Shark Alert: Early Warning System

The Shark Alert Early Warning System is a device geared toward avid beach goers such as surfers, divers, and swimmers. The system is composed of an ultrasonic transmitter mounted on a shark’s dorsal fin and a receiver worn by the user around the ankle. The receiver alerts the user to the presence of a shark upon ultrasonic signal detection. The receiver warns the user through both visual and tactile (vibration) alerts to ensure user notification. This circuit was built and tested in the EE labs and Recreation Center pools to determine transmission range. The receiver detects the transmitted signal up to 150 feet away and fits comfortably on the user’s ankle. The alert module determines receiver detection. The transmitter remains operational over the shark’s lifetime by hydraulic turbine-based AC power generation. This is accomplished by utilizing the shark’s movement through the water. Testing was conducted in the Cal Poly Civil Engineering Department’s Flume and in Lake Nacimiento

A Wearable System that Knows Who Wears It

Body-area networks of pervasive wearable devices are increasingly used for health monitoring, personal assistance, entertainment, and home automation. In an ideal world, a user would simply wear their desired set of devices with no configuration necessary: the devices would discover each other, recognize that they are on the same person, construct a secure communications channel, and recognize the user to which they are attached. In this paper we address a portion of this vision by offering a wearable system that unobtrusively recognizes the person wearing it. Because it can recognize the user, our system can properly label sensor data or personalize interactions. \par Our recognition method uses bioimpedance, a measurement of how tissue responds when exposed to an electrical current. By collecting bioimpedance samples using a small wearable device we designed, our system can determine that (a)the wearer is indeed the expected person and (b) the device is physically on the wearer\u27s body. Our recognition method works with 98% balanced-accuracy under a cross-validation of a day\u27s worth of bioimpedance samples from a cohort of 8 volunteer subjects. We also demonstrate that our system continues to recognize a subset of these subjects even several months later. Finally, we measure the energy requirements of our system as implemented on a Nexus S smart phone and custom-designed module for the Shimmer sensing platform

ZEBRA: Zero-Effort Bilateral Recurring Authentication

Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests. \par To address this problem we propose ZEBRA. In ZEBRA, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same – the user\u27s hand movement. In our experiments ZEBRA performed continuous authentication with 85% accuracy in verifying the correct user and identified all adversaries within 11 s. For a different threshold that trades security for usability, ZEBRA correctly verified 90% of users and identified all adversaries within 50 s

ZEBRA: Zero-Effort Bilateral Recurring Authentication (Companion report)

We describe and evaluate Zero-Effort Bilateral Recurring Authentication (ZEBRA) in our paper that appears in IEEE Symposium on Security and Privacy, May 2014. In this report we provide a more detailed comparative evaluation of ZEBRA against other related authentication schemes. The abstract of the paper follows. Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests. To address this problem we propose ZEBRA. In ZEBRA, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same - the user\u27s hand movement. In our experiments ZEBRA performed continuous authentication with 85% accuracy in verifying the correct user and identified all adversaries within 11 s. For a different threshold that trades security for usability, ZEBRA correctly verified 90% of users and identified all adversaries within 50 seconds

Economics of deficit irrigation utilizing soil moisture probes in the western corn belt

Effective irrigation management is critical for future food supplies and the prosperity of producers engaged in irrigation production. Through a deficit irrigation field experiment, we determine the financial impact on producers caused by changing irrigation costs, corn prices, extreme weather events, and restricting irrigation levels. Results suggest that the optimal economic strategy within our constrained optimization model is to fully irrigate, with the economic impact highly dependent on commodity prices, restriction level, and irrigation costs. The greatest economic losses caused by irrigation restrictions come from decreases in yield. Some simulations resulted in negative profits, indicating that a switch to alternative crops requiring less irrigation may be warranted

Who Wears Me? Bioimpedance as a Passive Biometric

Mobile and wearable systems for monitoring health are becoming common. If such an mHealth system knows the identity of its wearer, the system can properly label and store data collected by the system. Existing recognition schemes for such mobile applications and pervasive devices are not particularly usable – they require ıt active engagement with the person (e.g., the input of passwords), or they are too easy to fool (e.g., they depend on the presence of a device that is easily stolen or lost). \par We present a wearable sensor to passively recognize people. Our sensor uses the unique electrical properties of a person\u27s body to recognize their identity. More specifically, the sensor uses ıt bioimpedance – a measure of how the body\u27s tissues oppose a tiny applied alternating current – and learns how a person\u27s body uniquely responds to alternating current of different frequencies. In this paper we demonstrate the feasibility of our system by showing its effectiveness at accurately recognizing people in a household 90% of the time

