Autonomous intelligent assembly systems LDRD 105746 final report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Robert J.

2013-04-01

This report documents a three-year to develop technology that enables mobile robots to perform autonomous assembly tasks in unstructured outdoor environments. This is a multi-tier problem that requires an integration of a large number of different software technologies including: command and control, estimation and localization, distributed communications, object recognition, pose estimation, real-time scanning, and scene interpretation. Although ultimately unsuccessful in achieving a target brick stacking task autonomously, numerous important component technologies were nevertheless developed. Such technologies include: a patent-pending polygon snake algorithm for robust feature tracking, a color grid algorithm for uniquely identification and calibration, a command and control frameworkmore » for abstracting robot commands, a scanning capability that utilizes a compact robot portable scanner, and more. This report describes this project and these developed technologies.« less

A Portable and Autonomous Magnetic Detection Platform for Biosensing

PubMed Central

Germano, José; Martins, Verónica C.; Cardoso, Filipe A.; Almeida, Teresa M.; Sousa, Leonel; Freitas, Paulo P.; Piedade, Moisés S.

2009-01-01

This paper presents a prototype of a platform for biomolecular recognition detection. The system is based on a magnetoresistive biochip that performs biorecognition assays by detecting magnetically tagged targets. All the electronic circuitry for addressing, driving and reading out signals from spin-valve or magnetic tunnel junctions sensors is implemented using off-the-shelf components. Taking advantage of digital signal processing techniques, the acquired signals are processed in real time and transmitted to a digital analyzer that enables the user to control and follow the experiment through a graphical user interface. The developed platform is portable and capable of operating autonomously for nearly eight hours. Experimental results show that the noise level of the described platform is one order of magnitude lower than the one presented by the previously used measurement set-up. Experimental results also show that this device is able to detect magnetic nanoparticles with a diameter of 250 nm at a concentration of about 40 fM. Finally, the biomolecular recognition detection capabilities of the platform are demonstrated by performing a hybridization assay using complementary and non-complementary probes and a magnetically tagged 20mer single stranded DNA target. PMID:22408516

Photonic correlator pattern recognition: Application to autonomous docking

NASA Technical Reports Server (NTRS)

Sjolander, Gary W.

1991-01-01

Optical correlators for real-time automatic pattern recognition applications have recently become feasible due to advances in high speed devices and filter formulation concepts. The devices are discussed in the context of their use in autonomous docking.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Geometry-Based Observability Metric

NASA Technical Reports Server (NTRS)

Eaton, Colin; Naasz, Bo

2012-01-01

The Satellite Servicing Capabilities Office (SSCO) is currently developing and testing Goddard s Natural Feature Image Recognition (GNFIR) software for autonomous rendezvous and docking missions. GNFIR has flight heritage and is still being developed and tailored for future missions with non-cooperative targets: (1) DEXTRE Pointing Package System on the International Space Station, (2) Relative Navigation System (RNS) on the Space Shuttle for the fourth Hubble Servicing Mission.

Programmable and multiparameter DNA-based logic platform for cancer recognition and targeted therapy.

PubMed

You, Mingxu; Zhu, Guizhi; Chen, Tao; Donovan, Michael J; Tan, Weihong

2015-01-21

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy.

Automatic recognition of ship types from infrared images using superstructure moment invariants

NASA Astrophysics Data System (ADS)

Li, Heng; Wang, Xinyu

2007-11-01

Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.

Multirotor micro air vehicle autonomous landing system based on image markers recognition

NASA Astrophysics Data System (ADS)

Skoczylas, Marcin; Gadomer, Lukasz; Walendziuk, Wojciech

2017-08-01

In this paper the idea of an autonomic drone landing system which bases on different markers detection, is presented. The issue of safe autonomic drone landing is one of the major aspects connected with drone missions. The idea of the proposed system is to detect the landing place, marked with an image called marker, using one of the image recognition algorithms, and heading during the landing procedure to this place. Choosing the proper marker, which allows the greatest quality of the recognition system, is the main problem faced in this paper. Seven markers are tested and compared. The achieved results are described and discussed.

Automated Recognition of Geologically Significant Shapes in MER PANCAM and MI Images

NASA Technical Reports Server (NTRS)

Morris, Robert; Shipman, Mark; Roush, Ted L.

2004-01-01

Autonomous recognition of scientifically important information provides the capability of: 1) Prioritizing data return; 2) Intelligent data compression; 3) Reactive behavior onboard robotic vehicles. Such capabilities are desirable as mission scenarios include longer durations with decreasing interaction from mission control. To address such issues, we have implemented several computer algorithms, intended to autonomously recognize morphological shapes of scientific interest within a software architecture envisioned for future rover missions. Mars Exploration Rovers (MER) instrument payloads include a Panoramic Camera (PANCAM) and Microscopic Imager (MI). These provide a unique opportunity to evaluate our algorithms when applied to data obtained from the surface of Mars. Early in the mission we applied our algorithms to images available at the mission web site (http://marsrovers.jpl.nasa.gov/gallery/images.html), even though these are not at full resolution. Some algorithms would normally use ancillary information, e.g. camera pointing and position of the sun, but these data were not readily available. The initial results of applying our algorithms to the PANCAM and MI images are encouraging. The horizon is recognized in all images containing it; such information could be used to eliminate unwanted areas from the image prior to data transmission to Earth. Additionally, several rocks were identified that represent targets for the mini-thermal emission spectrometer. Our algorithms also recognize the layers, identified by mission scientists. Such information could be used to prioritize data return or in a decision-making process regarding future rover activities. The spherules seen in MI images were also autonomously recognized. Our results indicate that reliable recognition of scientifically relevant morphologies in images is feasible.

Development of an Autonomous Face Recognition Machine.

DTIC Science & Technology

1986-12-08

This approach, like Baron’s, would be a very time consuming task. The problem of locating a face in Bromley’s work was the least complex of the three...top level design and the development and design decisions that were made in developing the Autonomous Face Recognition Machine (AFRM). The chapter is...images within a digital image. The second sectio examines the algorithm used in performing face recognition. The decision to divide the development

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

PubMed Central

Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

2016-01-01

Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

Programmable and Multiparameter DNA-Based Logic Platform For Cancer Recognition and Targeted Therapy

PubMed Central

2014-01-01

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy. PMID:25361164

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems 12/8/06 to 12/31/09

DTIC Science & Technology

2010-01-01

8/06 to 12/31/09. Qilian Liang Department of Electrical Engineering 416 Yates Street, Room 518 University of Texas at Arlington Arlington, TX 76019...Modeling in Foliage Environment Jing Liang and Qilian Liang, Senior Member, IEEE Department of Electrical Engineering University of Texas at Arlington E...32 46 of 816 NEW: Network-enabled Electronic Warfare for Target Recognition Qilian Liang Xiuzhen Cheng Sherwood W. Samn Dept of Electrical

The Use of an Autonomous Pedagogical Agent and Automatic Speech Recognition for Teaching Sight Words to Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Saadatzi, Mohammad Nasser; Pennington, Robert C.; Welch, Karla C.; Graham, James H.; Scott, Renee E.

2017-01-01

In the current study, we examined the effects of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and constant time delay during the instruction of reading sight words aloud to young adults with autism spectrum disorder. We used a concurrent multiple baseline across participants design to…

Vision requirements for Space Station applications

NASA Technical Reports Server (NTRS)

Crouse, K. R.

1985-01-01

Problems which will be encountered by computer vision systems in Space Station operations are discussed, along with solutions be examined at Johnson Space Station. Lighting cannot be controlled in space, nor can the random presence of reflective surfaces. Task-oriented capabilities are to include docking to moving objects, identification of unexpected objects during autonomous flights to different orbits, and diagnoses of damage and repair requirements for autonomous Space Station inspection robots. The approaches being examined to provide these and other capabilities are television IR sensors, advanced pattern recognition programs feeding on data from laser probes, laser radar for robot eyesight and arrays of SMART sensors for automated location and tracking of target objects. Attention is also being given to liquid crystal light valves for optical processing of images for comparisons with on-board electronic libraries of images.

Defense Small Business Innovation Research Program (SBIR). Volume 1. Army Abstracts of Phase 1 Awards 1991

DTIC Science & Technology

1991-01-01

Office: MICOM HUNTSVILLE, AL 35805 Contract #: DAAHO1-92-C-R150 Phone: (205) 876-7502 Pi: D. BRETI BEASLEY Title: INFRARED LASER DIODE BASED INFRARED ...TECHNIQUES WILL BE INVESTIGATED TO DESIGN A FORM FIT GIMBALL-MOUNTED 94 GHZ/ INFRARED FOCAL PLANE ARRAY DUAL-MODE MISSILE SEEKER SENSOR BASED ON LOW...RESOLUTION AT 94 GHZ AND A 128X128 ARRAY IR IMAGE PROCESSING FOR AUTONOMOUS TARGET RECOGNITION AND AIMPOINT SELECTION. THE 94 GHZ AND INFRARED ELECTRONICS

Aerobot Autonomy Architecture

NASA Technical Reports Server (NTRS)

Elfes, Alberto; Hall, Jeffery L.; Kulczycki, Eric A.; Cameron, Jonathan M.; Morfopoulos, Arin C.; Clouse, Daniel S.; Montgomery, James F.; Ansar, Adnan I.; Machuzak, Richard J.

2009-01-01

An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.

State-Estimation Algorithm Based on Computer Vision

NASA Technical Reports Server (NTRS)

Bayard, David; Brugarolas, Paul

2007-01-01

An algorithm and software to implement the algorithm are being developed as means to estimate the state (that is, the position and velocity) of an autonomous vehicle, relative to a visible nearby target object, to provide guidance for maneuvering the vehicle. In the original intended application, the autonomous vehicle would be a spacecraft and the nearby object would be a small astronomical body (typically, a comet or asteroid) to be explored by the spacecraft. The algorithm could also be used on Earth in analogous applications -- for example, for guiding underwater robots near such objects of interest as sunken ships, mineral deposits, or submerged mines. It is assumed that the robot would be equipped with a vision system that would include one or more electronic cameras, image-digitizing circuitry, and an imagedata- processing computer that would generate feature-recognition data products.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

3D range-gated super-resolution imaging based on stereo matching for moving platforms and targets

NASA Astrophysics Data System (ADS)

Sun, Liang; Wang, Xinwei; Zhou, Yan

2017-11-01

3D range-gated superresolution imaging is a novel 3D reconstruction technique for target detection and recognition with good real-time performance. However, for moving targets or platforms such as airborne, shipborne, remote operated vehicle and autonomous vehicle, 3D reconstruction has a large error or failure. In order to overcome this drawback, we propose a method of stereo matching for 3D range-gated superresolution reconstruction algorithm. In experiment, the target is a doll of Mario with a height of 38cm at the location of 34m, and we obtain two successive frame images of the Mario. To confirm our method is effective, we transform the original images with translation, rotation, scale and perspective, respectively. The experimental result shows that our method has a good result of 3D reconstruction for moving targets or platforms.

Higher-order neural network software for distortion invariant object recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

New Autonomous Motors of Metal-Organic Framework (MOF) Powered by Reorganization of Self-Assembled Peptides at interfaces

PubMed Central

Ikezoe, Yasuhiro; Washino, Gosuke; Uemura, Takashi; Kitagawa, Susumu; Matsui, Hiroshi

2012-01-01

There have developed a variety of microsystems that harness energy and convert it to mechanical motion. Here we developed new autonomous biochemical motors by integrating metal-organic framework (MOF) and self-assembling peptides. MOF is applied as an energy-storing cell that assembles peptides inside nanoscale pores of the coordination framework. The robust assembling nature of peptides enables reconfiguring their assemblies at the water-MOF interface, which is converted to fuel energy. Re-organization of hydrophobic peptides could create the large surface tension gradient around the MOF and it efficiently powers the translation motion of MOF. As a comparison, the velocity of normalized by volume for the DPA-MOF particle is faster and the kinetic energy per the unit mass of fuel is more than twice as large as the one for previous gel motor systems. This demonstration opens the new application of MOF and reconfigurable molecular self-assembly and it may evolve into the smart autonomous motor that mimic bacteria to swim and harvest target chemicals by integrating recognition units. PMID:23104155

Using an Improved SIFT Algorithm and Fuzzy Closed-Loop Control Strategy for Object Recognition in Cluttered Scenes

PubMed Central

Nie, Haitao; Long, Kehui; Ma, Jun; Yue, Dan; Liu, Jinguo

2015-01-01

Partial occlusions, large pose variations, and extreme ambient illumination conditions generally cause the performance degradation of object recognition systems. Therefore, this paper presents a novel approach for fast and robust object recognition in cluttered scenes based on an improved scale invariant feature transform (SIFT) algorithm and a fuzzy closed-loop control method. First, a fast SIFT algorithm is proposed by classifying SIFT features into several clusters based on several attributes computed from the sub-orientation histogram (SOH), in the feature matching phase only features that share nearly the same corresponding attributes are compared. Second, a feature matching step is performed following a prioritized order based on the scale factor, which is calculated between the object image and the target object image, guaranteeing robust feature matching. Finally, a fuzzy closed-loop control strategy is applied to increase the accuracy of the object recognition and is essential for autonomous object manipulation process. Compared to the original SIFT algorithm for object recognition, the result of the proposed method shows that the number of SIFT features extracted from an object has a significant increase, and the computing speed of the object recognition processes increases by more than 40%. The experimental results confirmed that the proposed method performs effectively and accurately in cluttered scenes. PMID:25714094

A Face Attention Technique for a Robot Able to Interpret Facial Expressions

NASA Astrophysics Data System (ADS)

Simplício, Carlos; Prado, José; Dias, Jorge

Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.

An autonomous rendezvous and docking system using cruise missile technologies

NASA Technical Reports Server (NTRS)

Jones, Ruel Edwin

1991-01-01

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery.

Autonomous planning and scheduling on the TechSat 21 mission

NASA Technical Reports Server (NTRS)

Sherwood, R.; Chien, S.; Castano, R.; Rabideau, G.

2002-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting.

When Early Experiences Build a Wall to Others’ Emotions: An Electrophysiological and Autonomic Study

PubMed Central

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Sestito, Mariateresa; Ravera, Roberto; Gallese, Vittorio

2013-01-01

Facial expression of emotions is a powerful vehicle for communicating information about others’ emotional states and it normally induces facial mimicry in the observers. The aim of this study was to investigate if early aversive experiences could interfere with emotion recognition, facial mimicry, and with the autonomic regulation of social behaviors. We conducted a facial emotion recognition task in a group of “street-boys” and in an age-matched control group. We recorded facial electromyography (EMG), a marker of facial mimicry, and respiratory sinus arrhythmia (RSA), an index of the recruitment of autonomic system promoting social behaviors and predisposition, in response to the observation of facial expressions of emotions. Results showed an over-attribution of anger, and reduced EMG responses during the observation of both positive and negative expressions only among street-boys. Street-boys also showed lower RSA after observation of facial expressions and ineffective RSA suppression during presentation of non-threatening expressions. Our findings suggest that early aversive experiences alter not only emotion recognition but also facial mimicry of emotions. These deficits affect the autonomic regulation of social behaviors inducing lower social predisposition after the visualization of facial expressions and an ineffective recruitment of defensive behavior in response to non-threatening expressions. PMID:23593374

Shape and Color Features for Object Recognition Search

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

2012-01-01

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor.

PubMed

Hoang, Toan Minh; Baek, Na Rae; Cho, Se Woon; Kim, Ki Wan; Park, Kang Ryoung

2017-10-28

Recently, autonomous vehicles, particularly self-driving cars, have received significant attention owing to rapid advancements in sensor and computation technologies. In addition to traffic sign recognition, road lane detection is one of the most important factors used in lane departure warning systems and autonomous vehicles for maintaining the safety of semi-autonomous and fully autonomous systems. Unlike traffic signs, road lanes are easily damaged by both internal and external factors such as road quality, occlusion (traffic on the road), weather conditions, and illumination (shadows from objects such as cars, trees, and buildings). Obtaining clear road lane markings for recognition processing is a difficult challenge. Therefore, we propose a method to overcome various illumination problems, particularly severe shadows, by using fuzzy system and line segment detector algorithms to obtain better results for detecting road lanes by a visible light camera sensor. Experimental results from three open databases, Caltech dataset, Santiago Lanes dataset (SLD), and Road Marking dataset, showed that our method outperformed conventional lane detection methods.

Bringing UAVs to the fight: recent army autonomy research and a vision for the future

NASA Astrophysics Data System (ADS)

Moorthy, Jay; Higgins, Raymond; Arthur, Keith

2008-04-01

The Unmanned Autonomous Collaborative Operations (UACO) program was initiated in recognition of the high operational burden associated with utilizing unmanned systems by both mounted and dismounted, ground and airborne warfighters. The program was previously introduced at the 62nd Annual Forum of the American Helicopter Society in May of 20061. This paper presents the three technical approaches taken and results obtained in UACO. All three approaches were validated extensively in contractor simulations, two were validated in government simulation, one was flight tested outside the UACO program, and one was flight tested in Part 2 of UACO. Results and recommendations are discussed regarding diverse areas such as user training and human-machine interface, workload distribution, UAV flight safety, data link bandwidth, user interface constructs, adaptive algorithms, air vehicle system integration, and target recognition. Finally, a vision for UAV As A Wingman is presented.

Scannerless laser range imaging using loss modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sandusky, John V

2011-08-09

A scannerless 3-D imaging apparatus is disclosed which utilizes an amplitude modulated cw light source to illuminate a field of view containing a target of interest. Backscattered light from the target is passed through one or more loss modulators which are modulated at the same frequency as the light source, but with a phase delay .delta. which can be fixed or variable. The backscattered light is demodulated by the loss modulator and detected with a CCD, CMOS or focal plane array (FPA) detector to construct a 3-D image of the target. The scannerless 3-D imaging apparatus, which can operate inmore » the eye-safe wavelength region 1.4-1.7 .mu.m and which can be constructed as a flash LADAR, has applications for vehicle collision avoidance, autonomous rendezvous and docking, robotic vision, industrial inspection and measurement, 3-D cameras, and facial recognition.« less

Scannerless laser range imaging using loss modulation

DOEpatents

Sandusky, John V [Albuquerque, NM

2011-08-09

A scannerless 3-D imaging apparatus is disclosed which utilizes an amplitude modulated cw light source to illuminate a field of view containing a target of interest. Backscattered light from the target is passed through one or more loss modulators which are modulated at the same frequency as the light source, but with a phase delay .delta. which can be fixed or variable. The backscattered light is demodulated by the loss modulator and detected with a CCD, CMOS or focal plane array (FPA) detector to construct a 3-D image of the target. The scannerless 3-D imaging apparatus, which can operate in the eye-safe wavelength region 1.4-1.7 .mu.m and which can be constructed as a flash LADAR, has applications for vehicle collision avoidance, autonomous rendezvous and docking, robotic vision, industrial inspection and measurement, 3-D cameras, and facial recognition.

SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal.

PubMed

Gnadt, William; Grossberg, Stephen

2008-06-01

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.

Real-time road detection in infrared imagery

NASA Astrophysics Data System (ADS)

Andre, Haritini E.; McCoy, Keith

1990-09-01

Automatic road detection is an important part in many scene recognition applications. The extraction of roads provides a means of navigation and position update for remotely piloted vehicles or autonomous vehicles. Roads supply strong contextual information which can be used to improve the performance of automatic target recognition (ATh) systems by directing the search for targets and adjusting target classification confidences. This paper will describe algorithmic techniques for labeling roads in high-resolution infrared imagery. In addition, realtime implementation of this structural approach using a processor array based on the Martin Marietta Geometric Arithmetic Parallel Processor (GAPPTh) chip will be addressed. The algorithm described is based on the hypothesis that a road consists of pairs of line segments separated by a distance "d" with opposite gradient directions (antiparallel). The general nature of the algorithm, in addition to its parallel implementation in a single instruction, multiple data (SIMD) machine, are improvements to existing work. The algorithm seeks to identify line segments meeting the road hypothesis in a manner that performs well, even when the side of the road is fragmented due to occlusion or intersections. The use of geometrical relationships between line segments is a powerful yet flexible method of road classification which is independent of orientation. In addition, this approach can be used to nominate other types of objects with minor parametric changes.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner.

PubMed

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-07-20

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner

PubMed Central

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-01-01

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation. PMID:27447640

Background Characterization Techniques For Pattern Recognition Applications

NASA Astrophysics Data System (ADS)

Noah, Meg A.; Noah, Paul V.; Schroeder, John W.; Kessler, Bernard V.; Chernick, Julian A.

1989-08-01

The Department of Defense has a requirement to investigate technologies for the detection of air and ground vehicles in a clutter environment. The use of autonomous systems using infrared, visible, and millimeter wave detectors has the potential to meet DOD's needs. In general, however, the hard-ware technology (large detector arrays with high sensitivity) has outpaced the development of processing techniques and software. In a complex background scene the "problem" is as much one of clutter rejection as it is target detection. The work described in this paper has investigated a new, and innovative, methodology for background clutter characterization, target detection and target identification. The approach uses multivariate statistical analysis to evaluate a set of image metrics applied to infrared cloud imagery and terrain clutter scenes. The techniques are applied to two distinct problems: the characterization of atmospheric water vapor cloud scenes for the Navy's Infrared Search and Track (IRST) applications to support the Infrared Modeling Measurement and Analysis Program (IRAMMP); and the detection of ground vehicles for the Army's Autonomous Homing Munitions (AHM) problems. This work was sponsored under two separate Small Business Innovative Research (SBIR) programs by the Naval Surface Warfare Center (NSWC), White Oak MD, and the Army Material Systems Analysis Activity at Aberdeen Proving Ground MD. The software described in this paper will be available from the respective contract technical representatives.

Cultural differences in self-recognition: the early development of autonomous and related selves?

PubMed

Ross, Josephine; Yilmaz, Mandy; Dale, Rachel; Cassidy, Rose; Yildirim, Iraz; Suzanne Zeedyk, M

2017-05-01

Fifteen- to 18-month-old infants from three nationalities were observed interacting with their mothers and during two self-recognition tasks. Scottish interactions were characterized by distal contact, Zambian interactions by proximal contact, and Turkish interactions by a mixture of contact strategies. These culturally distinct experiences may scaffold different perspectives on self. In support, Scottish infants performed best in a task requiring recognition of the self in an individualistic context (mirror self-recognition), whereas Zambian infants performed best in a task requiring recognition of the self in a less individualistic context (body-as-obstacle task). Turkish infants performed similarly to Zambian infants on the body-as-obstacle task, but outperformed Zambians on the mirror self-recognition task. Verbal contact (a distal strategy) was positively related to mirror self-recognition and negatively related to passing the body-as-obstacle task. Directive action and speech (proximal strategies) were negatively related to mirror self-recognition. Self-awareness performance was best predicted by cultural context; autonomous settings predicted success in mirror self-recognition, and related settings predicted success in the body-as-obstacle task. These novel data substantiate the idea that cultural factors may play a role in the early expression of self-awareness. More broadly, the results highlight the importance of moving beyond the mark test, and designing culturally sensitive tests of self-awareness. © 2016 John Wiley & Sons Ltd.

