programmed into the WiFi sensor a series of 1s and 0s, essentially turning the signal on and off in a specific pattern. The router was able to distinguish this pattern from the surrounding wireless noise.</p><p>So even if the sensor’s data wasn’t being received, the router could pick out that pattern in the ambient noise and know that the sensor was still transmitting something.</p><p>The process isn’t entirely straightforward; some noise is louder than other noise, so the team had to devise a way to quiet some of the loudest noise in order to spot the sensor’s hidden message. Nearby signals — say, the television next to the router — were canceled out. By analyzing just a few weaker signals, it becomes much easier to pick out the pattern being sent by the sensor.</p><p>“If the access point hears this code, it says, ‘OK, I know the sensor is still alive and trying to reach me, it’s just out of range,’” Patwari said. “It’s basically sending one bit of information that says it’s alive.”</p><p>The team, which also included <a href="https://www.cs.utah.edu/~kasera/">Sneha K. Kasera</a>, professor at the University of Utah, eventually showed that the code could be transmitted even further than the edge of the WiFi data range — twice as far away, in fact.</p><p>“Even when the laundry basket is in the way and the link can’t send data at the 1 Mbps rate, it can still send this code,” Patwari said, “and your router then knows that the sensor is alive and transmitting. The researcher can rest easy knowing that the sensor is still collecting data, and eventually they’ll get their air quality data.”</p><p>This is just the beginning for the new innovation. It might be able to make so-called “long range” wireless protocols even longer range, according to Lundrigan, or be used on top of other wireless technology such as bluetooth or cellular.</p><p>“We can send and receive data regardless of what WiFi is doing,” Lundrigan said. “All we need is the ability to transmit energy and then receive noise measurements.”</p><SPAN ID="__publishingReusableFragment"></SPAN><p><br/></p><div><div class="cstm-section"><h3>Neal Patwari<br/></h3><div style="text-align: center;"> <strong> <a href="/Profiles/Pages/Neal-Patwari.aspx"> </a> <img src="/Profiles/PublishingImages/Neal%20Patwari_03.jpg?RenditionID=3" alt="" style="margin: 5px;"/> <br/></strong></div><ul style="text-align: left;"><li>Professor<br/></li><li>Research: The intersection of statistical signal processing and wireless networking, for improving wireless sensor networking and RF sensing. <br/></li></ul><p style="text-align: center;"> <a href="/Profiles/Pages/Neal-Patwari.aspx">>> View Bio</a><br/></p></div></div> <span> <div class="cstm-section"><h3>Media Coverage<br/></h3><div> <strong>Engadget: </strong><a href="https://www.engadget.com/2019/10/22/wifi-onpc-protocol/?guccounter=2">BYU researchers extend WiFi range by 200 feet with a software upgrade</a></div><div><br/></div><div><strong style="caret-color: #343434; color: #343434;">TechRadar: </strong><a href="https://www.techradar.com/news/this-new-technology-could-make-your-wi-fi-instantly-better">This new technology could make your Wi-Fi instantly better</a><br/></div></div></span>Brandie Jeffersonhttps://source.wustl.edu/?p=364543&preview=1&_ppp=30030957712019-10-22T05:00:00ZRecognizing wireless noise can be key to sending information, researchers find<p>​Recognizing wireless noise can be key to sending information, researchers find<br/></p>
