1,271 research outputs found
Anaerobic Degradation of Organochlorinated Pesticides DDT and Heptachlor in River Sediment of Taiwan
No full text
T.C. Powers, '25, author of the book, "Leakage: The Bleeding of the American Economy"
No full textIncludes letters from the American Society for Testing Material about T.C. PowersBlack and WhitePeople: Powers, T.C
Efficiency Enhancement and Beam Shaping of GaN–InGaN Vertical-Injection Light-Emitting Diodes via High-Aspect-Ratio Nanorod Arrays
No full textEfficient generation of human-like aiming movements
No full textHuman-like reaching movement can be efficiently generated by appropriately replicating an initial ballistic segment and a concluding corrective segment. During the ballistic segment, a damped inertial plant is driven toward a fixed target using a specific form of position-based feedback, referred to as a displacement-normalized actuation program (DNAP). Instead of trying to regulate a particular kinematic profile, the DNAP is used to adjust force (or torque) during the movement. This choice of control structure causes the resulting movement to match key characteristics of human movement that are not easily replicated with traditional control architectures. Only two parameters are required to scale the DNAP template, and these values can be computed as functions of the aiming task configuration. Thus, ballistic control is effectively implemented using a lookup table that contains the DNAP template, and two scaling factors. Stochastic variability is intentionally introduced into these scaling parameters to produce kinematic and temporal randomness that is similar to that found in human subjects making repeated movements. As the movement concludes, control is then switched to a conventional feedback architecture that terminates the motion at a desired endpoint. By making the mechanical system respond as a second-order system, the kinematic response can be modified using just two additional parameters. Again, these control values can be expressed as functions of the aiming task configuration. To merge the ballistic and corrective phases, a particular compensator state is associated with the transition instant. Since each ballistic trajectory transitions into corrective action with a different velocity and acceleration, each movement follows a unique path. Endpoint variation that is typical of aimed human movement is accomplished by adding stochastic noise to the target displacement. Simulated movements generated with the proposed method are shown to be consistent with human motion
Interval analysis techniques for field mapping and geolocation
No full textField mapping and estimation become a challenging problem, with their various applications on non-linear estimation, geolocation, and positioning systems. In this research, we develop novel algorithms based on interval analysis and introduce a solution for autonomous map construction, field mapping, geolocation, and simultaneous localization and mapping (SLAM), providing applications on indoor geolocation and other potential areas. Generally, the localization algorithm includes a quasi-state estimation and a dynamic estimation. Quasi-static estimation collects each single measurement and give a group of estimation intervals on the pre-constructed field map. Results from quasi-static estimation are processed into the dynamic estimation algorithm, having properties of removing redundant intervals while keep the best estimation results. Sizes of estimation from quasi-static estimation are proved to be related to the resolution of the map and the quality of the sensor. Based on quasi-state estimation algorithm, we develop an algorithm to fuse different type of measurements and discuss the condition when this algorithm an be applied effectively. Having theoretical guarantees, we apply these algorithms to augment the accuracy of cell phone geolocation by taking advantage of local variations of magnetic intensity. Thus, the sources of disturbances to magnetometer readings caused indoors are effectively used as beacons for localization. We construct a magnetic intensity map for an indoor environment by collecting magnetic field data over each floor tile. We then test the algorithms without position initialization and obtain indoor geolocation to within 2m while slowly walking over a complex path of 80 meters. The geolocation errors are smaller in the vicinity of large magnetic disturbances. After fusing the magnetometer measurement with inertial measurements on the cell phone, the algorithm yields even smaller geolocation errors of under 50cm for a moving user. The map construction and geolocation algorithms are then extended to realize the SLAM, with hierarchical structure of estimation update and localization update. When a new user steps into a random map, the dead reckoning algorithm with assistance of IMU and Kalman filter provides initial estimation of position on the map, which coordinates the corresponding reading of magnetic field intensity as well as all other sources such as WiFi received signal strength (RSS), to construct an initial map. Based on the initial map, we then apply the localization algorithm to estimate new geolocations consequently and fuse the estimation intervals both from IMU and from crowd-sourced field maps to reduce the estimation size and eventually revise the map as well as the geolocation. In this research, we have built up mathematical model and developed mathematical solutions with corresponding theories and proofs. Our theoretical results connect geolocation accuracy to combinations of sensor and map properties