Simulation of laser detection and ranging (LADAR) and forward-looking infrared (FLIR) data for autonomous tracking of airborne objects

NASA Astrophysics Data System (ADS)

Powell, Gavin; Markham, Keith C.; Marshall, David

2000-06-01

This paper presents the results of an investigation leading into an implementation of FLIR and LADAR data simulation for use in a multi sensor data fusion automated target recognition system. At present the main areas of application are in military environments but systems can easily be adapted to other areas such as security applications, robotics and autonomous cars. Recent developments have been away from traditional sensor modeling and toward modeling of features that are external to the system, such as atmosphere and part occlusion, to create a more realistic and rounded system. We have implemented such techniques and introduced a means of inserting these models into a highly detailed scene model to provide a rich data set for later processing. From our study and implementation we are able to embed sensor model components into a commercial graphics and animation package, along with object and terrain models, which can be easily used to create a more realistic sequence of images.

Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor

PubMed Central

Hoang, Toan Minh; Baek, Na Rae; Cho, Se Woon; Kim, Ki Wan; Park, Kang Ryoung

2017-01-01

Recently, autonomous vehicles, particularly self-driving cars, have received significant attention owing to rapid advancements in sensor and computation technologies. In addition to traffic sign recognition, road lane detection is one of the most important factors used in lane departure warning systems and autonomous vehicles for maintaining the safety of semi-autonomous and fully autonomous systems. Unlike traffic signs, road lanes are easily damaged by both internal and external factors such as road quality, occlusion (traffic on the road), weather conditions, and illumination (shadows from objects such as cars, trees, and buildings). Obtaining clear road lane markings for recognition processing is a difficult challenge. Therefore, we propose a method to overcome various illumination problems, particularly severe shadows, by using fuzzy system and line segment detector algorithms to obtain better results for detecting road lanes by a visible light camera sensor. Experimental results from three open databases, Caltech dataset, Santiago Lanes dataset (SLD), and Road Marking dataset, showed that our method outperformed conventional lane detection methods. PMID:29143764

In flight image processing on multi-rotor aircraft for autonomous landing

NASA Astrophysics Data System (ADS)

Henry, Richard, Jr.

An estimated $6.4 billion was spent during the year 2013 on developing drone technology around the world and is expected to double in the next decade. However, drone applications typically require strong pilot skills, safety, responsibilities and adherence to regulations during flight. If the flight control process could be safer and more reliable in terms of landing, it would be possible to further develop a wider range of applications. The objective of this research effort is to describe the design and evaluation of a fully autonomous Unmanned Aerial system (UAS), specifically a four rotor aircraft, commonly known as quad copter for precise landing applications. The full landing autonomy is achieved by image processing capabilities during flight for target recognition by employing the open source library OpenCV. In addition, all imaging data is processed by a single embedded computer that estimates a relative position with respect to the target landing pad. Results shows a reduction on the average offset error by 67.88% in comparison to the current return to lunch (RTL) method which only relies on GPS positioning. The present work validates the need for relying on image processing for precise landing applications instead of the inexact method of a commercial low cost GPS dependency.

Autonomous operations through onboard artificial intelligence

NASA Technical Reports Server (NTRS)

Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

2002-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

Environmental Recognition and Guidance Control for Autonomous Vehicles using Dual Vision Sensor and Applications

NASA Astrophysics Data System (ADS)

Moriwaki, Katsumi; Koike, Issei; Sano, Tsuyoshi; Fukunaga, Tetsuya; Tanaka, Katsuyuki

We propose a new method of environmental recognition around an autonomous vehicle using dual vision sensor and navigation control based on binocular images. We consider to develop a guide robot that can play the role of a guide dog as the aid to people such as the visually impaired or the aged, as an application of above-mentioned techniques. This paper presents a recognition algorithm, which finds out the line of a series of Braille blocks and the boundary line between a sidewalk and a roadway where a difference in level exists by binocular images obtained from a pair of parallelarrayed CCD cameras. This paper also presents a tracking algorithm, with which the guide robot traces along a series of Braille blocks and avoids obstacles and unsafe areas which exist in the way of a person with the guide robot.

The nature of the autonomic dysfunction in multiple system atrophy

NASA Technical Reports Server (NTRS)

Parikh, Samir M.; Diedrich, Andre; Biaggioni, Italo; Robertson, David

2002-01-01

The concept that multiple system atrophy (MSA, Shy-Drager syndrome) is a disorder of the autonomic nervous system is several decades old. While there has been renewed interest in the movement disorder associated with MSA, two recent consensus statements confirm the centrality of the autonomic disorder to the diagnosis. Here, we reexamine the autonomic pathophysiology in MSA. Whereas MSA is often thought of as "autonomic failure", new evidence indicates substantial persistence of functioning sympathetic and parasympathetic nerves even in clinically advanced disease. These findings help explain some of the previously poorly understood features of MSA. Recognition that MSA entails persistent, constitutive autonomic tone requires a significant revision of our concepts of its diagnosis and therapy. We will review recent evidence bearing on autonomic tone in MSA and discuss their therapeutic implications, particularly in terms of the possible development of a bionic baroreflex for better control of blood pressure.

Antigen clasping by two antigen-binding sites of an exceptionally specific antibody for histone methylation

DOE PAGES

Hattori, Takamitsu; Lai, Darson; Dementieva, Irina S.; ...

2016-02-09

Antibodies have a well-established modular architecture wherein the antigen-binding site residing in the antigen-binding fragment (Fab or Fv) is an autonomous and complete unit for antigen recognition. Here, we describe antibodies departing from this paradigm. We developed recombinant antibodies to trimethylated lysine residues on histone H3, important epigenetic marks and challenging targets for molecular recognition. Quantitative characterization demonstrated their exquisite specificity and high affinity, and they performed well in common epigenetics applications. Surprisingly, crystal structures and biophysical analyses revealed that two antigen-binding sites of these antibodies form a head-to-head dimer and cooperatively recognize the antigen in the dimer interface. Thismore » “antigen clasping” produced an expansive interface where trimethylated Lys bound to an unusually extensive aromatic cage in one Fab and the histone N terminus to a pocket in the other, thereby rationalizing the high specificity. A long-neck antibody format with a long linker between the antigen-binding module and the Fc region facilitated antigen clasping and achieved both high specificity and high potency. Antigen clasping substantially expands the paradigm of antibody–antigen recognition and suggests a strategy for developing extremely specific antibodies.« less

Antigen clasping by two antigen-binding sites of an exceptionally specific antibody for histone methylation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hattori, Takamitsu; Lai, Darson; Dementieva, Irina S.

Antibodies have a well-established modular architecture wherein the antigen-binding site residing in the antigen-binding fragment (Fab or Fv) is an autonomous and complete unit for antigen recognition. Here, we describe antibodies departing from this paradigm. We developed recombinant antibodies to trimethylated lysine residues on histone H3, important epigenetic marks and challenging targets for molecular recognition. Quantitative characterization demonstrated their exquisite specificity and high affinity, and they performed well in common epigenetics applications. Surprisingly, crystal structures and biophysical analyses revealed that two antigen-binding sites of these antibodies form a head-to-head dimer and cooperatively recognize the antigen in the dimer interface. Thismore » “antigen clasping” produced an expansive interface where trimethylated Lys bound to an unusually extensive aromatic cage in one Fab and the histone N terminus to a pocket in the other, thereby rationalizing the high specificity. A long-neck antibody format with a long linker between the antigen-binding module and the Fc region facilitated antigen clasping and achieved both high specificity and high potency. Antigen clasping substantially expands the paradigm of antibody–antigen recognition and suggests a strategy for developing extremely specific antibodies.« less

Flight Mechanics/Estimation Theory Symposium. [with application to autonomous navigation and attitude/orbit determination

NASA Technical Reports Server (NTRS)

Fuchs, A. J. (Editor)

1979-01-01

Onboard and real time image processing to enhance geometric correction of the data is discussed with application to autonomous navigation and attitude and orbit determination. Specific topics covered include: (1) LANDSAT landmark data; (2) star sensing and pattern recognition; (3) filtering algorithms for Global Positioning System; and (4) determining orbital elements for geostationary satellites.

Bioinspired polarization navigation sensor for autonomous munitions systems

NASA Astrophysics Data System (ADS)

Giakos, G. C.; Quang, T.; Farrahi, T.; Deshpande, A.; Narayan, C.; Shrestha, S.; Li, Y.; Agarwal, M.

2013-05-01

Small unmanned aerial vehicles UAVs (SUAVs), micro air vehicles (MAVs), Automated Target Recognition (ATR), and munitions guidance, require extreme operational agility and robustness which can be partially offset by efficient bioinspired imaging sensor designs capable to provide enhanced guidance, navigation and control capabilities (GNC). Bioinspired-based imaging technology can be proved useful either for long-distance surveillance of targets in a cluttered environment, or at close distances limited by space surroundings and obstructions. The purpose of this study is to explore the phenomenology of image formation by different insect eye architectures, which would directly benefit the areas of defense and security, on the following four distinct areas: a) fabrication of the bioinspired sensor b) optical architecture, c) topology, and d) artificial intelligence. The outcome of this study indicates that bioinspired imaging can impact the areas of defense and security significantly by dedicated designs fitting into different combat scenarios and applications.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources.

PubMed

Liu, Yu-Ting; Pal, Nikhil R; Marathe, Amar R; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources

PubMed Central

Liu, Yu-Ting; Pal, Nikhil R.; Marathe, Amar R.; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems. PMID:28676734

The Development of Mirror Self-Recognition in Different Sociocultural Contexts

ERIC Educational Resources Information Center

Kartner, Joscha; Keller, Heidi; Chaudhary, Nandita; Yovsi, Relindis D.

2012-01-01

The overarching goal of the present study was to trace the development of mirror self-recognition (MSR), as an index of toddlers' sense of themselves and others as autonomous intentional agents, in different sociocultural environments. A total of 276 toddlers participated in the present study. Toddlers were either 16, 17, 18, 19, 20, or 21 months…

Emotion Recognition in Children with Autism Spectrum Disorders: Relations to Eye Gaze and Autonomic State

ERIC Educational Resources Information Center

Bal, Elgiz; Harden, Emily; Lamb, Damon; Van Hecke, Amy Vaughan; Denver, John W.; Porges, Stephen W.

2010-01-01

Respiratory Sinus Arrhythmia (RSA), heart rate, and accuracy and latency of emotion recognition were evaluated in children with autism spectrum disorders (ASD) and typically developing children while viewing videos of faces slowly transitioning from a neutral expression to one of six basic emotions (e.g., anger, disgust, fear, happiness, sadness,…

Ultrasensitive electrochemical sensing platform based on graphene wrapping SnO2 nanocorals and autonomous cascade DNA duplication strategy.

PubMed

Chen, Ying-Xu; Huang, Ke-Jing; Lin, Feng; Fang, Lin-Xia

2017-12-01

In this work, a sensitive, universal and reusable electrochemical biosensor based on stannic oxide nanocorals-graphene hybrids (SnO 2 NCs-Gr) is developed for target DNA detection by using two kinds of DNA enzymes for signal amplification through an autonomous cascade DNA duplication strategy. A hairpin probe is designed composing of a projecting part at the 3'-end as identification sequence for target, a recognition site for nicking endonuclease, and an 18-carbon shim to stop polymerization process. The designed DNA duplication-incision-replacement process is handled by KF polymerase and endonuclease, then combining with gold nanoparticles as signal carrier for further signal amplification. In the detection system, the electrochemical-chemical-chemical procedure, which uses ferrocene methanol, tris(2-carboxyethyl)phosphine and l-ascorbic acid 2-phosphate as oxidoreduction neurogen, deoxidizer and zymolyte, separately, is applied to amplify detection signal. Benefiting from the multiple signal amplification mechanism, the proposed sensor reveals a good linear connection between the peak current and logarithm of analyte concentration in range of 0.0001-1 × 10 -11 molL -1 with a detection limit of 1.25 × 10 -17 molL -1 (S/N=3). This assay also opens one promising strategy for ultrasensitive determination of other biological molecules for bioanalysis and biomedicine diagnostics. Copyright © 2017 Elsevier B.V. All rights reserved.

[Characteristics of communication systems of suspected occupational disease in the Autonomous Communities, Spain].

PubMed

García Gómez, Montserrat; Urbaneja Arrúe, Félix; García López, Vega; Estaban Buedo, Valentín; Rodríguez Suárez, Valentín; Miralles Martínez-Portillo, Lourdes; González García, Isabel; Egea Garcia, Josefa; Corraliza Infanzon, Emma; Ramírez Salvador, Laura; Briz Blázquez, Santiago; Armengol Rosell, Ricard; Cisnal Gredilla, José María; Correa Rodríguez, Juan Francisco; Coto Fernández, Juan Carlos; Díaz Peral, Mª Rosario; Elvira Espinosa, Mercedes; Fernández Fernández, Iñigo; García-Ramos Alonso, Eduardo; Martínez Arguisuelas, Nieves; Rivas Pérez, Ana Isabel

2017-03-17

There are several initiatives to develop systems for the notification of suspected occupational disease (OD) in different autonomous communities. The objective was to describe the status of development and characteristics of these systems implemented by the health authorities. A cross-sectional descriptive study was carried out on the existence of systems for the information and surveillance of suspected OD, their legal framework, responsible institution and availability of information. A specific meeting was held and a survey was designed and sent to all autonomous communities and autonomous cities (AACC). Information was collected on the existence of a regulatory standard, assigned human resources, notifiers, coverage and number of suspected OD received, processed and recognized. 18 of 19 AACC responded. 10 have developed a suspected OD notification system, 3 of them supported by specific autonomic law. The notifiers were physicians of the public health services, physicians of the occupational health services and, in 2 cases, medical inspectors. 7 AACC had specific software to support the system. The OD recognition rate of suspected cases was 53% in the Basque Country; 41% in Castilla-La Mancha; 36% in Murcia; 32.6% in the Valencian Community and 31% in La Rioja. The study has revealed an heterogeneous development of suspected OD reporting systems in Spain. Although the trend is positive, only 55% of the AACC have some type of development and 39% have specific software supporting it. Therefore unequal OD recognition rates have been obtained depending on the territory.

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device.

PubMed

Popok, David; West, Christopher; Frias, Barbara; Krassioukov, Andrei V

2016-07-29

Spinal cord injury (SCI) is a debilitating neurological condition characterized by somatic and autonomic dysfunctions. In particular, SCI above the mid-thoracic level can lead to a potentially life-threatening hypertensive condition called autonomic dysreflexia (AD) that is often triggered by noxious or non-noxious somatic or visceral stimuli below the level of injury. One of the most common triggers of AD is the distension of pelvic viscera, such as during bladder and bowel distension or evacuation. This protocol presents a novel pattern recognition algorithm developed for a JAVA platform software to study the fluctuations of cardiovascular parameters as well as the number, severity and duration of spontaneously occurring AD events. The software is able to apply a pattern recognition algorithm on hemodynamic data such as systolic blood pressure (SBP) and heart rate (HR) extracted from telemetry recordings of conscious and unrestrained animals before and after thoracic (T3) complete transection. With this software, hemodynamic parameters and episodes of AD are able to be detected and analyzed with minimal experimenter bias.

Free-Flight Terrestrial Rocket Lander Demonstration for NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System

NASA Technical Reports Server (NTRS)

Rutishauser, David K.; Epp, Chirold; Robertson, Ed

2012-01-01

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. Since its inception in 2006, the ALHAT Project has executed four field test campaigns to characterize and mature sensors and algorithms that support real-time hazard detection and global/local precision navigation for planetary landings. The driving objective for Government Fiscal Year 2012 (GFY2012) is to successfully demonstrate autonomous, real-time, closed loop operation of the ALHAT system in a realistic free flight scenario on Earth using the Morpheus lander developed at the Johnson Space Center (JSC). This goal represents an aggressive target consistent with a lean engineering culture of rapid prototyping and development. This culture is characterized by prioritizing early implementation to gain practical lessons learned and then building on this knowledge with subsequent prototyping design cycles of increasing complexity culminating in the implementation of the baseline design. This paper provides an overview of the ALHAT/Morpheus flight demonstration activities in GFY2012, including accomplishments, current status, results, and lessons learned. The ALHAT/Morpheus effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

The autonomous sciencecraft constellations

NASA Technical Reports Server (NTRS)

Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

2003-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

Control system of hexacopter using color histogram footprint and convolutional neural network

NASA Astrophysics Data System (ADS)

Ruliputra, R. N.; Darma, S.

2017-07-01

The development of unmanned aerial vehicles (UAV) has been growing rapidly in recent years. The use of logic thinking which is implemented into the program algorithms is needed to make a smart system. By using visual input from a camera, UAV is able to fly autonomously by detecting a target. However, some weaknesses arose as usage in the outdoor environment might change the target's color intensity. Color histogram footprint overcomes the problem because it divides color intensity into separate bins that make the detection tolerant to the slight change of color intensity. Template matching compare its detection result with a template of the reference image to determine the target position and use it to position the vehicle in the middle of the target with visual feedback control based on Proportional-Integral-Derivative (PID) controller. Color histogram footprint method localizes the target by calculating the back projection of its histogram. It has an average success rate of 77 % from a distance of 1 meter. It can position itself in the middle of the target by using visual feedback control with an average positioning time of 73 seconds. After the hexacopter is in the middle of the target, Convolutional Neural Networks (CNN) classifies a number contained in the target image to determine a task depending on the classified number, either landing, yawing, or return to launch. The recognition result shows an optimum success rate of 99.2 %.

PRoViScout: a planetary scouting rover demonstrator

NASA Astrophysics Data System (ADS)

Paar, Gerhard; Woods, Mark; Gimkiewicz, Christiane; Labrosse, Frédéric; Medina, Alberto; Tyler, Laurence; Barnes, David P.; Fritz, Gerald; Kapellos, Konstantinos

2012-01-01

Mobile systems exploring Planetary surfaces in future will require more autonomy than today. The EU FP7-SPACE Project ProViScout (2010-2012) establishes the building blocks of such autonomous exploration systems in terms of robotics vision by a decision-based combination of navigation and scientific target selection, and integrates them into a framework ready for and exposed to field demonstration. The PRoViScout on-board system consists of mission management components such as an Executive, a Mars Mission On-Board Planner and Scheduler, a Science Assessment Module, and Navigation & Vision Processing modules. The platform hardware consists of the rover with the sensors and pointing devices. We report on the major building blocks and their functions & interfaces, emphasizing on the computer vision parts such as image acquisition (using a novel zoomed 3D-Time-of-Flight & RGB camera), mapping from 3D-TOF data, panoramic image & stereo reconstruction, hazard and slope maps, visual odometry and the recognition of potential scientifically interesting targets.

Sign detection for autonomous navigation

NASA Astrophysics Data System (ADS)

Goodsell, Thomas G.; Snorrason, Magnus S.; Cartwright, Dustin; Stube, Brian; Stevens, Mark R.; Ablavsky, Vitaly X.

2003-09-01

Mobile robots currently cannot detect and read arbitrary signs. This is a major hindrance to mobile robot usability, since they cannot be tasked using directions that are intuitive to humans. It also limits their ability to report their position relative to intuitive landmarks. Other researchers have demonstrated some success on traffic sign recognition, but using template based methods limits the set of recognizable signs. There is a clear need for a sign detection and recognition system that can process a much wider variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. We are developing a system for Sign Understanding in Support of Autonomous Navigation (SUSAN), that detects signs from various cues common to most signs: vivid colors, compact shape, and text. We have demonstrated the feasibility of our approach on a variety of signs in both indoor and outdoor locations.

Environmental modeling and recognition for an autonomous land vehicle

NASA Technical Reports Server (NTRS)

Lawton, D. T.; Levitt, T. S.; Mcconnell, C. C.; Nelson, P. C.

1987-01-01

An architecture for object modeling and recognition for an autonomous land vehicle is presented. Examples of objects of interest include terrain features, fields, roads, horizon features, trees, etc. The architecture is organized around a set of data bases for generic object models and perceptual structures, temporary memory for the instantiation of object and relational hypotheses, and a long term memory for storing stable hypotheses that are affixed to the terrain representation. Multiple inference processes operate over these databases. Researchers describe these particular components: the perceptual structure database, the grouping processes that operate over this, schemas, and the long term terrain database. A processing example that matches predictions from the long term terrain model to imagery, extracts significant perceptual structures for consideration as potential landmarks, and extracts a relational structure to update the long term terrain database is given.

Autonomic imbalance is associated with reduced facial recognition in somatoform disorders.

PubMed

Pollatos, Olga; Herbert, Beate M; Wankner, Sarah; Dietel, Anja; Wachsmuth, Cornelia; Henningsen, Peter; Sack, Martin

2011-10-01

Somatoform disorders are characterized by the presence of multiple somatic symptoms. While the accuracy of perceiving bodily signal (interoceptive awareness) is only sparely investigated in somatoform disorders, recent research has associated autonomic imbalance with cognitive and emotional difficulties in stress-related diseases. This study aimed to investigate how sympathovagal reactivity interacts with performance in recognizing emotions in faces (facial recognition task). Using a facial recognition and appraisal task, skin conductance levels (SCLs), heart rate (HR) and heart rate variability (HRV) were assessed in 26 somatoform patients and compared to healthy controls. Interoceptive awareness was assessed by a heartbeat detection task. We found evidence for a sympathovagal imbalance in somatoform disorders characterized by low parasympathetic reactivity during emotional tasks and increased sympathetic activation during baseline. Somatoform patients exhibited a reduced recognition performance for neutral and sad emotional expressions only. Possible confounding variables such as alexithymia, anxiety or depression were taken into account. Interoceptive awareness was reduced in somatoform patients. Our data demonstrate an imbalance in sympathovagal activation in somatoform disorders associated with decreased parasympathetic activation. This might account for difficulties in processing of sad and neutral facial expressions in somatoform patients which might be a pathogenic mechanism for increased everyday vulnerability. Copyright © 2011 Elsevier Inc. All rights reserved.

A comparison of image processing techniques for bird recognition.