https://engineering.wustl.edu/news/Pages/Big-data-analysis-leads-to-discovery-of-new-class-of-RNA.aspx1184Big data analysis leads to discovery of new class of RNA <img alt="" src="/news/PublishingImages/iStock-1094685558.jpg?RenditionID=2" style="BORDER:0px solid;" /><div id="__publishingReusableFragmentIdSection"><a href="/ReusableContent/36_.000">a</a></div><p>In the past several years, circular RNA, a type of RNA formed by fusion of the two ends of a linear RNA, has been recognized to play roles in cell development and in various types of cancer and neurodegenerative diseases. A computer scientist in the McKelvey School of Engineering at Washington University in St. Louis has found a new class of circular RNA, which could shed light on some of these diseases. </p><p>Weixiong Zhang, professor of computer science & engineering and professor of genetics at the School of Medicine, along with his doctoral student Xiaoxin Liu, discovered and studied a new class of these circular RNAs, or circRNAs, by analyzing enormous amounts of genetic data from humans, mice and rice. After having biologists at Jianghan University in China validate their computational results, they reported their findings in <em>RNA Biology</em>, published online Sept. 27, 2019. </p><p>In their analysis, Zhang and his collaborators found a new class of circRNAs that circulate at the positions inside of exons, introns and RNA sequences from the genomic regions between genes and called them interior circRNAs. These interior circRNAs are abundant in humans, mice and rice. In HeLa cells, the oldest and most commonly used human cell line, 92.2% of the total circRNAs are interior circRNAs; in the human brain, 43.2% are interior circRNAs; in the mouse brain, 84.3% are interior circRNAs; and in rice roots, 96.6% are interior circRNAs. </p><p>"We developed an algorithm and a program to systematically look for joining points in circular RNAs," Zhang said. "Our new method is purely a data-driven approach that does not rely on information of gene annotation or RNA splicing signals and is able to identify candidate circRNAs regardless of their genomic origins." </p><p>Zhang's work investigating the novel ways that these interior circRNAs are created, which led to new hypotheses of splicing independent biogenesis of circRNA production, opens a new way to understand circRNAs. He plans to continue studying classes of circular RNA and what roles they may have in cancer and neurodegenerative diseases. </p><p>"This is a big missing piece in the study of circular RNA," Zhang said.</p><SPAN ID="__publishingReusableFragment"></SPAN><p> Liu X, Hu Z, Zhou J, Tian C, Tian G, He M, Gao L, Chen L, Li T, Peng H, Zhang W. Interior circular RNA. <em>RNA Biology</em>, <a href="https://doi.org/10.1080/15476286.2019.1669391">https://doi.org/10.1080/15476286.2019.1669391</a>.</p><p>Funding for this work was provided by the National Institutes of Health (R01 GM100364) and the National Natural Science Foundation of China. <br/></p><div><div class="cstm-section"><h3>Weixiong Zhang<br/></h3><div style="text-align: center;"> <strong> <a href="/Profiles/Pages/Randall-Martin.aspx"> </a><img src="/Profiles/PublishingImages/Zhang_018_R.jpg?RenditionID=3" alt="" style="margin: 5px;"/> <br/></strong></div><ul style="text-align: left;"><li>Professor<br/></li><li>Research: Develops computational methods for complex problems appeared in molecular biology, genetics, systems biology and genomics <br/></li></ul><p style="text-align: center;"> <a href="/Profiles/Pages/Weixiong-Zhang.aspx">>> View Bio</a><br/></p></div></div> <span> </span> <br/>Weixiong Zhang and his collaborators found a new class of circRNAs that circulate at the positions inside of exons, introns and RNA sequences from the genomic regions between genes and called them interior circRNAs. Beth Miller 2019-10-16T05:00:00ZWeixiong Zhang and members of his lab have found a missing piece in the study of circular RNA.