Passive Biometrics for Pervasive Wearable Devices (Poster Paper)

Wearable devices – like the FitBit, MOTOACTV, and Jawbone UP – are increasingly becoming more pervasive whether for monitoring health and fitness, personal assistance, or home automation. While pervasive wearable devices have long been researched, we are now beginning to see the fruits of this research in the form of commercial offerings. Today, many of these commercial wearable devices are closed systems that do not interoperate with other devices a person might carry. We believe, however, these commercial offerings signal the coming of wireless body-area networks that will connect these pervasive wearable devices and leverage existing devices a user already owns (e.g., a smartphone). Such wireless body-area networks will allow devices to specialize and utilize the capabilities of other devices in the network. A sensor, for example, might harness the internet connectivity of a smartphone to store its data in the cloud. Utilized in this way, devices will become cheaper because they will only require the components necessary for their speciality, and they will also become more pervasive because they can easily be shared between users. \par In order for such a vision to be successful, these devices will need to seamlessly interoperate with no interaction required of the user. As difficult as it is for users to manage their wireless area networks, it will be even more difficult for a user to manage their wireless body-area network in a truly pervasive world. As such, we believe these wearable devices should form a wireless body-area network that is passive in nature. This means that these pervasive wearable devices will require no configuration, yet they will be able form a wireless body-area network by (1) discovering their peers, (2) recognizing they are attached to the same body, (3) securing their communications, and (4) identifying to whom they are attached. While we are interested in all aspects of these passive wireless body-area networks, we focus on the last requirement: identifying who is wearing a device

Potential Benefits of Combined Statin and Metformin Therapy on Resistance Training Response in Older Individuals

Metformin and statins are currently the focus of large clinical trials testing their ability to counter age-associated declines in health, but recent reports suggest that both may negatively affect skeletal muscle response to exercise. However, it has also been suggested that metformin may act as a possible protectant of statin-related muscle symptoms. The potential impact of combined drug use on the hypertrophic response to resistance exercise in healthy older adults has not been described. We present secondary statin analyses of data from the MASTERS trial where metformin blunted the hypertrophy response in healthy participants (\u3e65 years) following 14 weeks of progressive resistance training (PRT) when compared to identical placebo treatment (n = 94). Approximately one-third of MASTERS participants were taking prescribed statins. Combined metformin and statin resulted in rescue of the metformin-mediated impaired growth response to PRT but did not significantly affect strength. Improved muscle fiber growth may be associated with medication-induced increased abundance of CD11b+/CD206+ M2-like macrophages. Sarcopenia is a significant problem with aging and this study identifies a potential interaction between these commonly used drugs which may help prevent metformin-related blunting of the beneficial effects of PRT

Laser-Based Propagation of Human iPS and ES Cells Generates Reproducible Cultures with Enhanced Differentiation Potential

Proper maintenance of stem cells is essential for successful utilization of ESCs/iPSCs as tools in developmental and drug discovery studies and in regenerative medicine. Standardization is critical for all future applications of stem cells and necessary to fully understand their potential. This study reports a novel approach for the efficient, consistent expansion of human ESCs and iPSCs using laser sectioning, instead of mechanical devices or enzymes, to divide cultures into defined size clumps for propagation. Laser-mediated propagation maintained the pluripotency, quality, and genetic stability of ESCs/iPSCs and led to enhanced differentiation potential. This approach removes the variability associated with ESC/iPSC propagation, significantly reduces the expertise, labor, and time associated with manual passaging techniques and provides the basis for scalable delivery of standardized ESC/iPSC lines. Adoption of standardized protocols would allow researchers to understand the role of genetics, environment, and/or procedural effects on stem cells and would ensure reproducible production of stem cell cultures for use in clinical/therapeutic applications

ZEBRA: Zero-Effort Bilateral Recurring Authentication

Abstract-Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests. To address this problem we propose Zero-Effort Bilateral Recurring Authentication (ZEBRA). In ZEBRA, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same -the user's hand movement. In our experiments ZEBRA performed continuous authentication with 85 % accuracy in verifying the correct user and identified all adversaries within 11 s. For a different threshold that trades security for usability, ZEBRA correctly verified 90 % of users and identified all adversaries within 50 s