PubMed

Nadimpalli, Uma D; Price, Randy R; Hall, Steven G; Bomma, Pallavi

2006-01-01

Bird predation is one of the major concerns for fish culture in open ponds. A novel method for dispersing birds is the use of autonomous vehicles. Image recognition software can improve their efficiency. Several image processing techniques for recognition of birds have been tested. A series of morphological operations were implemented. We divided images into 3 types, Type 1, Type 2, and Type 3, based on the level of difficulty of recognizing birds. Type 1 images were clear; Type 2 images were medium clear, and Type 3 images were unclear. Local thresholding has been implemented using HSV (Hue, Saturation, and Value), GRAY, and RGB (Red, Green, and Blue) color models on all three sections of images and results were tabulated. Template matching using normal correlation and artificial neural networks (ANN) are the other methods that have been developed in this study in addition to image morphology. Template matching produced satisfactory results irrespective of the difficulty level of images, but artificial neural networks produced accuracies of 100, 60, and 50% on Type 1, Type 2, and Type 3 images, respectively. Correct classification rate can be increased by further training. Future research will focus on testing the recognition algorithms in natural or aquacultural settings on autonomous boats. Applications of such techniques to industrial, agricultural, or related areas are additional future possibilities.

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

NASA Technical Reports Server (NTRS)

Brockers, Roland; Ma, Jeremy C.; Matthies, Larry H.; Bouffard, Patrick

2012-01-01

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

First Image from a Mars Rover Choosing a Target

NASA Image and Video Library

2010-03-23

This true-color image is the result of the first observation of a target selected autonomously by NASA Mars Exploration Rover Opportunity using newly developed and uploaded software named Autonomous Exploration for Gathering Increased Science, or AEGIS.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

Context recognition and situation assessment in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Yavnai, Arie

1993-05-01

The capability to recognize the operating context and to assess the situation in real-time is needed, if a high functionality autonomous mobile robot has to react properly and effectively to continuously changing situations and events, either external or internal, while the robot is performing its assigned tasks. A new approach and architecture for context recognition and situation assessment module (CORSA) is presented in this paper. CORSA is a multi-level information processing module which consists of adaptive decision and classification algorithms. It performs dynamic mapping from the data space to the context space, and dynamically decides on the context class. Learning mechanism is employed to update the decision variables so as to minimize the probability of misclassification. CORSA is embedded within the Mission Manager module of the intelligent autonomous hyper-controller (IAHC) of the mobile robot. The information regarding operating context, events and situation is then communicated to other modules of the IAHC where it is used to: (a) select the appropriate action strategy; (b) support the processes to arbitration and conflict resolution between reflexive behaviors and reasoning-driven behaviors; (c) predict future events and situations; and (d) determine criteria and priorities for planning, replanning, and decision making.

"The face of ostracism": The impact of the social categorization on the thermal facial responses of the target and the observer.

PubMed

Paolini, Daniele; Alparone, Francesca R; Cardone, Daniela; van Beest, Ilja; Merla, Arcangelo

2016-01-01

Ostracism has been shown to elicit pain in both the target and the observers. Two experiments investigated the autonomic thermal signature associated with an ostracism experience and assessed whether and how social categorization impacts the autonomic arousal of both the target and the observer. Autonomic response was assessed using thermal infrared imaging, recording facial temperature variation during an online game of ball toss (i.e., Cyberball). Social categorization was manipulated using a minimal group paradigm. The results show a more intense autonomic response during ostracism (vs. inclusion), marked by an increase in facial temperature in the nose and the perioral area. This autonomic response is stronger when individuals are ostracized by ingroup (vs. outgroup) members. Similar pattern of temperature variations emerge when individuals observe an ostracism episode involving ingroup members. Our findings advance the understanding of psycho-physiological mechanisms underlying the ostracism experience and emphasize the impact of social categorization in such mechanisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

NASA Technical Reports Server (NTRS)

Neilan, James H.; Cross, Charles; Rothhaar, Paul; Tran, Loc; Motter, Mark; Qualls, Garry; Trujillo, Anna; Allen, B. Danette

2016-01-01

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Nature and extent of person recognition impairments associated with Capgras syndrome in Lewy body dementia

PubMed Central

Fiacconi, Chris M.; Barkley, Victoria; Finger, Elizabeth C.; Carson, Nicole; Duke, Devin; Rosenbaum, R. Shayna; Gilboa, Asaf; Köhler, Stefan

2014-01-01

Patients with Capgras syndrome (CS) adopt the delusional belief that persons well-known to them have been replaced by an imposter. Several current theoretical models of CS attribute such misidentification problems to deficits in covert recognition processes related to the generation of appropriate affective autonomic signals. These models assume intact overt recognition processes for the imposter and, more broadly, for other individuals. As such, it has been suggested that CS could reflect the “mirror-image” of prosopagnosia. The purpose of the current study was to determine whether overt person recognition abilities are indeed always spared in CS. Furthermore, we examined whether CS might be associated with any impairments in overt affective judgments of facial expressions. We pursued these goals by studying a patient with Dementia with Lewy bodies (DLB) who showed clear signs of CS, and by comparing him to another patient with DLB who did not experience CS, as well as to a group of healthy control participants. Clinical magnetic resonance imaging scans revealed medial prefrontal cortex (mPFC) atrophy that appeared to be uniquely associated with the presence CS. We assessed overt person recognition with three fame recognition tasks, using faces, voices, and names as cues. We also included measures of confidence and probed pertinent semantic knowledge. In addition, participants rated the intensity of fearful facial expressions. We found that CS was associated with overt person recognition deficits when probed with faces and voices, but not with names. Critically, these deficits were not present in the DLB patient without CS. In addition, CS was associated with impairments in overt judgments of affect intensity. Taken together, our findings cast doubt on the traditional view that CS is the mirror-image of prosopagnosia and that it spares overt recognition abilities. These findings can still be accommodated by models of CS that emphasize deficits in autonomic responding, to the extent that the potential role of interoceptive awareness in overt judgments is taken into account. PMID:25309399

Three-dimensional obstacle classification in laser range data

NASA Astrophysics Data System (ADS)

Armbruster, Walter; Bers, Karl-Heinz

1998-10-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser rangefinders which are presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from wires at over 500 m range (depends on the system) with a high hit-and-detect probability. Despite the efficiency of the sensor, acceptance of current obstacle warning systems by test pilots is not very high, mainly due to the systems' inadequacies in obstacle recognition and visualization. This has motivated the development and the testing of more advanced 3d-scene analysis algorithm at FGAN-FIM to replace the obstacle recognition component of current warning systems. The basic ideas are to increase the recognition probability and to reduce the false alarm rate for hard-to-extract obstacles such as wires, by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. by implementing a hierarchical classification procedure to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition.

Recognition of flow in everyday life using sensor agent robot with laser range finder

NASA Astrophysics Data System (ADS)

Goshima, Misa; Mita, Akira

2011-04-01

In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

Engineering self-contained DNA circuit for proximity recognition and localized signal amplification of target biomolecules

PubMed Central

Ang, Yan Shan; Yung, Lin-Yue Lanry

2014-01-01

Biomolecular interactions have important cellular implications, however, a simple method for the sensing of such proximal events is lacking in the current molecular toolbox. We designed a dynamic DNA circuit capable of recognizing targets in close proximity to initiate a pre-programmed signal transduction process resulting in localized signal amplification. The entire circuit was engineered to be self-contained, i.e. it can self-assemble onto individual target molecules autonomously and form localized signal with minimal cross-talk. α-thrombin was used as a model protein to evaluate the performance of the individual modules and the overall circuit for proximity interaction under physiologically relevant buffer condition. The circuit achieved good selectivity in presence of non-specific protein and interfering serum matrix and successfully detected for physiologically relevant α-thrombin concentration (50 nM–5 μM) in a single mixing step without any further washing. The formation of localized signal at the interaction site can be enhanced kinetically through the control of temperature and probe concentration. This work provides a basic general framework from which other circuit modules can be adapted for the sensing of other biomolecular or cellular interaction of interest. PMID:25056307

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Cynthia Lee

There is a need in security systems to rapidly and accurately grant access of authorized personnel to a secure facility while denying access to unauthorized personnel. In many cases this role is filled by security personnel, which can be very costly. Systems that can perform this role autonomously without sacrificing accuracy or speed of throughput are very appealing. To address the issue of autonomous facility access through the use of technology, the idea of a ''secure portal'' is introduced. A secure portal is a defined zone where state-of-the-art technology can be implemented to grant secure area access or to allowmore » special privileges for an individual. Biometric technologies are of interest because they are generally more difficult to defeat than technologies such as badge swipe and keypad entry. The biometric technologies selected for this concept were facial and gait recognition. They were chosen since they require less user cooperation than other biometrics such as fingerprint, iris, and hand geometry and because they have the most potential for flexibility in deployment. The secure portal concept could be implemented within the boundaries of an entry area to a facility. As a person is approaching a badge and/or PIN portal, face and gait information can be gathered and processed. The biometric information could be fused for verification against the information that is gathered from the badge. This paper discusses a facial recognition technology that was developed for the purposes of providing high verification probabilities with low false alarm rates, which would be required of an autonomous entry control system. In particular, a 3-D facial recognition approach using Fisher Linear Discriminant Analysis is described. Gait recognition technology, based on Hidden Markov Models has been explored, but those results are not included in this paper. Fusion approaches for combining the results of the biometrics would be the next step in realizing the secure portal concept.« less

Sensor performance and weather effects modeling for intelligent transportation systems (ITS) applications

NASA Astrophysics Data System (ADS)

Everson, Jeffrey H.; Kopala, Edward W.; Lazofson, Laurence E.; Choe, Howard C.; Pomerleau, Dean A.

1995-01-01

Optical sensors are used for several ITS applications, including lateral control of vehicles, traffic sign recognition, car following, autonomous vehicle navigation, and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of inherent road/off- road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling are used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the U.S. Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.

Efficient Parvovirus Replication Requires CRL4Cdt2-Targeted Depletion of p21 to Prevent Its Inhibitory Interaction with PCNA

PubMed Central

Pintel, David J.

2014-01-01

Infection by the autonomous parvovirus minute virus of mice (MVM) induces a vigorous DNA damage response in host cells which it utilizes for its efficient replication. Although p53 remains activated, p21 protein levels remain low throughout the course of infection. We show here that efficient MVM replication required the targeting for degradation of p21 during this time by the CRL4Cdt2 E3-ubiquitin ligase which became re-localized to MVM replication centers. PCNA provides a molecular platform for substrate recognition by the CRL4Cdt2 E3-ubiquitin ligase and p21 targeting during MVM infection required its interaction both with Cdt2 and PCNA. PCNA is also an important co-factor for MVM replication which can be antagonized by p21 in vitro. Expression of a stable p21 mutant that retained interaction with PCNA inhibited MVM replication, while a stable p21 mutant which lacked this interaction did not. Thus, while interaction with PCNA was important for targeting p21 to the CRL4Cdt2 ligase re-localized to MVM replication centers, efficient viral replication required subsequent depletion of p21 to abrogate its inhibition of PCNA. PMID:24699724

Efficient parvovirus replication requires CRL4Cdt2-targeted depletion of p21 to prevent its inhibitory interaction with PCNA.

PubMed

Adeyemi, Richard O; Fuller, Matthew S; Pintel, David J

2014-04-01

Infection by the autonomous parvovirus minute virus of mice (MVM) induces a vigorous DNA damage response in host cells which it utilizes for its efficient replication. Although p53 remains activated, p21 protein levels remain low throughout the course of infection. We show here that efficient MVM replication required the targeting for degradation of p21 during this time by the CRL4Cdt2 E3-ubiquitin ligase which became re-localized to MVM replication centers. PCNA provides a molecular platform for substrate recognition by the CRL4Cdt2 E3-ubiquitin ligase and p21 targeting during MVM infection required its interaction both with Cdt2 and PCNA. PCNA is also an important co-factor for MVM replication which can be antagonized by p21 in vitro. Expression of a stable p21 mutant that retained interaction with PCNA inhibited MVM replication, while a stable p21 mutant which lacked this interaction did not. Thus, while interaction with PCNA was important for targeting p21 to the CRL4Cdt2 ligase re-localized to MVM replication centers, efficient viral replication required subsequent depletion of p21 to abrogate its inhibition of PCNA.

Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

PubMed

Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

2016-09-01

Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Human abdomen recognition using camera and force sensor in medical robot system for automatic ultrasound scan.

PubMed

Bin Mustafa, Ammar Safwan; Ishii, Takashi; Matsunaga, Yoshiki; Nakadate, Ryu; Ishii, Hiroyuki; Ogawa, Kouji; Saito, Akiko; Sugawara, Motoaki; Niki, Kiyomi; Takanishi, Atsuo

2013-01-01

Physicians use ultrasound scans to obtain real-time images of internal organs, because such scans are safe and inexpensive. However, people in remote areas face difficulties to be scanned due to aging society and physician's shortage. Hence, it is important to develop an autonomous robotic system to perform remote ultrasound scans. Previously, we developed a robotic system for automatic ultrasound scan focusing on human's liver. In order to make it a completely autonomous system, we present in this paper a way to autonomously localize the epigastric region as the starting position for the automatic ultrasound scan. An image processing algorithm marks the umbilicus and mammary papillae on a digital photograph of the patient's abdomen. Then, we made estimation for the location of the epigastric region using the distances between these landmarks. A supporting algorithm distinguishes rib position from epigastrium using the relationship between force and displacement. We implemented these algorithms with the automatic scanning system into an apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator. Tests on 14 healthy male subjects showed the apparatus located the epigastric region with a success rate of 94%. The results suggest that image recognition was effective in localizing a human body part.

Toll-like Receptor 2: A Novel Therapeutic Target for Ischemic White Matter Injury and Oligodendrocyte Death

PubMed Central

Choi, Jun Young

2017-01-01

Despite paramount clinical significance of white matter stroke, there is a paucity of researches on the pathomechanism of ischemic white matter damage and accompanying oligodendrocyte (OL) death. Therefore, a large gap exists between clinical needs and laboratory researches in this disease entity. Recent works have started to elucidate cellular and molecular basis of white matter injury under ischemic stress. In this paper, we briefly introduce white matter stroke from a clinical point of view and review pathophysiology of ischemic white matter injury characterized by OL death and demyelination. We present a series of evidence that Toll-like receptor 2 (TLR2), one of the membranous pattern recognition receptors, plays a cell-autonomous protective role in ischemic OL death and ensuing demyelination. Moreover, we also discuss our recent findings that its endogenous ligand, high-mobility group box 1 (HMGB1), is released from dying OLs and exerts autocrine trophic effects on OLs and myelin sheath under ischemic condition. We propose that modulation of TLR2 and its endogenous ligand HMGB1 can be a novel therapeutic target for ischemic white matter disease. PMID:28912641

Young Children's Explorations: Young Children's Research?

ERIC Educational Resources Information Center

Murray, Jane

2012-01-01

"Exploration" is recognised as research behaviour; anecdotally, as an early years' teacher, I witnessed many young children exploring. However, young children's self-initiated explorations are rarely regarded as research by adult researchers and policy-makers. The exclusion of young children's autonomous explorations from recognition as…

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

Bolts from Orion: Destroying Mobile Surface-to-Air Missile Systems with Lethal Autonomous Aircraft

DTIC Science & Technology

2016-07-01

era SAMs that had been upgraded by Ukrainian contractors . During the operation, Russian aircraft’s 10 electronic countermeasures could not...main SEAD asset is the F-16 CJ equipped with the HARM targeting system ( HTS ). The HTS can autonomously locate and identify threat radars and pass...targeting information to the HARMs before launch. The HTS can also provide targeting 13 information to global positioning system (GPS) guided

Monozygotic twins discordant for ROHHAD phenotype.

PubMed

Patwari, Pallavi P; Rand, Casey M; Berry-Kravis, Elizabeth M; Ize-Ludlow, Diego; Weese-Mayer, Debra E

2011-09-01

Rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD) falls within a group of pediatric disorders with both respiratory control and autonomic nervous system dysregulation. Children with ROHHAD typically present after 1.5 years of age with rapid weight gain as the initial sign. Subsequently, they develop alveolar hypoventilation, autonomic nervous system dysregulation, and, if untreated, cardiorespiratory arrest. To our knowledge, this is the first report of discordant presentation of ROHHAD in monozygotic twins. Twin girls, born at term, had concordant growth and development until 8 years of age. From 8 to 12 years of age, the affected twin developed features characteristic of ROHHAD including obesity, alveolar hypoventilation, scoliosis, hypothalamic dysfunction (central diabetes insipidus, hypothyroidism, premature pubarche, and growth hormone deficiency), right paraspinal/thoracic ganglioneuroblastoma, seizures, and autonomic dysregulation including altered pain perception, large and sluggishly reactive pupils, hypothermia, and profound bradycardia that required a cardiac pacemaker. Results of genetic testing for PHOX2B (congenital central hypoventilation syndrome disease-defining gene) mutations were negative. With early recognition and conservative management, the affected twin had excellent neurocognitive outcome that matched that of the unaffected twin. The unaffected twin demonstrated rapid weight gain later in age but not development of signs/symptoms consistent with ROHHAD. This discordant twin pair demonstrates key features of ROHHAD including the importance of early recognition (especially hypoventilation), complexity of signs/symptoms and clinical course, and importance of initiating comprehensive, multispecialty care. These cases confound the hypothesis of a monogenic etiology for ROHHAD and indicate alternative etiologies including autoimmune or epigenetic phenomenon or a combination of genetic predisposition and acquired precipitant.

Subject independent facial expression recognition with robust face detection using a convolutional neural network.

PubMed

Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

2003-01-01

Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

The use of multisensor data for robotic applications

NASA Technical Reports Server (NTRS)

Abidi, M. A.; Gonzalez, R. C.

1990-01-01

The feasibility of realistic autonomous space manipulation tasks using multisensory information is shown through two experiments involving a fluid interchange system and a module interchange system. In both cases, autonomous location of the mating element, autonomous location of the guiding light target, mating, and demating of the system were performed. Specifically, vision-driven techniques were implemented to determine the arbitrary two-dimensional position and orientation of the mating elements as well as the arbitrary three-dimensional position and orientation of the light targets. The robotic system was also equipped with a force/torque sensor that continuously monitored the six components of force and torque exerted on the end effector. Using vision, force, torque, proximity, and touch sensors, the two experiments were completed successfully and autonomously.

Research on application of LADAR in ground vehicle recognition

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles

NASA Technical Reports Server (NTRS)

Wolf, Michael; Kuwata, Yoshiaki; Zarzhitsky, Dimitri V.

2013-01-01

This software implements a motion-planning module for a maritime autonomous surface vehicle (ASV). The module trails a given target while also avoiding static and dynamic surface hazards. When surface hazards are other moving boats, the motion planner must apply International Regulations for Avoiding Collisions at Sea (COLREGS). A key subset of these rules has been implemented in the software. In case contact with the target is lost, the software can receive and follow a "reacquisition route," provided by a complementary system, until the target is reacquired. The programmatic intention is that the trailed target is a submarine, although any mobile naval platform could serve as the target. The algorithmic approach to combining motion with a (possibly moving) goal location, while avoiding local hazards, may be applicable to robotic rovers, automated landing systems, and autonomous airships. The software operates in JPL s CARACaS (Control Architecture for Robotic Agent Command and Sensing) software architecture and relies on other modules for environmental perception data and information on the predicted detectability of the target, as well as the low-level interface to the boat controls.

Multi-modal low cost mobile indoor surveillance system on the Robust Artificial Intelligence-based Defense Electro Robot (RAIDER)

NASA Astrophysics Data System (ADS)

Nair, Binu M.; Diskin, Yakov; Asari, Vijayan K.

2012-10-01

We present an autonomous system capable of performing security check routines. The surveillance machine, the Clearpath Husky robotic platform, is equipped with three IP cameras with different orientations for the surveillance tasks of face recognition, human activity recognition, autonomous navigation and 3D reconstruction of its environment. Combining the computer vision algorithms onto a robotic machine has given birth to the Robust Artificial Intelligencebased Defense Electro-Robot (RAIDER). The end purpose of the RAIDER is to conduct a patrolling routine on a single floor of a building several times a day. As the RAIDER travels down the corridors off-line algorithms use two of the RAIDER's side mounted cameras to perform a 3D reconstruction from monocular vision technique that updates a 3D model to the most current state of the indoor environment. Using frames from the front mounted camera, positioned at the human eye level, the system performs face recognition with real time training of unknown subjects. Human activity recognition algorithm will also be implemented in which each detected person is assigned to a set of action classes picked to classify ordinary and harmful student activities in a hallway setting.The system is designed to detect changes and irregularities within an environment as well as familiarize with regular faces and actions to distinguish potentially dangerous behavior. In this paper, we present the various algorithms and their modifications which when implemented on the RAIDER serves the purpose of indoor surveillance.

Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

PubMed

Fischell, Erin M; Schmidt, Henrik

2015-12-01

One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

Demonstration of Autonomous Rendezvous Technology (DART) Project Summary

NASA Technical Reports Server (NTRS)

Rumford, TImothy E.

2003-01-01

Since the 1960's, NASA has performed numerous rendezvous and docking missions. The common element of all US rendezvous and docking is that the spacecraft has always been piloted by astronauts. Only the Russian Space Program has developed and demonstrated an autonomous capability. The Demonstration of Autonomous Rendezvous Technology (DART) project currently funded under NASA's Space Launch Initiative (SLI) Cycle I, provides a key step in establishing an autonomous rendezvous capability for the United States. DART's objective is to demonstrate, in space, the hardware and software necessary for autonomous rendezvous. Orbital Sciences Corporation intends to integrate an Advanced Video Guidance Sensor and Autonomous Rendezvous and Proximity Operations algorithms into a Pegasus upper stage in order to demonstrate the capability to autonomously rendezvous with a target currently in orbit. The DART mission will occur in April 2004. The launch site will be Vandenburg AFB and the launch vehicle will be a Pegasus XL equipped with a Hydrazine Auxiliary Propulsion System 4th stage. All mission objectives will be completed within a 24 hour period. The paper provides a summary of mission objectives, mission overview and a discussion on the design features of the chase and target vehicles.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1991-01-01

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

Stability of distributed MPC in an intersection scenario

NASA Astrophysics Data System (ADS)

Sprodowski, T.; Pannek, J.

2015-11-01

The research topic of autonomous cars and the communication among them has attained much attention in the last years and is developing quickly. Among others, this research area spans fields such as image recognition, mathematical control theory, communication networks, and sensor fusion. We consider an intersection scenario where we divide the shared road space in different cells. These cells form a grid. The cars are modelled as an autonomous multi-agent system based on the Distributed Model Predictive Control algorithm (DMPC). We prove that the overall system reaches stability using Optimal Control for each multi-agent and demonstrate that by numerical results.