https://engineering.wustl.edu/news/Pages/Looking-for-the-best-from-man-and-machine-to-create-new-materials.aspx1190Looking for the best from human and machine to create new materials<img alt="" src="/news/PublishingImages/iStock-867341944.jpg?RenditionID=2" style="BORDER:0px solid;" /><div id="__publishingReusableFragmentIdSection"><a href="/ReusableContent/36_.000">a</a></div><p>​In the late 1990s, IBM's Deep Blue computer defeated world chess champion Garry Kasparov. The loss shocked the chess world and led Kasparov to envision a new form of chess called centaur chess, in which a human and computer cooperate as a team, modeled after the man-horse beast from Greek mythology.</p><p>An interdisciplinary, multi-institutional team of researchers plans to adapt this centaur analogy to accelerate scientific discovery. The team plans to develop a new framework to speed the discovery of electronic materials based on active machine learning and intelligent search, human-machine interaction and visualization with a two-year, $1.8 million grant from the National Science Foundation (NSF). The grant is part of the NSF's $300 million 10 Big Ideas program and falls under the Harnessing the Data Revolution Big Idea, which focuses on the emerging field of data science. </p><p>Roman Garnett, assistant professor of computer science & engineering in the McKelvey School of Engineering at Washington University in St. Louis, brings his research and experience in active machine learning to the project with $306,000 in funding. Garnett, who has an NSF CAREER Award for his work in active machine learning, has extensive experience applying machine learning to automate discovery, particularly in active search for drug and materials discovery. In this project, his expertise will help to design a framework that most efficiently reaches its objective. </p><p>"Making new materials is really expensive," Garnett said. "You can do experiments in the lab, but they are costly and slow. Computational simulations are cheaper, but not perfect. Intuitively we want to do the computations to get an idea of the most promising possibilities, then be confident enough to spend the money to run the experiments in the lab."</p><p>Garnett describes this as multifidelity learning, which simultaneously reasons about expensive, high-fidelity, in-lab experiments as well as cheaper, lower-fidelity computations. Multifidelity learning enables cost-effective decision-making by carefully modeling the tradeoff between the cost of collecting data and the information it provides. </p><p>Collaborating with Garnett on the project are Remco Chang, associate professor of computer science, Tufts University; Jane Greenberg, the Alice B. Kroeger Professor at Drexel University; Steven Lopez, assistant professor of chemistry and chemical biology, Northeastern University; and Eric Toberer, associate professor of physics, Colorado School of Mines.</p><p>In addition to the computational and experimental work, the team plans to bring in a human component. </p><p>"In a lot of these active learning pipelines, everything is automated and we try to get the human out of the loop," Garnett said. "But in these scientific applications, we want to make sure the human is involved and that the computer is aiding the human by being better at planning. Through the visualization, we want to give them insight into the system that they couldn't see before. The human and computer thus cooperate as a team and learn from each other." </p><p>Their plan would also allow a user to provide feedback on proposed experiments. </p><p>"The user will bring in other knowledge that a machine learning algorithm would not have, such as, 'I have a PhD in chemistry, and I know that those molecules would make my lab explode if I tried to combine them,'" Garnett said. "This will serve as another type of fidelity — the human provides another source of information we can seamlessly incorporate into our model. Now the computer can benefit from the human's expertise while the human benefits from the algorithm's ability to intelligently search complex spaces." <br/></p><p>Bringing together the five collaborators into developing the machine learning framework will be a unique experience, Garnett said. They met as part of a competitive ideas lab last spring to develop ideas for the Harnessing the Data Revolution Big Idea.<br/></p><p>"Our team includes experts from a wide range of fields," Garnett said. "Just as we envision the human-computer team cooperating to discover new materials, we will cooperate with each other to discover new methodologies enabling that team to succeed."<br/></p><SPAN ID="__publishingReusableFragment"></SPAN><p><br/></p><span> <div class="cstm-section"><h3 style="margin-top: 0px; font-family: "open sans", sans-serif; font-size: 1.34em; text-align: center; border-bottom: 1px solid #b0b0b0; padding-bottom: 12px;">Roman Garnett<br/></h3><div style="text-align: center;"> <img src="/Profiles/PublishingImages/Garnett_Roman.jpg?RenditionID=3" class="ms-rtePosition-4" alt="" style="color: #343434; font-size: 1em; font-family: "open sans", "helvetica neue", helvetica, arial, sans-serif; margin: 5px;"/> <div style="color: #343434;"></div></div> <ul style="padding-left: 20px;"><li>Assistant Professor of Computer Science & Engineering <br/></li><li>Expertise: Bayesian machine-learning techniques for sequential decision making<br/></li></ul><p style="text-align: center;"> <a href="/Profiles/Pages/Roman-Garnett.aspx" style="background-color: #ffffff;">View Bio</a> <br/><br/></p></div> </span>2019-10-07T05:00:00ZRoman Garnett and a multidisciplinary team plans to develop a new framework to speed the discovery of electronic materials based on active machine learning and intelligent search.