Design of an embedded fluorescence imaging system for implantable optical neural recording
Full text linkThe brain is the most complex and least understood biological system known to man. New imaging techniques are providing scientists with an entirely new perspective on the study of the functional brain at a neural circuit level, enabling in-depth understanding of both physiological processes and animal models of neurological and psychiatric diseases which currently lack effective treatments. These new tools come at the cost of meeting the challenges associated with the miniaturization of the hardware for in vivo recordings. Here we propose a miniaturized wearable device which enables to record neuronal activations with single cell resolution in rodents for in vivo, long term studies of neural activity in virtually any region of the brain. Additionally, we introduce new techniques for processing a new set of data and mining the relevant information from the recorded neural activity. The proposed image preprocessing techniques include image registration, automatic cell detection and calcium transient extraction algorithms designed for real-time hardware implementation, anticipating the application of single cell neural recordings jointly with optogenetic stimulation in a feedback control loop. The new developed tools were applied to the study of the neural activity in the di- rect and indirect pathways on the dorsal striatum and their role in locomotor activity, a controversial topic due to the lack of techniques for selectively and independently study these neural circuits with sucient detail. Our findings challenge the long standing classical model for D1 and D2 neurons, showing how neural activity in the indirect pathway cannot be explained as inhibitory for locomotor activity. Through the application of a k-means based clustering algorithm we propose a new model for the direct and indirect pathway role in locomotion, and demonstrate the remarkable heterogeneity in striatal D1 and D2 cell populations. The study of acute cocaine effect as a mean for pharmacologically increase locomotor activity further proved the diversity in the response of D1 and D2 neurons within the same cell population. Finally, through the application of machine learning algorithms, we show how neural activity in the dorsal striatum (particularly D2 neurons) can be used as a good predictor for behavior in open field tests
Two degree-of-freedom hysteresis compensation for a dynamic mirror with antagonistic piezoelectric stack actuation
No full textA dynamic mirror actuator (DMA) with antagonistic piezoelectric stack actuation (PESA) is considered for laser beam dot placement error reduction in electrophotographic processes. The DMA is required to meet tracking error specifications below 500~Hz to reduce low-frequency process noise and base vibration. In addition, the DMA is desired to compensate repeatable high-frequency tracking errors due to polygon mirror facet-to-facet misalignment. This high-frequency error correction is a new and novel problem. The development of the DMA is approached in two steps: development of a linear model and low-computation, high-bandwidth hysteresis control. First, a methodology for development of the best linear model to represent the DMA is presented. The DMA is known to exhibit hysteresis and other nonlinearities which are represented by additive input uncertainty and feedback uncertainty elements, respectively, connected to the linear plant model. The proposed linear model employs explicit PESA charging dynamics and incorporates two drive modes for mapping a single control input to the two PESA drive voltages. The proposed linear model is compared to constitutive models from literature and shown to exhibit less frequency response error when compared to experimental data. As a further validation, simulated step response data is shown to agree with experimental data. Second, a methodology for designing a low-computation, high-bandwidth strategy for closed-loop hysteresis control of the DMA without a priori knowledge of the desired trajectory is presented. The resulting hysteresis control is applied to the DMA. A hysteresis compensator is created as a finite state machine switching among polynomials for hysteresis inversion along rising or falling curves. Residual hysteresis error after compensation is further corrected by an LQR feedback controller. Experimental results demonstrate effectiveness of the hysteresis compensator and closed-loop system under the proposed hysteresis control strategy. For the triangular input signal tested, the closed-loop system achieves a 91.5% reduction in hysteresis uncertainty
- …