The ESP Instruction: A Study Based on the Pattern of Autonomous Inquiry

ERIC Educational Resources Information Center

Zhang, Jianfeng

2013-01-01

Autonomous inquiry learning is a kind of learning model, which relies mainly on learners and emphasizes that learners should inquire knowledge actively; moreover, ESP, which emphasizes the combination of language learning and specific purposes learning, is a goal-oriented and well targeted instruction system. Therefore, ESP and autonomous inquiry…

Neural Network-Based Landmark Recognition and Navigation with IAMRs. Understanding the Principles of Thought and Behavior.

ERIC Educational Resources Information Center

Doty, Keith L.

1999-01-01

Research on neural networks and hippocampal function demonstrating how mammals construct mental maps and develop navigation strategies is being used to create Intelligent Autonomous Mobile Robots (IAMRs). Such robots are able to recognize landmarks and navigate without "vision." (SK)

Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

DTIC Science & Technology

2006-09-28

navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

A retrospective review of safety using a nursing driven protocol for autonomic dysreflexia in patients with spinal cord injuries.

PubMed

Solinsky, Ryan; Svircev, Jelena N; James, Jennifer J; Burns, Stephen P; Bunnell, Aaron E

2016-11-01

Autonomic dysreflexia is a potentially life-threatening condition which afflicts a significant proportion of individuals with spinal cord injuries (SCI). To date, the safety and efficacy of several commonly used interventions for this condition have not been studied. A retrospective chart review of the safety of a previously implemented nursing driven inpatient autonomic dysreflexia protocol. Seventy-eight male patients with SCI who experienced autonomic dysreflexia while inpatient at our Veterans Affairs SCI unit over a 3-1/2-year period were included. The safety of a nursing driven protocol utilizing conservative measures, nitroglycerin paste, and oral hydralazine was evaluated. Occurrence of adverse events and relative hypotensive events during all episodes treated with the protocol, and efficacy of attaining target blood pressure for all episodes with protocol adherence and for initial episode experienced by each patient. Four hundred forty-five episodes of autonomic dysreflexia were recorded in the study period, with 92% adherence to the protocol. When the protocol was followed, target blood pressure was achieved for 97.6% of all episodes. Twenty-three total adverse events occurred (5.2% of all episodes). All adverse events were due to hypotension and only 0.9% required interventions beyond clinical monitoring. Of each patient's initial autonomic dysreflexia episode, 97.3% resolved using the protocol without need for further escalation of care. This inpatient nursing driven-protocol for treating autonomic dysreflexia utilizing conservative measures, nitroglycerin paste and oral hydralazine achieved target blood pressure with a high success rate and a low incidence of adverse events.

Palindromic Molecule Beacon-Based Cascade Amplification for Colorimetric Detection of Cancer Genes.

PubMed

Shen, Zhi-Fa; Li, Feng; Jiang, Yi-Fan; Chen, Chang; Xu, Huo; Li, Cong-Cong; Yang, Zhe; Wu, Zai-Sheng

2018-03-06

A highly sensitive and selective colorimetric assay based on a multifunctional molecular beacon with palindromic tail (PMB) was proposed for the detection of target p53 gene. The PMB probe can serve as recognition element, primer, and polymerization template and contains a nicking site and a C-rich region complementary to a DNAzyme. In the presence of target DNA, the hairpin of PMB is opened, and the released palindromic tails intermolecularly hybridize with each other, triggering the autonomous polymerization/nicking/displacement cycles. Although only one type of probe is involved, the system can execute triple and continuous polymerization strand displacement amplifications, generating large amounts of G-quadruplex fragments. These G-rich fragments can bind to hemin and form the DNAzymes that possess the catalytic activity similar to horseradish peroxidase, catalyzing the oxidation of ABTS by H 2 O 2 and producing the colorimetric signal. Utilizing the newly proposed sensing system, target DNA can be detected down to 10 pM with a linear response range from 10 pM to 200 nM, and mutant target DNAs are able to be distinguished even by the naked eye. The desirable detection sensitivity, high specificity, and operation convenience without any separation step and chemical modification demonstrate that the palindromic molecular beacon holds the potential for detecting and monitoring a variety of nucleic acid-related biomarkers.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Security Enhancement of Littoral Combat Ship Class Utilizing an Autonomous Mustering and Pier Monitoring System

DTIC Science & Technology

2010-03-01

allows the programmer to use the English language in an expressive manor while still maintaining the logical structure of a programming language ( Pressman ...and Choudhury Tanzeem. 2000. Face Recognition for Smart Environments, IEEE Computer, pp. 50–55. Pressman , Roger. 2010. Software Engineering A

Recent CESAR (Center for Engineering Systems Advanced Research) research activities in sensor based reasoning for autonomous machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, F.G.; de Saussure, G.; Spelt, P.F.

1988-01-01

This paper describes recent research activities at the Center for Engineering Systems Advanced Research (CESAR) in the area of sensor based reasoning, with emphasis being given to their application and implementation on our HERMIES-IIB autonomous mobile vehicle. These activities, including navigation and exploration in a-priori unknown and dynamic environments, goal recognition, vision-guided manipulation and sensor-driven machine learning, are discussed within the framework of a scenario in which an autonomous robot is asked to navigate through an unknown dynamic environment, explore, find and dock at the panel, read and understand the status of the panel's meters and dials, learn the functioningmore » of a process control panel, and successfully manipulate the control devices of the panel to solve a maintenance emergency problems. A demonstration of the successful implementation of the algorithms on our HERMIES-IIB autonomous robot for resolution of this scenario is presented. Conclusions are drawn concerning the applicability of the methodologies to more general classes of problems and implications for future work on sensor-driven reasoning for autonomous robots are discussed. 8 refs., 3 figs.« less

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

Triggered optical biosensor

DOEpatents

Song, Xuedong; Swanson, Basil I.

2001-10-02

An optical biosensor is provided for the detection of a multivalent target biomolecule, the biosensor including a substrate having a bilayer membrane thereon, a recognition molecule situated at the surface, the recognition molecule capable of binding with the multivalent target biomolecule, the recognition molecule further characterized as including a fluorescence label thereon and as being movable at the surface and a device for measuring a fluorescence change in response to binding between the recognition molecule and the multivalent target biomolecule.

In Situ Surveying of Saturn's Rings

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Cheung, C.

2004-01-01

The Saturn Autonomous Ring Array (SARA) mission concept is a new application for the Autonomous Nano-Technology Swarm (ANTS) architecture, a paradigm being developed for exploration of high surface area and/or multibody targets to minimize costs and maximize effectiveness of survey operations. Systems designed with ANTS architecture are built from potentially very large numbers of highly autonomous, yet socially interactive, specialists, in approximately ten specialist classes. Here, we analyze requirements for such a mission as well as specialized autonomous operations which would support this application.

Autonomous Rover Traverse and Precise Arm Placement on Remotely Designated Targets

NASA Technical Reports Server (NTRS)

Felder, Michael; Nesnas, Issa A.; Pivtoraiko, Mihail; Kelly, Alonzo; Volpe, Richard

2011-01-01

Exploring planetary surfaces typically involves traversing challenging and unknown terrain and acquiring in-situ measurements at designated locations using arm-mounted instruments. We present field results for a new implementation of an autonomous capability that enables a rover to traverse and precisely place an arm-mounted instrument on remote targets. Using point-and-click mouse commands, a scientist designates targets in the initial imagery acquired from the rover's mast cameras. The rover then autonomously traverse the rocky terrain for a distance of 10 - 15 m, tracks the target(s) of interest during the traverse, positions itself for approaching the target, and then precisely places an arm-mounted instrument within 2-3 cm from the originally designated target. The rover proceeds to acquire science measurements with the instrument. This work advances what has been previously developed and integrated on the Mars Exploration Rovers by using algorithms that are capable of traversing more rock-dense terrains, enabling tight thread-the-needle maneuvers. We integrated these algorithms on the newly refurbished Athena Mars research rover and fielded them in the JPL Mars Yard. We conducted 43 runs with targets at distances ranging from 5 m to 15 m and achieved a success rate of 93% for placement of the instrument within 2-3 cm.

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Memory dysfunction and autonomic neuropathy in non-insulin-dependent (type 2) diabetic patients.

PubMed

Zaslavsky, L M; Gross, J L; Chaves, M L; Machado, R

1995-11-01

Considering the nervous system as a unit, it might be expected that diabetic patients with autonomic neuropathy could have a central abnormality expressed as cognitive dysfunction. To determine whether autonomic neuropathy is independently associated with cognitive dysfunction, we studied a cross-section of 20 non-insulin-dependent diabetic patients with autonomic neuropathy (14 males and six females; age (mean) = 60 + or - 1 years); 29 non-insulin-dependent diabetic patients without autonomic neuropathy (14 males and 15 females; age = 59 + or - 1 years) and 34 non-diabetic patients (10 males and 24 females; age = 58 + or - 1 years), matched by age, education and duration of disease. Cognitive function was evaluated by tests of immediate, recent and remote memory: verbal (digit span; word span) and visual (recognition of towers and famous faces). Diabetic patients with autonomic neuropathy scored (median) lower in visual memory tests than diabetic patients without autonomic neuropathy and controls (towers immediate = 5 versus 7 and 6; towers recent = 4 versus 6 and 6; faces = 16 versus 18 and 18; respectively; Kruskal-Wallis; P < 0.05). There was no difference in verbal memory performance (Kruskal-Wallis; P > 0.05). Entering age, education, duration of disease and fasting plasma glucose in a stepwise multiple regression, the performance in these tests remained associated with autonomic neuropathy (towers immediate, P = 0.0054, partial r2 = 0.166; towers recent, P = 0.0076, partial r2 = 0.163). Scores in visual tests correlated negatively with the number of abnormal cardiovascular tests (faces, r = -0.25; towers recent, r = -0.24; Spearman; P < 0.05). Decreased visual cognitive function in non-insulin-dependent diabetic patients is associated with the presence and degree of autonomic neuropathy.

Automation study for space station subsystems and mission ground support

NASA Technical Reports Server (NTRS)

1985-01-01

An automation concept for the autonomous operation of space station subsystems, i.e., electric power, thermal control, and communications and tracking are discussed. To assure that functions essential for autonomous operations are not neglected, an operations function (systems monitoring and control) is included in the discussion. It is recommended that automated speech recognition and synthesis be considered a basic mode of man/machine interaction for space station command and control, and that the data management system (DMS) and other systems on the space station be designed to accommodate fully automated fault detection, isolation, and recovery within the system monitoring function of the DMS.

Implementing system simulation of C3 systems using autonomous objects

NASA Technical Reports Server (NTRS)

Rogers, Ralph V.

1987-01-01

The basis of all conflict recognition in simulation is a common frame of reference. Synchronous discrete-event simulation relies on the fixed points in time as the basic frame of reference. Asynchronous discrete-event simulation relies on fixed-points in the model space as the basic frame of reference. Neither approach provides sufficient support for autonomous objects. The use of a spatial template as a frame of reference is proposed to address these insufficiencies. The concept of a spatial template is defined and an implementation approach offered. Discussed are the uses of this approach to analyze the integration of sensor data associated with Command, Control, and Communication systems.

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems.

PubMed

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-08-28

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems

PubMed Central

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-01-01

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement. PMID:26343680

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Localization and recognition of traffic signs for automated vehicle control systems

NASA Astrophysics Data System (ADS)

Zadeh, Mahmoud M.; Kasvand, T.; Suen, Ching Y.

1998-01-01

We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched.

Doppler-Only Synthetic Aperture Radar

DTIC Science & Technology

2006-12-01

5 B. TARGET RECOGNITION TECHNIQUES .................................................6 1. Cooperative Targets...6 3. Techniques ............................................................................................6 C. TARGET RECOGNITION...3. Implementation of High Range Resolution Techniques .................12 F. TWO-DIMENSIONAL IMAGING

Fuzzy logic in autonomous orbital operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

Fuzzy logic can be used advantageously in autonomous orbital operations that require the capability of handling imprecise measurements from sensors. Several applications are underway to investigate fuzzy logic approaches and develop guidance and control algorithms for autonomous orbital operations. Translational as well as rotational control of a spacecraft have been demonstrated using space shuttle simulations. An approach to a camera tracking system has been developed to support proximity operations and traffic management around the Space Station Freedom. Pattern recognition and object identification algorithms currently under development will become part of this camera system at an appropriate level in the future. A concept to control environment and life support systems for large Lunar based crew quarters is also under development. Investigations in the area of reinforcement learning, utilizing neural networks, combined with a fuzzy logic controller, are planned as a joint project with the Ames Research Center.

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

NASA Technical Reports Server (NTRS)

Ambrose, Robert; Savely, Robert; Bluethmann, William; Kortenkamp, David

2003-01-01

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Modeling guidance and recognition in categorical search: bridging human and computer object detection.

PubMed

Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

2013-10-08

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

Modeling guidance and recognition in categorical search: Bridging human and computer object detection

PubMed Central

Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

2013-01-01

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery. PMID:24105460

Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; Brooks, Alexander J.-W.; Tarbell, Mark A.; Dohm, James M.

2017-05-01

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C4ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

A universal entropy-driven mechanism for thioredoxin–target recognition

PubMed Central

Palde, Prakash B.; Carroll, Kate S.

2015-01-01

Cysteine residues in cytosolic proteins are maintained in their reduced state, but can undergo oxidation owing to posttranslational modification during redox signaling or under conditions of oxidative stress. In large part, the reduction of oxidized protein cysteines is mediated by a small 12-kDa thiol oxidoreductase, thioredoxin (Trx). Trx provides reducing equivalents for central metabolic enzymes and is implicated in redox regulation of a wide number of target proteins, including transcription factors. Despite its importance in cellular redox homeostasis, the precise mechanism by which Trx recognizes target proteins, especially in the absence of any apparent signature binding sequence or motif, remains unknown. Knowledge of the forces associated with the molecular recognition that governs Trx–protein interactions is fundamental to our understanding of target specificity. To gain insight into Trx–target recognition, we have thermodynamically characterized the noncovalent interactions between Trx and target proteins before S-S reduction using isothermal titration calorimetry (ITC). Our findings indicate that Trx recognizes the oxidized form of its target proteins with exquisite selectivity, compared with their reduced counterparts. Furthermore, we show that recognition is dependent on the conformational restriction inherent to oxidized targets. Significantly, the thermodynamic signatures for multiple Trx targets reveal favorable entropic contributions as the major recognition force dictating these protein–protein interactions. Taken together, our data afford significant new insight into the molecular forces responsible for Trx–target recognition and should aid the design of new strategies for thiol oxidoreductase inhibition. PMID:26080424

Neurotoxic impact of mercury on the central nervous system evaluated by neuropsychological tests and on the autonomic nervous system evaluated by dynamic pupillometry.

PubMed

Milioni, Ana Luiza V; Nagy, Balázs V; Moura, Ana Laura A; Zachi, Elaine C; Barboni, Mirella T S; Ventura, Dora F

2017-03-01

Mercury vapor is highly toxic to the human body. The present study aimed to investigate the occurrence of neuropsychological dysfunction in former workers of fluorescent lamps factories that were exposed to mercury vapor (years after cessation of exposure), diagnosed with chronic mercurialism, and to investigate the effects of such exposure on the Autonomic Nervous System (ANS) using the non-invasive method of dynamic pupillometry. The exposed group and a control group matched by age and educational level were evaluated by the Beck Depression Inventory and with the computerized neuropsychological battery CANTABeclipse - subtests of working memory (Spatial Span), spatial memory (Spatial Recognition Memory), visual memory (Pattern Recognition Memory) and action planning (Stockings of Cambridge). The ANS was assessed by dynamic pupillometry, which provides information on the operation on both the sympathetic and parasympathetic functions. Depression scores were significantly higher among the former workers when compared with the control group. The exposed group also showed significantly worse performance in most of the cognitive functions assessed. In the dynamic pupillometry test, former workers showed significantly lower response than the control group in the sympathetic response parameter (time of 75% of pupillary recovery at 10cd/m 2 luminance). Our study found indications that are suggestive of cognitive deficits and losses in sympathetic autonomic activity among patients occupationally exposed to mercury vapor. Copyright © 2016 Elsevier B.V. All rights reserved.

Reciprocal phosphorylation and glycosylation recognition motifs control NCAPP1 interaction with pumpkin phloem proteins and their cell-to-cell movement.

PubMed

Taoka, Ken-Ichiro; Ham, Byung-Kook; Xoconostle-Cázares, Beatriz; Rojas, Maria R; Lucas, William J

2007-06-01

In plants, cell-to-cell trafficking of non-cell-autonomous proteins (NCAPs) involves protein-protein interactions, and a role for posttranslational modification has been implicated. In this study, proteins contained in pumpkin (Cucurbita maxima cv Big Max) phloem sap were used as a source of NCAPs to further explore the molecular basis for selective NCAP trafficking. Protein overlay assays and coimmunoprecipitation experiments established that phosphorylation and glycosylation, on both Nicotiana tabacum NON-CELL-AUTONOMOUS PATHWAY PROTEIN1 (Nt-NCAPP1) and the phloem NCAPs, are essential for their interaction. Detailed molecular analysis of a representative phloem NCAP, Cm-PP16-1, identified the specific residues on which glycosylation and phosphorylation must occur for effective binding to NCAPP1. Microinjection studies confirmed that posttranslational modification on these residues is essential for cell-to-cell movement of Cm-PP16-1. Lastly, a glutathione S-transferase (GST)-Cm-PP16-1 fusion protein system was employed to test whether the peptide region spanning these residues was required for cell-to-cell movement. These studies established that a 36-amino acid peptide was sufficient to impart cell-to-cell movement capacity to GST, a normally cell-autonomous protein. These findings are consistent with the hypothesis that a phosphorylation-glycosylation recognition motif functions to control the binding of a specific subset of phloem NCAPs to NCAPP1 and their subsequent transport through plasmodesmata.

Reciprocal Phosphorylation and Glycosylation Recognition Motifs Control NCAPP1 Interaction with Pumpkin Phloem Proteins and Their Cell-to-Cell Movement[W

PubMed Central

Taoka, Ken-ichiro; Ham, Byung-Kook; Xoconostle-Cázares, Beatriz; Rojas, Maria R.; Lucas, William J.

2007-01-01

In plants, cell-to-cell trafficking of non-cell-autonomous proteins (NCAPs) involves protein–protein interactions, and a role for posttranslational modification has been implicated. In this study, proteins contained in pumpkin (Cucurbita maxima cv Big Max) phloem sap were used as a source of NCAPs to further explore the molecular basis for selective NCAP trafficking. Protein overlay assays and coimmunoprecipitation experiments established that phosphorylation and glycosylation, on both Nicotiana tabacum NON-CELL-AUTONOMOUS PATHWAY PROTEIN1 (Nt-NCAPP1) and the phloem NCAPs, are essential for their interaction. Detailed molecular analysis of a representative phloem NCAP, Cm-PP16-1, identified the specific residues on which glycosylation and phosphorylation must occur for effective binding to NCAPP1. Microinjection studies confirmed that posttranslational modification on these residues is essential for cell-to-cell movement of Cm-PP16-1. Lastly, a glutathione S-transferase (GST)–Cm-PP16-1 fusion protein system was employed to test whether the peptide region spanning these residues was required for cell-to-cell movement. These studies established that a 36–amino acid peptide was sufficient to impart cell-to-cell movement capacity to GST, a normally cell-autonomous protein. These findings are consistent with the hypothesis that a phosphorylation-glycosylation recognition motif functions to control the binding of a specific subset of phloem NCAPs to NCAPP1 and their subsequent transport through plasmodesmata. PMID:17601822

Model-based recognition of 3D articulated target using ladar range data.

PubMed

Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

2015-06-10

Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate.

Anxiety and autonomic response to social-affective stimuli in individuals with Williams syndrome.

PubMed

Ng, Rowena; Bellugi, Ursula; Järvinen, Anna

2016-12-01

Williams syndrome (WS) is a genetic condition characterized by an unusual "hypersocial" personality juxtaposed by high anxiety. Recent evidence suggests that autonomic reactivity to affective face stimuli is disorganised in WS, which may contribute to emotion dysregulation and/or social disinhibition. Electrodermal activity (EDA) and mean interbeat interval (IBI) of 25 participants with WS (19 - 57 years old) and 16 typically developing (TD; 17-43 years old) adults were measured during a passive presentation of affective face and voice stimuli. The Beck Anxiety Inventory was administered to examine associations between autonomic reactivity to social-affective stimuli and anxiety symptomatology. The WS group was characterized by higher overall anxiety symptomatology, and poorer anger recognition in social visual and aural stimuli relative to the TD group. No between-group differences emerged in autonomic response patterns. Notably, for participants with WS, increased anxiety was uniquely associated with diminished arousal to angry faces and voices. In contrast, for the TD group, no associations emerged between anxiety and physiological responsivity to social-emotional stimuli. The anxiety associated with WS appears to be intimately related to reduced autonomic arousal to angry social stimuli, which may also be linked to the characteristic social disinhibition. Copyright © 2016. Published by Elsevier Ltd.

On the applicability of brain reading for predictive human-machine interfaces in robotics.

PubMed

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors.

On the Applicability of Brain Reading for Predictive Human-Machine Interfaces in Robotics

PubMed Central

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors. PMID:24358125

Ground target recognition using rectangle estimation.

PubMed

Grönwall, Christina; Gustafsson, Fredrik; Millnert, Mille

2006-11-01

We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

Target recognitions in multiple-camera closed-circuit television using color constancy

NASA Astrophysics Data System (ADS)

Soori, Umair; Yuen, Peter; Han, Ji Wen; Ibrahim, Izzati; Chen, Wentao; Hong, Kan; Merfort, Christian; James, David; Richardson, Mark

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by the proposed ELRCC algorithm. This amount of improvement represents a reduction of probability of false alarm by about a factor of 5 at the probability of detection of 0.5. Our study concerns mainly the detection of colored targets; and issues for the recognition of white or gray targets will be addressed in a forthcoming study.

An Autonomous Learning System of Bengali Characters Using Web-Based Intelligent Handwriting Recognition

ERIC Educational Resources Information Center

Khatun, Nazma; Miwa, Jouji

2016-01-01

This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…

A Gesture Recognition System to Transition Autonomously through Vocational Tasks for Individuals with Cognitive Impairments

ERIC Educational Resources Information Center

Chang, Yao-Jen; Chen, Shu-Fang; Chuang, An-Fu

2011-01-01

This study assessed the possibility of training two individuals with cognitive impairments using a Kinect-based task prompting system. This study was carried out according to an ABAB sequence in which A represented the baseline and B represented intervention phases. Data showed that the two participants significantly increased their target…

On-chip learning of hyper-spectral data for real time target recognition

NASA Technical Reports Server (NTRS)

Duong, T. A.; Daud, T.; Thakoor, A.