https://engineering.wustl.edu/news/Pages/Weiderhold-helping-NASA-to-build-ICE-Sat2-locator-app.aspx1159Wiederhold helping NASA to build ICESat-2 locator app<div class="youtube-wrap"><div class="iframe-container"> <iframe width="560" height="315" src="https://www.youtube.com/embed/rOXjuiQ3R_o" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"></iframe>      </div> </div> <br/><img alt="" src="/news/PublishingImages/Emme%20Weiderhold.jpg?RenditionID=1" style="BORDER:0px solid;" /><p>​Emme Wiederhold, a senior majoring in computer science, has spent the past two summers working for NASA on different projects. She is now helping to develop an app so that anyone in the world can locate the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2). We asked Emme about her experience as a two-time NASA intern. </p><p><strong>Q.</strong><strong> What have you worked on the past two summers?<img src="/news/PublishingImages/Emme%20Weiderhold.jpg?RenditionID=6" class="ms-rtePosition-2" alt="" style="margin: 5px;"/></strong><br/></p><p><strong>A.</strong> During the summer of 2018, I worked at NASA's Goddard Space Flight Center in Maryland. I worked with the Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) team, a team of cryospheric scientists studying the change in sea and land ice on Earth using this satellite. On this team, I worked to build a module for an augmented reality mobile application called HoloGLOBE. The goal of this module is to inform the public about the ICESat-2 mission and get them excited about the data it's collecting. This summer, I interned at NASA's Jet Propulsion Laboratory in Southern California, working with the Microsoft HoloLens to build an augmented reality application for the Mars 2020 rover mission. The goal of this application is to allow scientists, geologists and other users to gain spatial awareness of the Martian environment to be able to better plan science goals for the rover. The Mars 2020 mission will be launching next year and will carry a sample caching system to gather samples from the Martian surface.<br/></p><p rtenodeid="2"><strong>Q. What is the ICESat-2, and how did you get involved with it?</strong></p><p><strong>A.</strong> ICESat-2 is the Ice, Cloud, and Land Elevation Satellite 2. It is an Earth-observing satellite that uses a laser instrument called ATLAS, or the Advanced Topographic Laser Altimeter System, to measure the height of the Earth. This information can be used to monitor changes in land and sea ice thickness and elevation in our polar regions. I got involved with the ICESat-2 mission in the spring of 2018 when I received an opportunity to intern for the team during that summer. I was able to apply online to internships at various NASA centers, and this happened to be one in which I was particularly interested.<br/></p><p rtenodeid="3"><strong>Q. What is the app you are developing, how will it work, and who can use it?</strong></p><p><strong>A.</strong> The mobile application that I'm currently developing for the ICESat-2 team is one that will allow the public to see when the satellite will next be passing overhead. Users will be able to enter any location in which they are interested and see a set of results for future dates and times when the satellite will be passing over that location. Anyone can use this app! It will be useful for all sorts of people, whether they are curious when the satellite is passing over so they can try to catch a glimpse of the green laser at night or the sun reflecting off the solar array during the day, or scientists wondering when they can expect to access data from the satellite for their region.<br/></p><p rtenodeid="4"><strong>Q. What is your role in the app development?</strong></p><p><strong>A.</strong> My role in the development of the application has been fully involved. The project started off with needing to host the ground track data on a server. Now that the back-end, server-based step is mostly complete, the project has been transitioning into more of a front-end development effort. This involves using Xcode to code in Swift and deploy prototypes of the project to mobile devices for testing. The app itself uses that server to perform queries depending on the locations that the user inputs.<br/></p><p rtenodeid="5"><strong>Q. What has it been like to work on these projects with NASA as an undergraduate student?</strong></p><p><strong>A.</strong> I've had such a fantastic experience working with NASA as an undergraduate student, and I'm so grateful for all of the opportunities that I continue to receive from the teams I've worked with. Being able to "nerd out" about space and be amongst so many individuals who are passionate about space, science and technology has certainly been an incredible experience for me. And by means of working on these projects, I've discovered so many more things about which I'm passionate and feel as though I've found a niche type of computer science and programming that I really enjoy.<br/></p>2019-09-23T05:00:00ZSenior Emme Wiederhold is helping NASA develop an app so that anyone can determine the location of the ICE-Sat2 satellite in relation to the user.