2000-01-01

As the focus of our present paper, we have used the cascade error projection (CEP) learning algorithm (shown to be hardware-implementable) with on-chip learning (OCL) scheme to obtain three orders of magnitude speed-up in target recognition compared to software-based learning schemes. Thus, it is shown, real time learning as well as data processing for target recognition can be achieved.

Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

PubMed Central

Chen, Long; Li, Qingquan; Li, Ming; Zhang, Liang; Mao, Qingzhou

2012-01-01

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.

New transmitters and new targets in the autonomic nervous system.

PubMed

Barajas-López, C; Huizinga, J D

1993-12-01

Several recent findings have made research into the autonomic nervous system even more exciting, such as the revelation that nitric oxide is a major neurotransmitter, the delineation of the physiological roles for purines and vasoactive intestinal peptide, and the discovery that the interstitial cells of Cajal are major target cells for enteric innervation. Nitric oxide is probably the major neurotransmitter evoking inhibitory junction potentials in smooth muscle. ATP is a mediator of non-adrenergic non-cholinergic enteric innervation, as well as being a fast neurotransmitter in peripheral and autonomic neuro-neuronal synapses. The interactions between enteric nerves and both immune cells and interstitial cells of Cajal (as pacemaker cells of gut smooth muscle) are forcing a rethink of many aspects of gut physiology.

Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

PubMed

Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

2018-05-01

Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

Fuzzy logic control system to provide autonomous collision avoidance for Mars rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1990-01-01

NASA is currently involved with planning unmanned missions to Mars to investigate the terrain and process soil samples in advance of a manned mission. A key issue involved in unmanned surface exploration on Mars is that of supporting autonomous maneuvering since radio communication involves lengthy delays. It is anticipated that specific target locations will be designated for sample gathering. In maneuvering autonomously from a starting position to a target position, the rover will need to avoid a variety of obstacles such as boulders or troughs that may block the shortest path to the target. The physical integrity of the rover needs to be maintained while minimizing the time and distance required to attain the target position. Fuzzy logic lends itself well to building reliable control systems that function in the presence of uncertainty or ambiguity. The following major issues are discussed: (1) the nature of fuzzy logic control systems and software tools to implement them; (2) collision avoidance in the presence of fuzzy parameters; and (3) techniques for adaptation in fuzzy logic control systems.

Target recognition of ladar range images using even-order Zernike moments.

PubMed

Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

2012-11-01

Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target recognition and tracking routines. Target tracking is based on simplified versions of Kalman filtration. Accuracy of recognition and tracking of implemented versions of the proposed suite of unsupervised algorithms is somewhat degraded from the ideal. Target recognition and tracking by supervised routines and by unsupervised SVM and CLNN routines in the ground-based WSN is evaluated in simulations using published system values and sensor data from vehicular targets in ground-surveillance scenarios. Results are compared with previously published performance for the system of the ground-based sensor network (GSN) and UAV swarm.

Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

NASA Astrophysics Data System (ADS)

Yao, Shoukui; Qin, Xiaojuan

2018-02-01

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

Constraints in distortion-invariant target recognition system simulation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

NASA Astrophysics Data System (ADS)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high-definition video exploitation.

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

Using eye movements as an index of implicit face recognition in autism spectrum disorder.

PubMed

Hedley, Darren; Young, Robyn; Brewer, Neil

2012-10-01

Individuals with an autism spectrum disorder (ASD) typically show impairment on face recognition tasks. Performance has usually been assessed using overt, explicit recognition tasks. Here, a complementary method involving eye tracking was used to examine implicit face recognition in participants with ASD and in an intelligence quotient-matched non-ASD control group. Differences in eye movement indices between target and foil faces were used as an indicator of implicit face recognition. Explicit face recognition was assessed using old-new discrimination and reaction time measures. Stimuli were faces of studied (target) or unfamiliar (foil) persons. Target images at test were either identical to the images presented at study or altered by changing the lighting, pose, or by masking with visual noise. Participants with ASD performed worse than controls on the explicit recognition task. Eye movement-based measures, however, indicated that implicit recognition may not be affected to the same degree as explicit recognition. Autism Res 2012, 5: 363-379. © 2012 International Society for Autism Research, Wiley Periodicals, Inc. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.

Effects of Hearing Loss on Heart-Rate Variability and Skin Conductance Measured During Sentence Recognition in Noise

PubMed Central

Mackersie, Carol L.; MacPhee, Imola X.; Heldt, Emily W.

2014-01-01

SHORT SUMMARY (précis) Sentence recognition by participants with and without hearing loss was measured in quiet and in babble noise while monitoring two autonomic nervous system measures: heart-rate variability and skin conductance. Heart-rate variability decreased under difficult listening conditions for participants with hearing loss, but not for participants with normal hearing. Skin conductance noise reactivity was greater for those with hearing loss, than for those with normal hearing, but did not vary with the signal-to-noise ratio. Subjective ratings of workload/stress obtained after each listening condition were similar for the two participant groups. PMID:25170782

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton

PubMed Central

Corgnati, Lorenzo; Marini, Simone; Mazzei, Luca; Ottaviani, Ennio; Aliani, Stefano; Conversi, Alessandra; Griffa, Annalisa

2016-01-01

Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances. PMID:27983638

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

NASA Astrophysics Data System (ADS)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

Action Recognition in a Crowded Environment

PubMed Central

Nieuwenhuis, Judith; Bülthoff, Isabelle; Barraclough, Nick; de la Rosa, Stephan

2017-01-01

So far, action recognition has been mainly examined with small point-light human stimuli presented alone within a narrow central area of the observer’s visual field. Yet, we need to recognize the actions of life-size humans viewed alone or surrounded by bystanders, whether they are seen in central or peripheral vision. Here, we examined the mechanisms in central vision and far periphery (40° eccentricity) involved in the recognition of the actions of a life-size actor (target) and their sensitivity to the presence of a crowd surrounding the target. In Experiment 1, we used an action adaptation paradigm to probe whether static or idly moving crowds might interfere with the recognition of a target’s action (hug or clap). We found that this type of crowds whose movements were dissimilar to the target action hardly affected action recognition in central and peripheral vision. In Experiment 2, we examined whether crowd actions that were more similar to the target actions affected action recognition. Indeed, the presence of that crowd diminished adaptation aftereffects in central vision as wells as in the periphery. We replicated Experiment 2 using a recognition task instead of an adaptation paradigm. With this task, we found evidence of decreased action recognition accuracy, but this was significant in peripheral vision only. Our results suggest that the presence of a crowd carrying out actions similar to that of the target affects its recognition. We outline how these results can be understood in terms of high-level crowding effects that operate on action-sensitive perceptual channels. PMID:29308177

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames. Experimental results show that the improved automatic threshold processing has special application value for the recognition of dynamic target with low contrast.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Information-based approach to performance estimation and requirements allocation in multisensor fusion for target recognition

NASA Astrophysics Data System (ADS)

Harney, Robert C.

1997-03-01

A novel methodology offering the potential for resolving two of the significant problems of implementing multisensor target recognition systems, i.e., the rational selection of a specific sensor suite and optimal allocation of requirements among sensors, is presented. Based on a sequence of conjectures (and their supporting arguments) concerning the relationship of extractable information content to recognition performance of a sensor system, a set of heuristics (essentially a reformulation of Johnson's criteria applicable to all sensor and data types) is developed. An approach to quantifying the information content of sensor data is described. Coupling this approach with the widely accepted Johnson's criteria for target recognition capabilities results in a quantitative method for comparing the target recognition ability of diverse sensors (imagers, nonimagers, active, passive, electromagnetic, acoustic, etc.). Extension to describing the performance of multiple sensors is straightforward. The application of the technique to sensor selection and requirements allocation is discussed.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Autonomous learning in gesture recognition by using lobe component analysis

NASA Astrophysics Data System (ADS)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Adaptive optics to enhance target recognition

NASA Astrophysics Data System (ADS)

McAulay, Alastair D.

2012-06-01

Target recognition can be enhanced by reducing image degradation due to atmospheric turbulence. This is accomplished by an adaptive optic system. We discuss the forms of degradation when a target is viewed through the atmosphere1: scintillation from ground targets on a hot day in visible or infrared light; beam spreading and wavering around in time; atmospheric turbulence caused by motion of the target or by weather. In the case of targets we can use a beacon laser that reflects back from the target into a wavefront detector to measure the effects of turbulence on propagation to and from the target before imaging.1 A deformable mirror then corrects the wavefront shape of the transmitted, reflected or scattered data for enhanced imaging. Further, recognition of targets is enhanced by performing accurate distance measurements to localized parts of the target using lidar. Distance is obtained by sending a short pulse to the target and measuring the time for the pulse to return. There is inadequate time to scan the complete field of view so that the beam must be steered to regions of interest such as extremities of the image during image recognition. Distance is particularly valuable to recognize fine features in range along the target or when segmentation is required to separate a target from background or from other targets. We discuss the issues involved.

Perceptual fluency and affect without recognition.

PubMed

Anand, P; Sternthal, B

1991-05-01

A dichotic listening task was used to investigate the affect-without-recognition phenomenon. Subjects performed a distractor task by responding to the information presented in one ear while ignoring the target information presented in the other ear. The subjects' recognition of and affect toward the target information as well as toward foils was measured. The results offer evidence for the affect-without-recognition phenomenon. Furthermore, the data suggest that the subjects' affect toward the stimuli depended primarily on the extent to which the stimuli were perceived as familiar (i.e., subjective familiarity), and this perception was influenced by the ear in which the distractor or the target information was presented. These data are interpreted in terms of current models of recognition memory and hemispheric lateralization.

Multi-agent autonomous system

NASA Technical Reports Server (NTRS)

Fink, Wolfgang (Inventor); Dohm, James (Inventor); Tarbell, Mark A. (Inventor)

2010-01-01

A multi-agent autonomous system for exploration of hazardous or inaccessible locations. The multi-agent autonomous system includes simple surface-based agents or craft controlled by an airborne tracking and command system. The airborne tracking and command system includes an instrument suite used to image an operational area and any craft deployed within the operational area. The image data is used to identify the craft, targets for exploration, and obstacles in the operational area. The tracking and command system determines paths for the surface-based craft using the identified targets and obstacles and commands the craft using simple movement commands to move through the operational area to the targets while avoiding the obstacles. Each craft includes its own instrument suite to collect information about the operational area that is transmitted back to the tracking and command system. The tracking and command system may be further coupled to a satellite system to provide additional image information about the operational area and provide operational and location commands to the tracking and command system.

Autonomous Mars ascent and orbit rendezvous for earth return missions

NASA Technical Reports Server (NTRS)

Edwards, H. C.; Balmanno, W. F.; Cruz, Manuel I.; Ilgen, Marc R.

1991-01-01

The details of tha assessment of autonomous Mars ascent and orbit rendezvous for earth return missions are presented. Analyses addressing navigation system assessments, trajectory planning, targeting approaches, flight control guidance strategies, and performance sensitivities are included. Tradeoffs in the analysis and design process are discussed.

Real-Time Hazard Detection and Avoidance Demonstration for a Planetary Lander

NASA Technical Reports Server (NTRS)

Epp, Chirold D.; Robertson, Edward A.; Carson, John M., III

2014-01-01

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. In addition to precision landing close to a pre-mission defined landing location, the ALHAT System must be capable of autonomously identifying and avoiding surface hazards in real-time to enable a safe landing under any lighting conditions. This paper provides an overview of the recent results of the ALHAT closed loop hazard detection and avoidance flight demonstrations on the Morpheus Vertical Testbed (VTB) at the Kennedy Space Center, including results and lessons learned. This effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

GNC architecture for autonomous robotic capture of a non-cooperative target: Preliminary concept design

NASA Astrophysics Data System (ADS)

Jankovic, Marko; Paul, Jan; Kirchner, Frank

2016-04-01

Recent studies of the space debris population in low Earth orbit (LEO) have concluded that certain regions have already reached a critical density of objects. This will eventually lead to a cascading process called the Kessler syndrome. The time may have come to seriously consider active debris removal (ADR) missions as the only viable way of preserving the space environment for future generations. Among all objects in the current environment, the SL-8 (Kosmos 3M second stages) rocket bodies (R/Bs) are some of the most suitable targets for future robotic ADR missions. However, to date, an autonomous relative navigation to and capture of an non-cooperative target has never been performed. Therefore, there is a need for more advanced, autonomous and modular systems that can cope with uncontrolled, tumbling objects. The guidance, navigation and control (GNC) system is one of the most critical ones. The main objective of this paper is to present a preliminary concept of a modular GNC architecture that should enable a safe and fuel-efficient capture of a known but uncooperative target, such as Kosmos 3M R/B. In particular, the concept was developed having in mind the most critical part of an ADR mission, i.e. close range proximity operations, and state of the art algorithms in the field of autonomous rendezvous and docking. In the end, a brief description of the hardware in the loop (HIL) testing facility is made, foreseen for the practical evaluation of the developed architecture.

Pharmacologic suppression of target cell recognition by engineered T cells expressing chimeric T-cell receptors.

PubMed

Alvarez-Vallina, L; Yañez, R; Blanco, B; Gil, M; Russell, S J

2000-04-01

Adoptive therapy with autologous T cells expressing chimeric T-cell receptors (chTCRs) is of potential interest for the treatment of malignancy. To limit possible T-cell-mediated damage to normal tissues that weakly express the targeted tumor antigen (Ag), we have tested a strategy for the suppression of target cell recognition by engineered T cells. Jurkat T cells were transduced with an anti-hapten chTCR tinder the control of a tetracycline-suppressible promoter and were shown to respond to Ag-positive (hapten-coated) but not to Ag-negative target cells. The engineered T cells were then reacted with hapten-coated target cells at different effector to target cell ratios before and after exposure to tetracycline. When the engineered T cells were treated with tetracycline, expression of the chTCR was greatly decreased and recognition of the hapten-coated target cells was completely suppressed. Tetracycline-mediated suppression of target cell recognition by engineered T cells may be a useful strategy to limit the toxicity of the approach to cancer gene therapy.

A robust recognition and accurate locating method for circular coded diagonal target

NASA Astrophysics Data System (ADS)

Bao, Yunna; Shang, Yang; Sun, Xiaoliang; Zhou, Jiexin

2017-10-01

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

Oxytocin increases bias, but not accuracy, in face recognition line-ups.

PubMed

Bate, Sarah; Bennetts, Rachel; Parris, Benjamin A; Bindemann, Markus; Udale, Robert; Bussunt, Amanda

2015-07-01

Previous work indicates that intranasal inhalation of oxytocin improves face recognition skills, raising the possibility that it may be used in security settings. However, it is unclear whether oxytocin directly acts upon the core face-processing system itself or indirectly improves face recognition via affective or social salience mechanisms. In a double-blind procedure, 60 participants received either an oxytocin or placebo nasal spray before completing the One-in-Ten task-a standardized test of unfamiliar face recognition containing target-present and target-absent line-ups. Participants in the oxytocin condition outperformed those in the placebo condition on target-present trials, yet were more likely to make false-positive errors on target-absent trials. Signal detection analyses indicated that oxytocin induced a more liberal response bias, rather than increasing accuracy per se. These findings support a social salience account of the effects of oxytocin on face recognition and indicate that oxytocin may impede face recognition in certain scenarios. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Autonomous Language Learning on Twitter: Performing Affiliation with Target Language Users through #hashtags

ERIC Educational Resources Information Center

Solmaz, Osman

2017-01-01

The purpose of this study is to examine the potential of social networking sites for autonomous language learners, specifically the role of hashtag literacies in learners' affiliation performances with native speakers. Informed by ecological approach and guided by Zappavigna's (2012) concepts of "searchable talk" and "ambient…

Wireless sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamberti, Vincent E.; Howell, JR, Layton N.; Mee, David K.

Disclosed is a sensor for detecting a target material. The sensor includes a ferromagnetic metal and a molecular recognition reagent coupled to the ferromagnetic metal. The molecular recognition reagent is operable to expand upon exposure to vapor or liquid from the target material such that the molecular recognition reagent changes a tensile stress upon the ferromagnetic metal. The target material is detected based on changes in the magnetic switching characteristics of the ferromagnetic metal caused by the changes in the tensile stress.

Component-based target recognition inspired by human vision

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2009-05-01

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

SAMURAI: Polar AUV-Based Autonomous Dexterous Sampling

NASA Astrophysics Data System (ADS)

Akin, D. L.; Roberts, B. J.; Smith, W.; Roderick, S.; Reves-Sohn, R.; Singh, H.

2006-12-01

While autonomous undersea vehicles are increasingly being used for surveying and mapping missions, as of yet there has been little concerted effort to create a system capable of performing physical sampling or other manipulation of the local environment. This type of activity has typically been performed under teleoperated control from ROVs, which provides high-bandwidth real-time human direction of the manipulation activities. Manipulation from an AUV will require a completely autonomous sampling system, which implies both advanced technologies such as machine vision and autonomous target designation, but also dexterous robot manipulators to perform the actual sampling without human intervention. As part of the NASA Astrobiology Science and Technology for Exploring the Planets (ASTEP) program, the University of Maryland Space Systems Laboratory has been adapting and extending robotics technologies developed for spacecraft assembly and maintenance to the problem of autonomous sampling of biologicals and soil samples around hydrothermal vents. The Sub-polar ice Advanced Manipulator for Universal Sampling and Autonomous Intervention (SAMURAI) system is comprised of a 6000-meter capable six-degree-of-freedom dexterous manipulator, along with an autonomous vision system, multi-level control system, and sampling end effectors and storage mechanisms to allow collection of samples from vent fields. SAMURAI will be integrated onto the Woods Hole Oceanographic Institute (WHOI) Jaguar AUV, and used in Arctic during the fall of 2007 for autonomous vent field sampling on the Gakkel Ridge. Under the current operations concept, the JAGUAR and PUMA AUVs will survey the water column and localize on hydrothermal vents. Early mapping missions will create photomosaics of the vents and local surroundings, allowing scientists on the mission to designate desirable sampling targets. Based on physical characteristics such as size, shape, and coloration, the targets will be loaded into the SAMURAI control system, and JAGUAR (with SAMURAI mounted to the lower forward hull) will return to the designated target areas. Once on site, vehicle control will be turned over to the SAMURAI controller, which will perform vision-based guidance to the sampling site and will then ground the AUV to the sea bottom for stability. The SAMURAI manipulator will collect samples, such as sessile biologicals, geological samples, and (potentially) vent fluids, and store the samples for the return trip. After several hours of sampling operations on one or several sites, JAGUAR control will be returned to the WHOI onboard controller for the return to the support ship. (Operational details of AUV operations on the Gakkel Ridge mission are presented in other papers at this conference.) Between sorties, SAMURAI end effectors can be changed out on the surface for specific targets, such as push cores or larger biologicals such as tube worms. In addition to the obvious challenges in autonomous vision-based manipulator control from a free-flying support vehicle, significant development challenges have been the design of a highly capable robotic arm within the mass limitations (both wet and dry) of the JAGUAR vehicle, the development of a highly robust manipulator with modular maintenance units for extended polar operations, and the creation of a robot-based sample collection and holding system for multiple heterogeneous samples on a single extended sortie.

[Recognition of visual objects under forward masking. Effects of cathegorial similarity of test and masking stimuli].

PubMed

Gerasimenko, N Iu; Slavutskaia, A V; Kalinin, S A; Kulikov, M A; Mikhaĭlova, E S

2013-01-01

In 38 healthy subjects accuracy and response time were examined during recognition of two categories of images--animals andnonliving objects--under forward masking. We revealed new data that masking effects depended of categorical similarity of target and masking stimuli. The recognition accuracy was the lowest and the response time was the most slow, when the target and masking stimuli belongs to the same category, that was combined with high dispersion of response times. The revealed effects were more clear in the task of animal recognition in comparison with the recognition of nonliving objects. We supposed that the revealed effects connected with interference between cortical representations of the target and masking stimuli and discussed our results in context of cortical interference and negative priming.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Engineering a robust DNA split proximity circuit with minimized circuit leakage

PubMed Central

Ang, Yan Shan; Tong, Rachel; Yung, Lin-Yue Lanry

2016-01-01

DNA circuit is a versatile and highly-programmable toolbox which can potentially be used for the autonomous sensing of dynamic events, such as biomolecular interactions. However, the experimental implementation of in silico circuit designs has been hindered by the problem of circuit leakage. Here, we systematically analyzed the sources and characteristics of various types of leakage in a split proximity circuit which was engineered to spatially probe for target sites held within close proximity. Direct evidence that 3′-truncated oligonucleotides were the major impurity contributing to circuit leakage was presented. More importantly, a unique strategy of translocating a single nucleotide between domains, termed ‘inter-domain bridging’, was introduced to eliminate toehold-independent leakages while enhancing the strand displacement kinetics across a three-way junction. We also analyzed the dynamics of intermediate complexes involved in the circuit computation in order to define the working range of domain lengths for the reporter toehold and association region respectively. The final circuit design was successfully implemented on a model streptavidin-biotin system and demonstrated to be robust against both circuit leakage and biological interferences. We anticipate that this simple signal transduction strategy can be used to probe for diverse biomolecular interactions when used in conjunction with specific target recognition moieties. PMID:27207880

The autonomic nervous system as a therapeutic target in heart failure: a scientific position statement from the Translational Research Committee of the Heart Failure Association of the European Society of Cardiology.

PubMed

van Bilsen, Marc; Patel, Hitesh C; Bauersachs, Johann; Böhm, Michael; Borggrefe, Martin; Brutsaert, Dirk; Coats, Andrew J S; de Boer, Rudolf A; de Keulenaer, Gilles W; Filippatos, Gerasimos S; Floras, John; Grassi, Guido; Jankowska, Ewa A; Kornet, Lilian; Lunde, Ida G; Maack, Christoph; Mahfoud, Felix; Pollesello, Piero; Ponikowski, Piotr; Ruschitzka, Frank; Sabbah, Hani N; Schultz, Harold D; Seferovic, Petar; Slart, Riemer H J A; Taggart, Peter; Tocchetti, Carlo G; Van Laake, Linda W; Zannad, Faiez; Heymans, Stephane; Lyon, Alexander R

2017-11-01

Despite improvements in medical therapy and device-based treatment, heart failure (HF) continues to impose enormous burdens on patients and health care systems worldwide. Alterations in autonomic nervous system (ANS) activity contribute to cardiac disease progression, and the recent development of invasive techniques and electrical stimulation devices has opened new avenues for specific targeting of the sympathetic and parasympathetic branches of the ANS. The Heart Failure Association of the European Society of Cardiology recently organized an expert workshop which brought together clinicians, trialists and basic scientists to discuss the ANS as a therapeutic target in HF. The questions addressed were: (i) What are the abnormalities of ANS in HF patients? (ii) What methods are available to measure autonomic dysfunction? (iii) What therapeutic interventions are available to target the ANS in patients with HF, and what are their specific strengths and weaknesses? (iv) What have we learned from previous ANS trials? (v) How should we proceed in the future? © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

PubMed

Sherwin, Tyrone; Easte, Mikala; Chen, Andrew Tzer-Yeu; Wang, Kevin I-Kai; Dai, Wenbin

2018-02-14

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

PubMed Central

Sherwin, Tyrone; Easte, Mikala; Wang, Kevin I-Kai; Dai, Wenbin

2018-01-01

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system. PMID:29443906

Personal glucose meters for detection and quantification of a broad range of analytes

DOEpatents

Lu, Yi; Xiang, Yu

2015-02-03

A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

PubMed

Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

2002-01-01

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can also accommodate the clear impairment of forced-choice object-location recognition memory if it incorporates the view that the most complete convergence of spatial and object information, represented in different cortical regions, occurs in the hippocampus.

A Motion-Based Feature for Event-Based Pattern Recognition

PubMed Central

Clady, Xavier; Maro, Jean-Matthieu; Barré, Sébastien; Benosman, Ryad B.

2017-01-01

This paper introduces an event-based luminance-free feature from the output of asynchronous event-based neuromorphic retinas. The feature consists in mapping the distribution of the optical flow along the contours of the moving objects in the visual scene into a matrix. Asynchronous event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously generating “spiking” events that encode relative changes in pixels' illumination at high temporal resolutions. The optical flow is computed at each event, and is integrated locally or globally in a speed and direction coordinate frame based grid, using speed-tuned temporal kernels. The latter ensures that the resulting feature equitably represents the distribution of the normal motion along the current moving edges, whatever their respective dynamics. The usefulness and the generality of the proposed feature are demonstrated in pattern recognition applications: local corner detection and global gesture recognition. PMID:28101001

Emotional dampening in persons with elevated blood pressure: affect dysregulation and risk for hypertension.

PubMed

McCubbin, James A; Loveless, James P; Graham, Jack G; Hall, Gabrielle A; Bart, Ryan M; Moore, DeWayne D; Merritt, Marcellus M; Lane, Richard D; Thayer, Julian F

2014-02-01

Persons with higher blood pressure have emotional dampening in some contexts. This may reflect interactive changes in central nervous system control of affect and autonomic function in the early stages of hypertension development. The purpose of this study is to determine the independence of cardiovascular emotional dampening from alexithymia to better understand the role of affect dysregulation in blood pressure elevations. Ninety-six normotensives were assessed for resting systolic and diastolic (DBP) blood pressure, recognition of emotions in faces and sentences using the Perception of Affect Task (PAT), alexithymia, anxiety, and defensiveness. Resting DBP significantly predicted PAT emotion recognition accuracy in men after adjustment for age, self-reported affect, and alexithymia. Cardiovascular emotional dampening is independent of alexithymia and affect in men. Dampened emotion recognition could potentially influence interpersonal communication and psychosocial distress, thereby further contributing to BP dysregulation and increased cardiovascular risk.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Distinguishing highly confident accurate and inaccurate memory: insights about relevant and irrelevant influences on memory confidence

PubMed Central

Chua, Elizabeth F.; Hannula, Deborah E.; Ranganath, Charan

2012-01-01

It is generally believed that accuracy and confidence in one’s memory are related, but there are many instances when they diverge. Accordingly, it is important to disentangle the factors which contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment, we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence. PMID:22171810

Distinguishing highly confident accurate and inaccurate memory: insights about relevant and irrelevant influences on memory confidence.

PubMed

Chua, Elizabeth F; Hannula, Deborah E; Ranganath, Charan

2012-01-01

It is generally believed that accuracy and confidence in one's memory are related, but there are many instances when they diverge. Accordingly it is important to disentangle the factors that contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Enabling Autonomous Rover Science through Dynamic Planning and Scheduling

NASA Technical Reports Server (NTRS)

Estlin, Tara A.; Gaines, Daniel; Chouinard, Caroline; Fisher, Forest; Castano, Rebecca; Judd, Michele; Nesnas, Issa

2005-01-01

This paper describes how dynamic planning and scheduling techniques can be used onboard a rover to autonomously adjust rover activities in support of science goals. These goals could be identified by scientists on the ground or could be identified by onboard data-analysis software. Several different types of dynamic decisions are described, including the handling of opportunistic science goals identified during rover traverses, preserving high priority science targets when resources, such as power, are unexpectedly over-subscribed, and dynamically adding additional, ground-specified science targets when rover actions are executed more quickly than expected. After describing our specific system approach, we discuss some of the particular challenges we have examined to support autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations.

Target Trailing With Safe Navigation With Colregs for Maritime Autonomous Surface Vehicles

NASA Technical Reports Server (NTRS)

Kuwata, Yoshiaki (Inventor); Aghazarian, Hrand (Inventor); Huntsberger, Terrance L. (Inventor); Howard, Andrew B. (Inventor); Wolf, Michael T. (Inventor); Zarzhitsky, Dimitri V. (Inventor)

2014-01-01

Systems and methods for operating autonomous waterborne vessels in a safe manner. The systems include hardware for identifying the locations and motions of other vessels, as well as the locations of stationary objects that represent navigation hazards. By applying a computational method that uses a maritime navigation algorithm for avoiding hazards and obeying COLREGS using Velocity Obstacles to the data obtained, the autonomous vessel computes a safe and effective path to be followed in order to accomplish a desired navigational end result, while operating in a manner so as to avoid hazards and to maintain compliance with standard navigational procedures defined by international agreement. The systems and methods have been successfully demonstrated on water with radar and stereo cameras as the perception sensors, and integrated with a higher level planner for trailing a maneuvering target.

Real-time edge tracking using a tactile sensor

NASA Technical Reports Server (NTRS)

Berger, Alan D.; Volpe, Richard; Khosla, Pradeep K.

1989-01-01

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented.

Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation

DTIC Science & Technology

2012-09-13

odometry, SICK laser scanning unit ( Lidar ), Inertial Measurement Unit (IMU) and ultrasonic distance measurement system (Figure 32). The Lidar , IMU...2010, July) GPS world. [Online]. http://www.gpsworld.com/tech-talk- blog/gnss-independent-navigation-solution-using-integrated- lidar -data-11378 [4...Milford, David McKinnon, Michael Warren, Gordon Wyeth, and Ben Upcroft, "Feature-based Visual Odometry and Featureless Place Recognition for SLAM in

Autonomous onboard optical processor for driving aid

NASA Astrophysics Data System (ADS)

Attia, Mondher; Servel, Alain; Guibert, Laurent

1995-01-01

We take advantage of recent technological advances in the field of ferroelectric liquid crystal silicon back plane optoelectronic devices. These are well suited to perform massively parallel processing tasks. That choice enables the design of low cost vision systems and allows the implementation of an on-board system. We focus on transport applications such as road sign recognition. Preliminary in-car experimental results are presented.

AGATE: Adversarial Game Analysis for Tactical Evaluation

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.

2013-01-01

AGATE generates a set of ranked strategies that enables an autonomous vehicle to track/trail another vehicle that is trying to break the contact using evasive tactics. The software is efficient (can be run on a laptop), scales well with environmental complexity, and is suitable for use onboard an autonomous vehicle. The software will run in near-real-time (2 Hz) on most commercial laptops. Existing software is usually run offline in a planning mode, and is not used to control an unmanned vehicle actively. JPL has developed a system for AGATE that uses adversarial game theory (AGT) methods (in particular, leader-follower and pursuit-evasion) to enable an autonomous vehicle (AV) to maintain tracking/ trailing operations on a target that is employing evasive tactics. The AV trailing, tracking, and reacquisition operations are characterized by imperfect information, and are an example of a non-zero sum game (a positive payoff for the AV is not necessarily an equal loss for the target being tracked and, potentially, additional adversarial boats). Previously, JPL successfully applied the Nash equilibrium method for onboard control of an autonomous ground vehicle (AGV) travelling over hazardous terrain.

Incremental inverse kinematics based vision servo for autonomous robotic capture of non-cooperative space debris

NASA Astrophysics Data System (ADS)

Dong, Gangqi; Zhu, Z. H.

2016-04-01

This paper proposed a new incremental inverse kinematics based vision servo approach for robotic manipulators to capture a non-cooperative target autonomously. The target's pose and motion are estimated by a vision system using integrated photogrammetry and EKF algorithm. Based on the estimated pose and motion of the target, the instantaneous desired position of the end-effector is predicted by inverse kinematics and the robotic manipulator is moved incrementally from its current configuration subject to the joint speed limits. This approach effectively eliminates the multiple solutions in the inverse kinematics and increases the robustness of the control algorithm. The proposed approach is validated by a hardware-in-the-loop simulation, where the pose and motion of the non-cooperative target is estimated by a real vision system. The simulation results demonstrate the effectiveness and robustness of the proposed estimation approach for the target and the incremental control strategy for the robotic manipulator.

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.

2011-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Examination of soldier target recognition with direct view optics

NASA Astrophysics Data System (ADS)

Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

2017-10-01

Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

Target discrimination strategies in optics detection

NASA Astrophysics Data System (ADS)

Sjöqvist, Lars; Allard, Lars; Henriksson, Markus; Jonsson, Per; Pettersson, Magnus

2013-10-01

Detection and localisation of optical assemblies used for weapon guidance or sniper rifle scopes has attracted interest for security and military applications. Typically a laser system is used to interrogate a scene of interest and the retro-reflected radiation is detected. Different system approaches for area coverage can be realised ranging from flood illumination to step-and-stare or continuous scanning schemes. Independently of the chosen approach target discrimination is a crucial issue, particularly if a complex scene such as in an urban environment and autonomous operation is considered. In this work target discrimination strategies in optics detection are discussed. Typical parameters affecting the reflected laser radiation from the target are the wavelength, polarisation properties, temporal effects and the range resolution. Knowledge about the target characteristics is important to predict the target discrimination capability. Two different systems were used to investigate polarisation properties and range resolution information from targets including e.g. road signs, optical reflexes, rifle sights and optical references. The experimental results and implications on target discrimination will be discussed. If autonomous operation is required target discrimination becomes critical in order to reduce the number of false alarms.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

PubMed

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

Orbital Express Advanced Video Guidance Sensor

NASA Technical Reports Server (NTRS)

Howard, Ricky; Heaton, Andy; Pinson, Robin; Carrington, Connie

2008-01-01

In May 2007 the first US fully autonomous rendezvous and capture was successfully performed by DARPA's Orbital Express (OE) mission. Since then, the Boeing ASTRO spacecraft and the Ball Aerospace NEXTSat have performed multiple rendezvous and docking maneuvers to demonstrate the technologies needed for satellite servicing. MSFC's Advanced Video Guidance Sensor (AVGS) is a primary near-field proximity operations sensor integrated into ASTRO's Autonomous Rendezvous and Capture Sensor System (ARCSS), which provides relative state knowledge to the ASTRO GN&C system. This paper provides an overview of the AVGS sensor flying on Orbital Express, and a summary of the ground testing and on-orbit performance of the AVGS for OE. The AVGS is a laser-based system that is capable of providing range and bearing at midrange distances and full six degree-of-freedom (6DOF) knowledge at near fields. The sensor fires lasers at two different frequencies to illuminate the Long Range Targets (LRTs) and the Short Range Targets (SRTs) on NEXTSat. Subtraction of one image from the other image removes extraneous light sources and reflections from anything other than the corner cubes on the LRTs and SRTs. This feature has played a significant role for Orbital Express in poor lighting conditions. The very bright spots that remain in the subtracted image are processed by the target recognition algorithms and the inverse-perspective algorithms, to provide 3DOF or 6DOF relative state information. Although Orbital Express has configured the ASTRO ARCSS system to only use AVGS at ranges of 120 m or less, some OE scenarios have provided opportunities for AVGS to acquire and track NEXTSat at greater distances. Orbital Express scenarios to date that have utilized AVGS include a berthing operation performed by the ASTRO robotic arm, sensor checkout maneuvers performed by the ASTRO robotic arm, 10-m unmated operations, 30-m unmated operations, and Scenario 3-1 anomaly recovery. The AVGS performed very well during the pre-unmated operations, effectively tracking beyond its 10-degree Pitch and Yaw limit-specifications, and did not require I-LOAD adjustments before unmated operations. AVGS provided excellent performance in the 10-m unmated operations, effectively tracking and maintaining lock for the duration of this scenario, and showing good agreement between the short and long range targets. During the 30-m unmated operations, the AVGS continuously tracked the SRT to 31.6 m, exceeding expectations, and continuously tracked the LRT from 8.8 m out to 31.6 m, with good agreement between these two target solutions. After this scenario was aborted at a 10-m separation during remate operations, the AVGS tracked the LRT out 54.3 m, until the relative attitude between the vehicles was too large. The vehicles remained apart for eight days, at ranges from 1 km to 6 km. During the approach to remate in this recovery operation, the AVGS began tracking the LRT at 150 m, well beyond the OE planned limits for AVGS ranges, and functioned as the primary sensor for the autonomous rendezvous and docking.

Differences in antigen presentation to MHC class I-and class II- restricted influenza virus-specific cytolytic T lymphocyte clones

PubMed Central

1986-01-01

We have examined requirements for antigen presentation to a panel of MHC class I-and class II-restricted, influenza virus-specific CTL clones by controlling the form of virus presented on the target cell surface. Both H-2K/D- and I region-restricted CTL recognize target cells exposed to infectious virus, but only the I region-restricted clones efficiently lysed histocompatible target cells pulsed with inactivated virus preparations. The isolated influenza hemagglutinin (HA) polypeptide also could sensitize target cells for recognition by class II-restricted, HA-specific CTL, but not by class I-restricted, HA- specific CTL. Inhibition of nascent viral protein synthesis abrogated the ability of target cells to present viral antigen relevant for class I-restricted CTL recognition. Significantly, presentation for class II- restricted recognition was unaffected in target cells exposed to preparations of either inactivated or infectious virus. This differential sensitivity suggested that these H-2I region-restricted CTL recognized viral polypeptides derived from the exogenously introduced virions, rather than viral polypeptides newly synthesized in the infected cell. In support of this contention, treatment of the target cells with the lysosomotropic agent chloroquine abolished recognition of infected target cells by class II-restricted CTL without diminishing class I-restricted recognition of infected target cells. Furthermore, when the influenza HA gene was introduced into target cells without exogenous HA polypeptide, the target cells that expressed the newly synthesized protein product of the HA gene were recognized only by H-2K/D-restricted CTL. These observations suggest that important differences may exist in requirements for antigen presentation between H-2K/D and H-2I region-restricted CTL. These differences may reflect the nature of the antigenic epitopes recognized by these two CTL subsets. PMID:3485173

Technology transfer: Imaging tracker to robotic controller

NASA Technical Reports Server (NTRS)

Otaguro, M. S.; Kesler, L. O.; Land, Ken; Erwin, Harry; Rhoades, Don

1988-01-01

The transformation of an imaging tracker to a robotic controller is described. A multimode tracker was developed for fire and forget missile systems. The tracker locks on to target images within an acquisition window using multiple image tracking algorithms to provide guidance commands to missile control systems. This basic tracker technology is used with the addition of a ranging algorithm based on sizing a cooperative target to perform autonomous guidance and control of a platform for an Advanced Development Project on automation and robotics. A ranging tracker is required to provide the positioning necessary for robotic control. A simple functional demonstration of the feasibility of this approach was performed and described. More realistic demonstrations are under way at NASA-JSC. In particular, this modified tracker, or robotic controller, will be used to autonomously guide the Man Maneuvering Unit (MMU) to targets such as disabled astronauts or tools as part of the EVA Retriever efforts. It will also be used to control the orbiter's Remote Manipulator Systems (RMS) in autonomous approach and positioning demonstrations. These efforts will also be discussed.

Learning target masks in infrared linescan imagery

NASA Astrophysics Data System (ADS)

Fechner, Thomas; Rockinger, Oliver; Vogler, Axel; Knappe, Peter

1997-04-01

In this paper we propose a neural network based method for the automatic detection of ground targets in airborne infrared linescan imagery. Instead of using a dedicated feature extraction stage followed by a classification procedure, we propose the following three step scheme: In the first step of the recognition process, the input image is decomposed into its pyramid representation, thus obtaining a multiresolution signal representation. At the lowest three levels of the Laplacian pyramid a neural network filter of moderate size is trained to indicate the target location. The last step consists of a fusion process of the several neural network filters to obtain the final result. To perform this fusion we use a belief network to combine the various filter outputs in a statistical meaningful way. In addition, the belief network allows the integration of further knowledge about the image domain. By applying this multiresolution recognition scheme, we obtain a nearly scale- and rotational invariant target recognition with a significantly decreased false alarm rate compared with a single resolution target recognition scheme.

An evolution based biosensor receptor DNA sequence generation algorithm.

PubMed

Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng

2010-01-01

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.

Laser radar system for obstacle avoidance

NASA Astrophysics Data System (ADS)

Bers, Karlheinz; Schulz, Karl R.; Armbruster, Walter

2005-09-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser radars which are build by the EADS company and presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from objects at distances of military relevance with a high hit-and-detect probability. The development of advanced 3d-scene analysis algorithms had increased the recognition probability and reduced the false alarm rate by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The sensor system and the implemented algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition. This paper describes different 3D-imaging ladar sensors with unique system architecture but different components matched for different military application. Emphasis is laid on an obstacle warning system with a high probability of detection of thin wires, the real time processing of the measured range image data, obstacle classification und visualization.

Developing a Telescope Simulator Towards a Global Autonomous Robotic Telescope Network

NASA Astrophysics Data System (ADS)

Giakoumidis, N.; Ioannou, Z.; Dong, H.; Mavridis, N.

2013-05-01

A robotic telescope network is a system that integrates a number of telescopes to observe a variety of astronomical targets without being operated by a human. This system autonomously selects and observes targets in accordance to an optimized target. It dynamically allocates telescope resources depending on the observation requests, specifications of the telescopes, target visibility, meteorological conditions, daylight, location restrictions and availability and many other factors. In this paper, we introduce a telescope simulator, which can control a telescope to a desired position in order to observe a specific object. The system includes a Client Module, a Server Module, and a Dynamic Scheduler module. We make use and integrate a number of open source software to simulate the movement of a robotic telescope, the telescope characteristics, the observational data and weather conditions in order to test and optimize our system.

Implementation of an Autonomous Multi-Maneuver Targeting Sequence for Lunar Trans-Earth Injection

NASA Technical Reports Server (NTRS)

Whitley, Ryan J.; Williams, Jacob

2010-01-01

Using a fully analytic initial guess estimate as a first iterate, a targeting procedure that constructs a flyable burn maneuver sequence to transfer a spacecraft from any closed Moon orbit to a desired Earth entry state is developed and implemented. The algorithm is built to support the need for an anytime abort capability for Orion. Based on project requirements, the Orion spacecraft must be able to autonomously calculate the translational maneuver targets for an entire Lunar mission. Translational maneuver target sequences for the Orion spacecraft include Lunar Orbit Insertion (LOI), Trans-Earth Injection (TEI), and Trajectory Correction Maneuvers (TCMs). This onboard capability is generally assumed to be supplemental to redundant ground computation in nominal mission operations and considered as a viable alternative primarily in loss of communications contingencies. Of these maneuvers, the ability to accurately and consistently establish a flyable 3-burn TEI target sequence is especially critical. The TEI is the sole means by which the crew can successfully return from the Moon to a narrowly banded Earth Entry Interface (EI) state. This is made even more critical by the desire for global access on the lunar surface. Currently, the designed propellant load is based on fully optimized TEI solutions for the worst case geometries associated with the accepted range of epochs and landing sites. This presents two challenges for an autonomous algorithm: in addition to being feasible, the targets must include burn sequences that do not exceed the anticipated propellant load.

The utility of multiple synthesized views in the recognition of unfamiliar faces.

PubMed

Jones, Scott P; Dwyer, Dominic M; Lewis, Michael B

2017-05-01

The ability to recognize an unfamiliar individual on the basis of prior exposure to a photograph is notoriously poor and prone to errors, but recognition accuracy is improved when multiple photographs are available. In applied situations, when only limited real images are available (e.g., from a mugshot or CCTV image), the generation of new images might provide a technological prosthesis for otherwise fallible human recognition. We report two experiments examining the effects of providing computer-generated additional views of a target face. In Experiment 1, provision of computer-generated views supported better target face recognition than exposure to the target image alone and equivalent performance to that for exposure of multiple photograph views. Experiment 2 replicated the advantage of providing generated views, but also indicated an advantage for multiple viewings of the single target photograph. These results strengthen the claim that identifying a target face can be improved by providing multiple synthesized views based on a single target image. In addition, our results suggest that the degree of advantage provided by synthesized views may be affected by the quality of synthesized material.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Autonomous Selection of a Rover Laser Target on Mars

NASA Image and Video Library

2016-07-21

NASA's Curiosity Mars rover autonomously selects some of the targets for the laser and telescopic camera of the rover's Chemistry and Camera (ChemCam) instrument. For example, on-board software analyzed the image on the left, chose the target highlighted with the yellow dot, and pointed ChemCam to acquire laser analysis and the image on the right. Most ChemCam targets are still selected by scientists discussing rocks or soil seen in images the rover has sent to Earth, but the autonomous targeting provides an added capability. It can offer a head start on acquiring composition information at a location just reached by a drive. The software for target selection and instrument pointing is called AEGIS, for Autonomous Exploration for Gathering Increased Science. The image on the left was taken by the left eye of Curiosity's stereo Navigation Camera (Navcam) a few minutes after the rover completed a drive of about 43 feet (13 meters) on July 14, 2016, during the 1,400th Martian day, or sol, of the rover's work on Mars. Using AEGIS for target selection and pointing based on the Navcam imagery, Curiosity's ChemCam zapped a grid of nine points on a rock chosen for meeting criteria set by the science team. In this run, parameters were set to find bright-toned outcrop rock rather than darker rocks, which in this area tend to be loose on the surface. Within less than 30 minutes after the Navcam image was taken, ChemCam had used its laser on all nine points and had taken before-and-after images of the target area with its remote micro-imager (RMI) camera. The image at right combines those two RMI exposures. The nine laser targets are marked in red at the center. On the Navcam image at left, the yellow dot identifies the selected target area, which is about 2.2 inches (5.6 centimeters) in diameter. An unannotated version of this Sol 1400 Navcam image is available. ChemCam records spectra of glowing plasma generated when the laser hits a target point. These spectra provide information about the chemical elements present in the target. The light-toned patch of bedrock identified by AEGIS on Sol 1400 appears, geochemically, to belong to the "Stimson" sandstone unit of lower Mount Sharp. In mid-2016, Curiosity typically uses AEGIS for selecting a ChemCam target more than once per week. http://photojournal.jpl.nasa.gov/catalog/PIA20762

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Cytokinins in Symbiotic Nodulation: When, Where, What For?