https://engineering.wustl.edu/news/Pages/Center-for-Quantum-Sensors-awarded-NSF-Quantum-Leap-Challenge-seed-grant.aspx1169Center for Quantum Sensors awarded NSF Quantum Leap Challenge seed grant<img alt="" src="/news/PublishingImages/IMG_9062.jpg?RenditionID=1" style="BORDER:0px solid;" /><p>​</p><p>The <a href="https://artsci.wustl.edu/ampersand/quantum-launch">Center for Quantum Sensors</a> (CQS) was awarded a Quantum Leap Challenge Institute (QLCI) conceptualization grant from the National Science Foundation. QLCIs are large-scale, interdisciplinary research projects that aim to advance applications of quantum information science. This conceptualization grant will provide WashU's CQS the resources it needs to potentially develop into a fully-fledged QLCI, validate the center's work on quantum sensors as one of the most compelling areas of quantum research, and give the center a voice in shaping national collaborations around quantum sensing. The grant will support planning and team-building activities over the coming year, in preparation for the next stage of NSF funding and development.</p><p>"Our conceptualization grant aims to focus the community's conversation around quantum sensing to try to identify the most compelling questions and the most compelling ideas for addressing those questions," said <a href="https://physics.wustl.edu/people/kater-murch">Kater Murch</a>, associate professor in the Department of Physics in Arts & Sciences, who led the proposal. "Our goal is to identify challenges where we can make a transformative advance in the next five years."</p><p>Housed within Arts & Sciences, the Center for Quantum Sensors aims to engage the physics, chemistry, engineering, medical, and industrial communities to tackle quantum sensing problems that can only be addressed collaboratively. In addition to Murch, the center includes collaborators from several departments in Arts & Sciences and from the McKelvey School of Engineering: <a href="https://chemistry.wustl.edu/people/sophia-e-hayes">Sophia Hayes</a>, professor of chemistry in Arts & Sciences; <a href="https://physics.wustl.edu/people/james-h-buckley">James H. Buckley</a>, professor of physics in Arts & Sciences; <a href="/Profiles/Pages/Ron-Cytron.aspx">Ron K. Cytron</a>, professor and associate department chair of computer science and engineering in McKelvey Engineering; <a href="https://physics.wustl.edu/people/erik-henriksen">Erik A. Henriksen</a>, assistant professor of physics in Arts & Sciences; <a href="https://physics.wustl.edu/people/henric-krawczynski">Henric Krawczynski</a>, professor of physics in Arts & Sciences; <a href="/Profiles/Pages/Matthew-Lew.aspx">Matthew Lew</a>, assistant professor of electrical and systems engineering in McKelvey Engineering; and <a href="/Profiles/Pages/Lan-Yang.aspx">Lan Yang</a>, Edwin H. and Florence G. Skinner Professor of electrical and systems engineering in McKelvey Engineering. The cast of collaborators is set to expand this year as the center brings on graduate students from multiple disciplines and broadens its network of researchers beyond WashU.</p><p> </p><p> </p><p><br/></p><p><br/></p>Shawn Ballard2019-09-20T05:00:00ZThree McKelvey School of Engineering faculty are collaborators in the university's new Center for Quantum Sensors.

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