PubMed

Gamas, Pascal; Brault, Mathias; Jardinaud, Marie-Françoise; Frugier, Florian

2017-09-01

Substantial progress has been made in the understanding of early stages of the symbiotic interaction between legume plants and rhizobium bacteria. Those include the specific recognition of symbiotic partners, the initiation of bacterial infection in root hair cells, and the inception of a specific organ in the root cortex, the nodule. Increasingly complex regulatory networks have been uncovered in which cytokinin (CK) phytohormones play essential roles in different aspects of early symbiotic stages. Intriguingly, these roles can be either positive or negative, cell autonomous or non-cell autonomous, and vary, depending on time, root tissues, and possibly legume species. Recent developments on CK symbiotic functions and interconnections with other signaling pathways during nodule initiation are the focus of this review. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vision-based obstacle recognition system for automated lawn mower robot development

NASA Astrophysics Data System (ADS)

Mohd Zin, Zalhan; Ibrahim, Ratnawati

2011-06-01

Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

PubMed

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

The nonverbal expression of pride: evidence for cross-cultural recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-03-01

The present research tests whether recognition for the nonverbal expression of pride generalizes across cultures. Study 1 provided the first evidence for cross-cultural recognition of pride, demonstrating that the expression generalizes across Italy and the United States. Study 2 found that the pride expression generalizes beyond Western cultures; individuals from a preliterate, highly isolated tribe in Burkina Faso, West Africa, reliably recognized pride, regardless of whether it was displayed by African or American targets. These Burkinabe participants were unlikely to have learned the pride expression through cross-cultural transmission, so their recognition suggests that pride may be a human universal. Studies 3 and 4 used drawn figures to systematically manipulate the ethnicity and gender of targets showing the expression, and demonstrated that pride recognition generalizes across male and female targets of African, Asian, and Caucasian descent. Discussion focuses on the implications of the findings for the universality of the pride expression.

Multisensor robotic system for autonomous space maintenance and repair

NASA Technical Reports Server (NTRS)

Abidi, M. A.; Green, W. L.; Chandra, T.; Spears, J.

1988-01-01

The feasibility of realistic autonomous space manipulation tasks using multisensory information is demonstrated. The system is capable of acquiring, integrating, and interpreting multisensory data to locate, mate, and demate a Fluid Interchange System (FIS) and a Module Interchange System (MIS). In both cases, autonomous location of a guiding light target, mating, and demating of the system are performed. Implemented visio-driven techniques are used to determine the arbitrary two-dimensional position and orientation of the mating elements as well as the arbitrary three-dimensional position and orientation of the light targets. A force/torque sensor continuously monitors the six components of force and torque exerted on the end-effector. Both FIS and MIS experiments were successfully accomplished on mock-ups built for this purpose. The method is immune to variations in the ambient light, in particular because of the 90-minute day-night shift in space.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

The Design of an Autonomous Underwater Vehicle for Water Quality Monitoring

NASA Astrophysics Data System (ADS)

Li, Yulong; Liu, Rong; Liu, Shujin

2018-01-01

This paper describes the development of a civilian-used autonomous underwater vehicle (AUV) for water quality monitoring at reservoirs and watercourses that can obtain realtime visual and locational information. The mechanical design was completed with CAD software Solidworks. Four thrusters—two horizontal and two vertical—on board enable the vehicle to surge, heave, yaw, and pitch. A specialized water sample collection compartment is designed to perform water collection at target locations. The vehicle has a central controller—STM32—and a sub-coordinate controller—Arduino MEGA 2560—that coordinates multiple sensors including an inertial sensor, ultrasonic sensors, etc. Global Navigation Satellite System (GNSS) and the inertial sensor enable the vehicle’s localization. Remote operators monitor and control the vehicle via a host computer system. Operators choose either semi-autonomous mode in which they set target locations or manual mode. The experimental results show that the vehicle is able to perform well in either mode.

Identification and location of catenary insulator in complex background based on machine vision

NASA Astrophysics Data System (ADS)

Yao, Xiaotong; Pan, Yingli; Liu, Li; Cheng, Xiao

2018-04-01

It is an important premise to locate insulator precisely for fault detection. Current location algorithms for insulator under catenary checking images are not accurate, a target recognition and localization method based on binocular vision combined with SURF features is proposed. First of all, because of the location of the insulator in complex environment, using SURF features to achieve the coarse positioning of target recognition; then Using binocular vision principle to calculate the 3D coordinates of the object which has been coarsely located, realization of target object recognition and fine location; Finally, Finally, the key is to preserve the 3D coordinate of the object's center of mass, transfer to the inspection robot to control the detection position of the robot. Experimental results demonstrate that the proposed method has better recognition efficiency and accuracy, can successfully identify the target and has a define application value.

Intact suppression of increased false recognition in schizophrenia.

PubMed

Weiss, Anthony P; Dodson, Chad S; Goff, Donald C; Schacter, Daniel L; Heckers, Stephan

2002-09-01

Recognition memory is impaired in patients with schizophrenia, as they rely largely on item familiarity, rather than conscious recollection, to make mnemonic decisions. False recognition of novel items (foils) is increased in schizophrenia and may relate to this deficit in conscious recollection. By studying pictures of the target word during encoding, healthy adults can suppress false recognition. This study examined the effect of pictorial encoding on subsequent recognition of repeated foils in patients with schizophrenia. The study included 40 patients with schizophrenia and 32 healthy comparison subjects. After incidental encoding of 60 words or pictures, subjects were tested for recognition of target items intermixed with 60 new foils. These new foils were subsequently repeated following either a two- or 24-word delay. Subjects were instructed to label these repeated foils as new and not to mistake them for old target words. Schizophrenic patients showed greater overall false recognition of repeated foils. The rate of false recognition of repeated foils was lower after picture encoding than after word encoding. Despite higher levels of false recognition of repeated new items, patients and comparison subjects demonstrated a similar degree of false recognition suppression after picture, as compared to word, encoding. Patients with schizophrenia displayed greater false recognition of repeated foils than comparison subjects, suggesting both a decrement of item- (or source-) specific recollection and a consequent reliance on familiarity in schizophrenia. Despite these deficits, presenting pictorial information at encoding allowed schizophrenic subjects to suppress false recognition to a similar degree as the comparison group, implying the intact use of a high-level cognitive strategy in this population.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

Object recognition of real targets using modelled SAR images

NASA Astrophysics Data System (ADS)

Zherdev, D. A.

2017-12-01

In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

Effect of colour pop-out on the recognition of letters in crowding conditions.

PubMed

Põder, Endel

2007-11-01

The crowding effect of adjacent objects on the recognition of a target can be reduced when target and flankers differ in some feature, that is irrelevant to the recognition task. In this study, the mechanisms of this effect were explored using targets and flankers of the same and different colours. It was found that facilitation nearly equal to that of differently coloured targets and flankers can be observed with a differently coloured background blob in the location of the target. The different-colour effect does not require advance knowledge of the target and flanker colours, but the effect increases in the course of three trials with constant mapping of colours. The results are consistent with the notion of exogenous attention that facilitates the processing at the most salient locations in the visual field.

Evaluation of the national health surveillance program of workers previously exposed to asbestos in Spain (2008).

PubMed

Gómez, Montserrat García; Castañeda, Rosario; López, Vega García; Vidal, Manuel Martínez; Villanueva, Vicent; Espinosa, Mercedes Elvira

2012-01-01

Although asbestos was banned in Spain in 2001, monitoring the health of previously-exposed workers is required. In 2002 the Ministry of Health and the autonomous regions of Spain planned a health surveillance program for workers exposed to asbestos (Programa de Vigilancia de la Salud de los Trabajadores Expuestos al Amianto [PIVISTEA]) with employers' organizations, trade unions and scientific societies. The aim of this study was to evaluate the PIVISTEA to improve its effectiveness. A questionnaire with indicators for the year 2008 was sent to Spain's 17 autonomous regions, as well as to the autonomous cities of Ceuta and Melilla. The results were analyzed by evaluating the compliance of each program with the activities established by the PIVISTEA. In December 2008, a total of 22,158 workers from 14 autonomous regions and 306 companies were included in the program. The program had been started in 88% of the regions but surveillance activities remained scarce in 24%. Fifty-seven percent of the autonomous regions (69% of the total number of workers) provided the information requested. Seven autonomous regions provided data on the relationship between the diseases found and asbestos exposure. Only 5% of these diseases entitled affected individuals to receive compensation for occupational diseases. The health surveillance of workers previously exposed to asbestos in Spain, as well as medical-legal recognition of diseases caused by exposure at work, remain in adequate. Although the trend is positive, the effectiveness of many regional programs is limited, and inter-regional inequalities among affected workers have been detected. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

A digital retina-like low-level vision processor.

PubMed

Mertoguno, S; Bourbakis, N G

2003-01-01

This correspondence presents the basic design and the simulation of a low level multilayer vision processor that emulates to some degree the functional behavior of a human retina. This retina-like multilayer processor is the lower part of an autonomous self-organized vision system, called Kydon, that could be used on visually impaired people with a damaged visual cerebral cortex. The Kydon vision system, however, is not presented in this paper. The retina-like processor consists of four major layers, where each of them is an array processor based on hexagonal, autonomous processing elements that perform a certain set of low level vision tasks, such as smoothing and light adaptation, edge detection, segmentation, line recognition and region-graph generation. At each layer, the array processor is a 2D array of k/spl times/m hexagonal identical autonomous cells that simultaneously execute certain low level vision tasks. Thus, the hardware design and the simulation at the transistor level of the processing elements (PEs) of the retina-like processor and its simulated functionality with illustrative examples are provided in this paper.

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Cat-eye effect target recognition with single-pixel detectors

NASA Astrophysics Data System (ADS)

Jian, Weijian; Li, Li; Zhang, Xiaoyue

2015-12-01

A prototype of cat-eye effect target recognition with single-pixel detectors is proposed. Based on the framework of compressive sensing, it is possible to recognize cat-eye effect targets by projecting a series of known random patterns and measuring the backscattered light with three single-pixel detectors in different locations. The prototype only requires simpler, less expensive detectors and extends well beyond the visible spectrum. The simulations are accomplished to evaluate the feasibility of the proposed prototype. We compared our results to that obtained from conventional cat-eye effect target recognition methods using area array sensor. The experimental results show that this method is feasible and superior to the conventional method in dynamic and complicated backgrounds.

Increase in Speech Recognition Due to Linguistic Mismatch between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

ERIC Educational Resources Information Center

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose: To examine whether improved speech recognition during linguistically mismatched target-masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method: Monolingual English speakers (n = 20) and English-Greek simultaneous bilinguals (n = 20) listened to…

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

Individual differences in forced-choice recognition memory: partitioning contributions of recollection and familiarity.

PubMed

Migo, Ellen M; Quamme, Joel R; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A; Mayes, Andrew R; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: Each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice noncorresponding; FCNC). Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardized tests of recall, recognition, and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardized tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two-process model, where familiarity and recollection make separate contributions to recognition, is 10 times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity.

Recognition of visual stimuli and memory for spatial context in schizophrenic patients and healthy volunteers.

PubMed

Brébion, Gildas; David, Anthony S; Pilowsky, Lyn S; Jones, Hugh

2004-11-01

Verbal and visual recognition tasks were administered to 40 patients with schizophrenia and 40 healthy comparison subjects. The verbal recognition task consisted of discriminating between 16 target words and 16 new words. The visual recognition task consisted of discriminating between 16 target pictures (8 black-and-white and 8 color) and 16 new pictures (8 black-and-white and 8 color). Visual recognition was followed by a spatial context discrimination task in which subjects were required to remember the spatial location of the target pictures at encoding. Results showed that recognition deficit in patients was similar for verbal and visual material. In both schizophrenic and healthy groups, men, but not women, obtained better recognition scores for the colored than for the black-and-white pictures. However, men and women similarly benefited from color to reduce spatial context discrimination errors. Patients showed a significant deficit in remembering the spatial location of the pictures, independently of accuracy in remembering the pictures themselves. These data suggest that patients are impaired in the amount of visual information that they can encode. With regards to the perceptual attributes of the stimuli, memory for spatial information appears to be affected, but not processing of color information.

Advanced miniature processing handware for ATR applications

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Daud, Taher (Inventor); Thakoor, Anikumar (Inventor)

2003-01-01

A Hybrid Optoelectronic Neural Object Recognition System (HONORS), is disclosed, comprising two major building blocks: (1) an advanced grayscale optical correlator (OC) and (2) a massively parallel three-dimensional neural-processor. The optical correlator, with its inherent advantages in parallel processing and shift invariance, is used for target of interest (TOI) detection and segmentation. The three-dimensional neural-processor, with its robust neural learning capability, is used for target classification and identification. The hybrid optoelectronic neural object recognition system, with its powerful combination of optical processing and neural networks, enables real-time, large frame, automatic target recognition (ATR).

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

Autonomic nervous system involvement in pulmonary arterial hypertension.

PubMed

Vaillancourt, Mylène; Chia, Pamela; Sarji, Shervin; Nguyen, Jason; Hoftman, Nir; Ruffenach, Gregoire; Eghbali, Mansoureh; Mahajan, Aman; Umar, Soban

2017-12-04

Pulmonary arterial hypertension (PAH) is a chronic pulmonary vascular disease characterized by increased pulmonary vascular resistance (PVR) leading to right ventricular (RV) failure. Autonomic nervous system involvement in the pathogenesis of PAH has been demonstrated several years ago, however the extent of this involvement is not fully understood. PAH is associated with increased sympathetic nervous system (SNS) activation, decreased heart rate variability, and presence of cardiac arrhythmias. There is also evidence for increased renin-angiotensin-aldosterone system (RAAS) activation in PAH patients associated with clinical worsening. Reduction of neurohormonal activation could be an effective therapeutic strategy for PAH. Although therapies targeting adrenergic receptors or RAAS signaling pathways have been shown to reverse cardiac remodeling and improve outcomes in experimental pulmonary hypertension (PH)-models, the effectiveness and safety of such treatments in clinical settings have been uncertain. Recently, novel direct methods such as cervical ganglion block, pulmonary artery denervation (PADN), and renal denervation have been employed to attenuate SNS activation in PAH. In this review, we intend to summarize the multiple aspects of autonomic nervous system involvement in PAH and overview the different pharmacological and invasive strategies used to target autonomic nervous system for the treatment of PAH.

Additional targets of the Arabidopsis autonomous pathway members, FCA and FY.

PubMed

Marquardt, S; Boss, P K; Hadfield, J; Dean, C

2006-01-01

A central player in the Arabidopsis floral transition is the floral repressor FLC, the MADS-box transcriptional regulator that inhibits the activity of genes required to switch the meristem from vegetative to floral development. One of the many pathways that regulate FLC expression is the autonomous promotion pathway composed of FCA, FY, FLD, FPA, FVE, LD, and FLK. Rather than a hierarchical set of activities the autonomous promotion pathway comprises sub-pathways of genes with different biochemical functions that all share FLC as a target. One sub-pathway involves FCA and FY, which interact to regulate RNA processing of FLC. Several of the identified components (FY, FVE, and FLD) are homologous to yeast and mammalian proteins with rather generic roles in gene regulation. So why do mutations in these genes specifically show a late-flowering phenotype in Arabidopsis? One reason, found during the analysis of fy alleles, is that the mutant alleles identified in flowering screens can be hypomorphic, they still have partial function. A broader role for the autonomous promotion pathway is supported by a microarray analysis which has identified genes mis-regulated in fca mutants, and whose expression is also altered in fy mutants.

Method and system for providing autonomous control of a platform

NASA Technical Reports Server (NTRS)

Seelinger, Michael J. (Inventor); Yoder, John-David (Inventor)

2012-01-01

The present application provides a system for enabling instrument placement from distances on the order of five meters, for example, and increases accuracy of the instrument placement relative to visually-specified targets. The system provides precision control of a mobile base of a rover and onboard manipulators (e.g., robotic arms) relative to a visually-specified target using one or more sets of cameras. The system automatically compensates for wheel slippage and kinematic inaccuracy ensuring accurate placement (on the order of 2 mm, for example) of the instrument relative to the target. The system provides the ability for autonomous instrument placement by controlling both the base of the rover and the onboard manipulator using a single set of cameras. To extend the distance from which the placement can be completed to nearly five meters, target information may be transferred from navigation cameras (used for long-range) to front hazard cameras (used for positioning the manipulator).

Neural Dynamics Underlying Target Detection in the Human Brain

PubMed Central

Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

2014-01-01

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

Repetition priming across distinct contexts: effects of lexical status, word frequency, and retrieval test.

PubMed

Coane, Jennifer H; Balota, David A

2010-12-01

Repetition priming, the facilitation observed when a target is preceded by an identity prime, is a robust phenomenon that occurs across a variety of conditions. Oliphant (1983), however, failed to observe repetition priming for targets embedded in the instructions to an experiment in a subsequent lexical decision task. In the present experiments, we examined the roles of priming context (list or instructions), target lexicality, and target frequency in both lexical decision and episodic recognition performance. Initial encoding context did not modulate priming in lexical decision or recognition memory for low-frequency targets or nonwords, whereas context strongly modulated episodic recognition for high-frequency targets. The results indicate that priming across contexts is sensitive to the distinctiveness of the trace and the reliance on episodic retrieval mechanisms. These results also shed light on the influence of event boundaries, such that priming occurs across different events for relatively distinct (low-frequency) items.

Structural basis for microRNA targeting

DOE PAGES

Schirle, Nicole T.; Sheu-Gruttadauria, Jessica; MacRae, Ian J.

2014-10-31

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions withmore » the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.« less

Human target acquisition performance

NASA Astrophysics Data System (ADS)

Teaney, Brian P.; Du Bosq, Todd W.; Reynolds, Joseph P.; Thompson, Roger; Aghera, Sameer; Moyer, Steven K.; Flug, Eric; Espinola, Richard; Hixson, Jonathan

2012-06-01

The battlefield has shifted from armored vehicles to armed insurgents. Target acquisition (identification, recognition, and detection) range performance involving humans as targets is vital for modern warfare. The acquisition and neutralization of armed insurgents while at the same time minimizing fratricide and civilian casualties is a mounting concern. U.S. Army RDECOM CERDEC NVESD has conducted many experiments involving human targets for infrared and reflective band sensors. The target sets include human activities, hand-held objects, uniforms & armament, and other tactically relevant targets. This paper will define a set of standard task difficulty values for identification and recognition associated with human target acquisition performance.

Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

NASA Astrophysics Data System (ADS)

Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

2006-05-01

Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

Celestial Pattern Recognition Allowing Autonomous Earth-Surface or Deep-Space Positioning.

DTIC Science & Technology

1983-12-01

viii :% -7 .2 I. INTRODUCTION AND BACKGROUND Background of the Project This research project is conceptual and opportunistic. It is conceptual in that...alternative approaches and the usefulness of a device in different navigation regimes. Both the research and this report have tried to follow these...Packard, Potter, and Viglione (Ref 2; 7; 15; 17; 23) have published papers (most of these 20 years ago) suggesting that some form of star

Dealing with Common Mistakes Using an Error Corpus for EFL Students to Increase Their Autonomy in Error Recognition and Correction in Every Day Class Tasks

ERIC Educational Resources Information Center

Terreros Lazo, Oscar

2012-01-01

In this article, you will find how autonomous students of EFL in Lima, Peru can be when they recognize and correct their errors based on the teachers' guidance about what to look for and how to do it in a process that I called "Error Hunting" during regular class activities without interfering with these activities.

Active Visual SLAM with Exploration for Autonomous Underwater Navigation

DTIC Science & Technology

2012-01-01

tourism. Reconstruction of Notre Dame de Paris (Snavely et al., 2006). (c) Web-scale landmark recognition engine (Zheng et al., 2009). eters for an...structures, such as Notre Dame Cathedral in Paris and the Great Wall of China (Figure 1.3(b)), using photographs compiled from the Internet. Given the...representation. Originally developed for text-based applications, expansion of this approach to images were found in Leung and Malik (2001), Sivic and Zisserman

A nonlinear heartbeat dynamics model approach for personalized emotion recognition.

PubMed

Valenza, Gaetano; Citi, Luca; Lanatà, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2013-01-01

Emotion recognition based on autonomic nervous system signs is one of the ambitious goals of affective computing. It is well-accepted that standard signal processing techniques require relative long-time series of multivariate records to ensure reliability and robustness of recognition and classification algorithms. In this work, we present a novel methodology able to assess cardiovascular dynamics during short-time (i.e. < 10 seconds) affective stimuli, thus overcoming some of the limitations of current emotion recognition approaches. We developed a personalized, fully parametric probabilistic framework based on point-process theory where heartbeat events are modelled using a 2(nd)-order nonlinear autoregressive integrative structure in order to achieve effective performances in short-time affective assessment. Experimental results show a comprehensive emotional characterization of 4 subjects undergoing a passive affective elicitation using a sequence of standardized images gathered from the international affective picture system. Each picture was identified by the IAPS arousal and valence scores as well as by a self-reported emotional label associating a subjective positive or negative emotion. Results show a clear classification of two defined levels of arousal, valence and self-emotional state using features coming from the instantaneous spectrum and bispectrum of the considered RR intervals, reaching up to 90% recognition accuracy.

First Image from a Mars Rover Choosing a Target, False Color

NASA Image and Video Library

2010-03-23

This image is the result of the first observation of a target selected autonomously by NASA Opportunity using newly developed and uploaded software called AEGIS. The false color makes some differences between materials easier to see.

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Vision-based mapping with cooperative robots

NASA Astrophysics Data System (ADS)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

Secure VM for Monitoring Industrial Process Controllers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Dipankar; Ali, Mohammad Hassan; Abercrombie, Robert K

2011-01-01

In this paper, we examine the biological immune system as an autonomic system for self-protection, which has evolved over millions of years probably through extensive redesigning, testing, tuning and optimization process. The powerful information processing capabilities of the immune system, such as feature extraction, pattern recognition, learning, memory, and its distributive nature provide rich metaphors for its artificial counterpart. Our study focuses on building an autonomic defense system, using some immunological metaphors for information gathering, analyzing, decision making and launching threat and attack responses. In order to detection Stuxnet like malware, we propose to include a secure VM (or dedicatedmore » host) to the SCADA Network to monitor behavior and all software updates. This on-going research effort is not to mimic the nature but to explore and learn valuable lessons useful for self-adaptive cyber defense systems.« less

Bioinspired Pollen-Like Hierarchical Surface for Efficient Recognition of Target Cancer Cells.

PubMed

Wang, Wenshuo; Yang, Gao; Cui, Haijun; Meng, Jingxin; Wang, Shutao; Jiang, Lei

2017-08-01

The efficient recognition and isolation of rare cancer cells holds great promise for cancer diagnosis and prognosis. In nature, pollens exploit spiky structures to realize recognition and adhesion to stigma. Herein, a bioinspired pollen-like hierarchical surface is developed by replicating the assembly of pollen grains, and efficient and specific recognition to target cancer cells is achieved. The pollen-like surface is fabricated by combining filtering-assisted assembly and soft lithography-based replication of pollen grains of wild chrysanthemum. After modification with a capture agent specific to cancer cells, the pollen-like surface enables the capture of target cancer cells with high efficiency and specificity. In addition, the pollen-like surface not only assures high viability of captured cells but also performs well in cell mixture system and at low cell density. This study represents a good example of constructing cell recognition biointerfaces inspired by pollen-stigma adhesion. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Eyes on crowding: crowding is preserved when responding by eye and similarly affects identity and position accuracy.

PubMed

Yildirim, Funda; Meyer, Vincent; Cornelissen, Frans W

2015-02-16

Peripheral vision guides recognition and selection of targets for eye movements. Crowding—a decline in recognition performance that occurs when a potential target is surrounded by other, similar, objects—influences peripheral object recognition. A recent model study suggests that crowding may be due to increased uncertainty about both the identity and the location of peripheral target objects, but very few studies have assessed these properties in tandem. Eye tracking can integrally provide information on both the perceived identity and the position of a target and therefore could become an important approach in crowding studies. However, recent reports suggest that around the moment of saccade preparation crowding may be significantly modified. If these effects were to generalize to regular crowding tasks, it would complicate the interpretation of results obtained with eye tracking and the comparison to results obtained using manual responses. For this reason, we first assessed whether the manner by which participants responded—manually or by eye—affected their performance. We found that neither recognition performance nor response time was affected by the response type. Hence, we conclude that crowding magnitude was preserved when observers responded by eye. In our main experiment, observers made eye movements to the location of a tilted Gabor target while we varied flanker tilt to manipulate target-flanker similarity. The results indicate that this similarly affected the accuracy of peripheral recognition and saccadic target localization. Our results inform about the importance of both location and identity uncertainty in crowding. © 2015 ARVO.

A hierarchical, automated target recognition algorithm for a parallel analog processor

NASA Technical Reports Server (NTRS)

Woodward, Gail; Padgett, Curtis

1997-01-01

A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1x4096 every 250 nanoseconds.

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute

PubMed Central

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-01-01

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson–Crick base-pairing even in the 3′-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5′ base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region. PMID:27325485

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute.

PubMed

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-06-21

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson-Crick base-pairing even in the 3'-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5' base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Autonomous search and surveillance with small fixed wing aircraft

NASA Astrophysics Data System (ADS)

McGee, Timothy Garland

Small unmanned aerial vehicles (UAVs) have the potential to act as low cost tools in a variety of both civilian and military applications including traffic monitoring, border patrol, and search and rescue. While most current operational UAV systems require human operators, advances in autonomy will allow these systems to reach their full potential as sensor platforms. This dissertation specifically focuses on developing advanced control, path planning, search, and image processing techniques that allow small fixed wing aircraft to autonomously collect data. The problems explored were motivated by experience with the development and experimental flight testing of a fleet of small autonomous fixed wing aircraft. These issues, which have not been fully addressed in past work done on ground vehicles or autonomous helicopters, include the influence of wind and turning rate constraints, the non-negligible velocity of ground targets relative to the aircraft velocity, and limitations on sensor size and processing power on small vehicles. Several contributions for the autonomous operation of small fixed wing aircraft are presented. Several sliding surface controllers are designed which extend previous techniques to include variable sliding surface coefficients and the use of spatial vehicle dynamics. These advances eliminate potential singularities in the control laws to follow spatially defined paths and allow smooth transition between controllers. The optimal solution for the problem of path planning through an ordered set of points for an aircraft with a bounded turning rate in the presence of a constant wind is then discussed. Path planning strategies are also explored to guarantee that a searcher will travel within sensing distance of a mobile ground target. This work assumes only a maximum velocity of the target and is designed to succeed for any possible path of the target. Closed-loop approximations of both the path planning and search techniques, using the sliding surface controllers already discussed, are also studied. Finally, a novel method is presented to detect obstacles by segmenting an image into sky and non-sky regions. The feasibility of this method is demonstrated experimentally on an aircraft test bed.

Advancing Autonomous Operations for Deep Space Vehicles

NASA Technical Reports Server (NTRS)

Haddock, Angie T.; Stetson, Howard K.

2014-01-01

Starting in Jan 2012, the Advanced Exploration Systems (AES) Autonomous Mission Operations (AMO) Project began to investigate the ability to create and execute "single button" crew initiated autonomous activities [1]. NASA Marshall Space Flight Center (MSFC) designed and built a fluid transfer hardware test-bed to use as a sub-system target for the investigations of intelligent procedures that would command and control a fluid transfer test-bed, would perform self-monitoring during fluid transfers, detect anomalies and faults, isolate the fault and recover the procedures function that was being executed, all without operator intervention. In addition to the development of intelligent procedures, the team is also exploring various methods for autonomous activity execution where a planned timeline of activities are executed autonomously and also the initial analysis of crew procedure development. This paper will detail the development of intelligent procedures for the NASA MSFC Autonomous Fluid Transfer System (AFTS) as well as the autonomous plan execution capabilities being investigated. Manned deep space missions, with extreme communication delays with Earth based assets, presents significant challenges for what the on-board procedure content will encompass as well as the planned execution of the procedures.

Precision Control and Maneuvering of the Phoenix Autonomous Underwater Vehicle for Entering a Recovery Tube

DTIC Science & Technology

1996-09-01

T1wo such modes have buen iinrylvni teted: a full target-track mode0 and a target- edge-track mode. Whun using thc full target-track mode the sonai ...direction is reversed. Rather than tracking across the target all the way to the opposing edge, however, the sonai is scanned only until three returns

Multi-AUV Target Search Based on Bioinspired Neurodynamics Model in 3-D Underwater Environments.

PubMed

Cao, Xiang; Zhu, Daqi; Yang, Simon X

2016-11-01

Target search in 3-D underwater environments is a challenge in multiple autonomous underwater vehicles (multi-AUVs) exploration. This paper focuses on an effective strategy for multi-AUV target search in the 3-D underwater environments with obstacles. First, the Dempster-Shafer theory of evidence is applied to extract information of environment from the sonar data to build a grid map of the underwater environments. Second, a topologically organized bioinspired neurodynamics model based on the grid map is constructed to represent the dynamic environment. The target globally attracts the AUVs through the dynamic neural activity landscape of the model, while the obstacles locally push the AUVs away to avoid collision. Finally, the AUVs plan their search path to the targets autonomously by a steepest gradient descent rule. The proposed algorithm deals with various situations, such as static targets search, dynamic targets search, and one or several AUVs break down in the 3-D underwater environments with obstacles. The simulation results show that the proposed algorithm is capable of guiding multi-AUV to achieve search task of multiple targets with higher efficiency and adaptability compared with other algorithms.

Glucose enhancement of a facial recognition task in young adults.

PubMed

Metzger, M M

2000-02-01

Numerous studies have reported that glucose administration enhances memory processes in both elderly and young adult subjects. Although these studies have utilized a variety of procedures and paradigms, investigations of both young and elderly subjects have typically used verbal tasks (word list recall, paragraph recall, etc.). In the present study, the effect of glucose consumption on a nonverbal, facial recognition task in young adults was examined. Lemonade sweetened with either glucose (50 g) or saccharin (23.7 mg) was consumed by college students (mean age of 21.1 years) 15 min prior to a facial recognition task. The task consisted of a familiarization phase in which subjects were presented with "target" faces, followed immediately by a recognition phase in which subjects had to identify the targets among a random array of familiar target and novel "distractor" faces. Statistical analysis indicated that there were no differences on hit rate (target identification) for subjects who consumed either saccharin or glucose prior to the test. However, further analyses revealed that subjects who consumed glucose committed significantly fewer false alarms and had (marginally) higher d-prime scores (a signal detection measure) compared to subjects who consumed saccharin prior to the test. These results parallel a previous report demonstrating glucose enhancement of a facial recognition task in probable Alzheimer's patients; however, this is believed to be the first demonstration of glucose enhancement for a facial recognition task in healthy, young adults.

A fusion approach for coarse-to-fine target recognition

NASA Astrophysics Data System (ADS)

Folkesson, Martin; Grönwall, Christina; Jungert, Erland

2006-04-01

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Multidisciplinary unmanned technology teammate (MUTT)

NASA Astrophysics Data System (ADS)

Uzunovic, Nenad; Schneider, Anne; Lacaze, Alberto; Murphy, Karl; Del Giorno, Mark

2013-01-01

The U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) held an autonomous robot competition called CANINE in June 2012. The goal of the competition was to develop innovative and natural control methods for robots. This paper describes the winning technology, including the vision system, the operator interaction, and the autonomous mobility. The rules stated only gestures or voice commands could be used for control. The robots would learn a new object at the start of each phase, find the object after it was thrown into a field, and return the object to the operator. Each of the six phases became more difficult, including clutter of the same color or shape as the object, moving and stationary obstacles, and finding the operator who moved from the starting location to a new location. The Robotic Research Team integrated techniques in computer vision, speech recognition, object manipulation, and autonomous navigation. A multi-filter computer vision solution reliably detected the objects while rejecting objects of similar color or shape, even while the robot was in motion. A speech-based interface with short commands provided close to natural communication of complicated commands from the operator to the robot. An innovative gripper design allowed for efficient object pickup. A robust autonomous mobility and navigation solution for ground robotic platforms provided fast and reliable obstacle avoidance and course navigation. The research approach focused on winning the competition while remaining cognizant and relevant to real world applications.

A translational in vivo model of trigeminal autonomic cephalalgias: therapeutic characterization.

PubMed

Akerman, Simon; Holland, Philip R; Summ, Oliver; Lasalandra, Michele P; Goadsby, Peter J

2012-12-01

Trigeminal autonomic cephalalgias are highly disabling primary headache disorders, characterized by severe unilateral head pain and associated ipsilateral cranial autonomic features. There is limited understanding of their pathophysiology and how and where treatments act to reduce symptoms; this is significantly hindered by a lack of animal models. We have developed the first animal model to explore trigeminal autonomic cephalalgias, using stimulation within the brainstem, at the level of the superior salivatory nucleus, to activate the trigeminal autonomic reflex arc. Using electrophysiological recording of neurons of the trigeminocervical complex and laser Doppler blood flow changes around the ipsilateral lacrimal duct, superior salivatory nucleus stimulation exhibited both neuronal trigeminovascular and cranial autonomic manifestations. These responses were specifically inhibited by the autonomic ganglion blocker hexamethonium bromide. These data demonstrate that brainstem activation may be the driver of both sensory and autonomic symptoms in these disorders, and part of this activation may be via the parasympathetic outflow to the cranial vasculature. Additionally, both sensory and autonomic manifestations were significantly inhibited by highly effective treatments for trigeminal autonomic cephalalgias, such as oxygen, indomethacin and triptans, and some part of their therapeutic action appears to be specifically on the parasympathetic outflow to the cranial vasculature. Treatments more used to migraine, such as naproxen and a calcitonin gene-related peptide receptor inhibitor, olcegepant, were less effective in this model. This is the first model to represent the phenotype of trigeminal autonomic cephalalgias and their response to therapies, and indicates the parasympathetic pathway may be uniquely involved in their pathophysiology and targeted to relieve symptoms.

Individual differences in forced-choice recognition memory: Partitioning contributions of recollection and familiarity

PubMed Central

Migo, Ellen M.; Quamme, Joel R.; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A.; Mayes, Andrew R.; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice non-corresponding; FCNC).Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardised tests of recall, recognition and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardised tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two process model, where familiarity and recollection make separate contributions to recognition, is ten times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity. PMID:24796268

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

PubMed

O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

2015-09-01

Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

Stress, autonomic imbalance, and the prediction of metabolic risk: A model and a proposal for research.

PubMed

Wulsin, Lawson; Herman, James; Thayer, Julian F

2018-03-01

Devising novel prevention strategies for metabolic disorders will depend in part on the careful elucidation of the common pathways for developing metabolic risks. The neurovisceral integration model has proposed that autonomic imbalance plays an important role in the pathway from acute and chronic stress to cardiovascular disease. Though generally overlooked by clinicians, autonomic imbalance (sympathetic overactivity and/or parasympathetic underactivity) can be measured and modified by methods that are available in primary care. This review applies the neurovisceral integration concept to the clinical setting by proposing that autonomic imbalance plays a primary role in the development of metabolic risks. We present a testable model, a systematic review of the evidence in support of autonomic imbalance as a predictor for metabolic risks, and specific approaches to test this model as a guide to future research on the role of stress in metabolic disorders. We propose that autonomic imbalance deserves consideration by researchers, clinicians, and policymakers as a target for early interventions to prevent metabolic disorders. Published by Elsevier Ltd.

Target-context unitization effect on the familiarity-related FN400: a face recognition exclusion task.

PubMed

Guillaume, Fabrice; Etienne, Yann

2015-03-01

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Pattern-Recognition System for Approaching a Known Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2008-01-01

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Near-Nash targeting strategies for heterogeneous teams of autonomous combat vehicles

NASA Astrophysics Data System (ADS)

Galati, David G.; Simaan, Marwan A.

2008-04-01

Military strategists are currently seeking methodologies to control large numbers of autonomous assets. Automated planners based upon the Nash equilibrium concept in non-zero sum games are one option. Because such planners inherently consider possible adversarial actions, assets are able to adapt to, and to some extent predict, potential enemy actions. However, these planners must function properly both in cases in which a pure Nash strategy does not exist and in scenarios possessing multiple Nash equilibria. Another issue that needs to be overcome is the scalability of the Nash equilibrium. That is, as the dimensionality of the problem increases, the Nash strategies become unfeasible to compute using traditional methodologies. In this paper we introduce the concept of near-Nash strategies as a mechanism to overcome these difficulties. We then illustrate this concept by deriving the near-Nash strategies and using these strategies as the basis for an intelligent battle plan for heterogeneous teams of autonomous combat air vehicles in the Multi-Team Dynamic Weapon Target Assignment model.

Evaluation of a Home Biomonitoring Autonomous Mobile Robot.

PubMed

Dorronzoro Zubiete, Enrique; Nakahata, Keigo; Imamoglu, Nevrez; Sekine, Masashi; Sun, Guanghao; Gomez, Isabel; Yu, Wenwei

2016-01-01

Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed. However, the system has not been tested in any home living scenarios. In this study we did a series of experiments to investigate the accuracy of activity recognition of the mobile robot in a home living scenario. The daily activities tested in the evaluation experiment include watching TV and sleeping. A dataset recorded by a distributed distance-measuring sensor network was used as a reference to the activity recognition results. It was shown that the accuracy is not consistent for all the activities; that is, mobile robot could achieve a high success rate in some activities but a poor success rate in others. It was found that the observation position of the mobile robot and subject surroundings have high impact on the accuracy of the activity recognition, due to the variability of the home living daily activities and their transitional process. The possibility of improvement of recognition accuracy has been shown too.

Recognition memory strength is predicted by pupillary responses at encoding while fixation patterns distinguish recollection from familiarity.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2011-10-01

Thirty-five healthy participants incidentally encoded a set of man-made and natural object pictures, while their pupil response and eye movements were recorded. At retrieval, studied and new stimuli were rated as novel, familiar (strong, moderate, or weak), or recollected. We found that both pupil response and fixation patterns at encoding predict later recognition memory strength. The extent of pupillary response accompanying incidental encoding was found to be predictive of subsequent memory. In addition, the number of fixations was also predictive of later recognition memory strength, suggesting that the accumulation of greater visual detail, even for single objects, is critical for the creation of a strong memory. Moreover, fixation patterns at encoding distinguished between recollection and familiarity at retrieval, with more dispersed fixations predicting familiarity and more clustered fixations predicting recollection. These data reveal close links between the autonomic control of pupil responses and eye movement patterns on the one hand and memory encoding on the other. Moreover, the data illustrate quantitative as well as qualitative differences in the incidental visual processing of stimuli, which are differentially predictive of the strength and the kind of memory experienced at recognition.

Lexical Competition in Non-Native Spoken-Word Recognition

ERIC Educational Resources Information Center

Weber, Andrea; Cutler, Anne

2004-01-01

Four eye-tracking experiments examined lexical competition in non-native spoken-word recognition. Dutch listeners hearing English fixated longer on distractor pictures with names containing vowels that Dutch listeners are likely to confuse with vowels in a target picture name ("pencil," given target "panda") than on less confusable distractors…

An Evaluation and Comparison of Several Measures of Image Quality for Television Displays

DTIC Science & Technology

1979-01-01

vehicles, buildings, or faces , or they may be artificial much as trn-bar patterns, rectangles, or sine waves. The typical objective image quality assessment...Snyder (1974b) wac able to obtain very good correlations with reaction time and correct responses for a face recognition task. Display quality was varied...recognition versus log JUDA for the target recognition study of Chapter 4, 5) graph of angle oubtended by target at recognitio , versus log JNDA for the

Parietal lobe critically supports successful paired immediate and single-item delayed memory for targets.

PubMed

Krumm, Sabine; Kivisaari, Sasa L; Monsch, Andreas U; Reinhardt, Julia; Ulmer, Stephan; Stippich, Christoph; Kressig, Reto W; Taylor, Kirsten I

2017-05-01

The parietal lobe is important for successful recognition memory, but its role is not yet fully understood. We investigated the parietal lobes' contribution to immediate paired-associate memory and delayed item-recognition memory separately for hits (targets) and correct rejections (distractors). We compared the behavioral performance of 56 patients with known parietal and medial temporal lobe dysfunction (i.e. early Alzheimer's Disease) to 56 healthy control participants in an immediate paired and delayed single item object memory task. Additionally, we performed voxel-based morphometry analyses to investigate the functional-neuroanatomic relationships between performance and voxel-based estimates of atrophy in whole-brain analyses. Behaviorally, all participants performed better identifying targets than rejecting distractors. The voxel-based morphometry analyses associated atrophy in the right ventral parietal cortex with fewer correct responses to familiar items (i.e. hits) in the immediate and delayed conditions. Additionally, medial temporal lobe integrity correlated with better performance in rejecting distractors, but not in identifying targets, in the immediate paired-associate task. Our findings suggest that the parietal lobe critically supports successful immediate and delayed target recognition memory, and that the ventral aspect of the parietal cortex and the medial temporal lobe may have complementary preferences for identifying targets and rejecting distractors, respectively, during recognition memory. Copyright © 2017. Published by Elsevier Inc.

ROHHAD syndrome and evolution of sleep disordered breathing.

PubMed

Reppucci, Diana; Hamilton, Jill; Yeh, E Ann; Katz, Sherri; Al-Saleh, Suhail; Narang, Indra

2016-07-30

Rapid-onset obesity with hypothalamic dysfunction, hypoventilation and autonomic dysregulation (ROHHAD) is a rare disease with a high mortality rate. Although nocturnal hypoventilation (NH) is central to ROHHAD, the evolution of sleep disordered breathing (SDB) is not well studied. The aim of the study was to assess early manifestations of SDB and their evolution in ROHHAD syndrome. Retrospective study of children with ROHHAD at two Canadian centers. All children with suspected ROHHAD at presentation underwent polysomnography (PSG) to screen for nocturnal hypoventilation. PSG findings at baseline and follow-up were collected. Interventions and diagnostic test results were recorded. Six children were included. The median age of rapid onset obesity and nocturnal hypoventilation (NH) was 3.5 and 7.2 years respectively. On initial screening for ROHHAD 4/6 (66.7 %) children had obstructive sleep apnea (OSA), 1/6 (16.7 %) had NH and 1/6 (16.7 %) had both OSA and NH. Follow up PSGs were performed in 5/6 children as one child died following a cardiorespiratory arrest. All children at follow up had NH and required non-invasive positive pressure ventilation. Additionally, 3/6 (50 %) children demonstrated irregular breathing patterns during wakefulness. Children with ROHHAD may initially present with OSA and only develop NH later as well as dysregulation of breathing during wakefulness. The recognition of the spectrum of respiratory abnormalities at presentation and over time may be important in raising the index of suspicion of ROHHAD. Early recognition and targeted therapeutic interventions may limit morbidity and mortality associated with ROHHAD.

How do robots take two parts apart

NASA Technical Reports Server (NTRS)

Bajcsy, Ruzena K.; Tsikos, Constantine J.

1989-01-01

This research is a natural progression of efforts which begun with the introduction of a new research paradigm in machine perception, called Active Perception. There it was stated that Active Perception is a problem of intelligent control strategies applied to data acquisition processes which will depend on the current state of the data interpretation, including recognition. The disassembly/assembly problem is treated as an Active Perception problem, and a method for autonomous disassembly based on this framework is presented.

Realism and Effectiveness of Robotic Moving Targets

DTIC Science & Technology

2017-04-01

scenario or be manually controlled . The targets can communicate with other nearby targets, which means they can move independently, as a group , or...present a realistic three- dimensional human-sized target that can freely move with semi-autonomous control . The U.S. Army Research Institute for...Procedure: Performance and survey data were collected during multiple training exercises from Soldiers who engaged the RHTTs. Different groups

Unification of automatic target tracking and automatic target recognition

NASA Astrophysics Data System (ADS)

Schachter, Bruce J.

2014-06-01

The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

The role of semantically related distractors during encoding and retrieval of words in long-term memory.

PubMed

Meade, Melissa E; Fernandes, Myra A

2016-07-01

We examined the influence of divided attention (DA) on recognition of words when the concurrent task was semantically related or unrelated to the to-be-recognised target words. Participants were asked to either study or retrieve a target list of semantically related words while simultaneously making semantic decisions (i.e., size judgements) to another set of related or unrelated words heard concurrently. We manipulated semantic relatedness of distractor to target words, and whether DA occurred during the encoding or retrieval phase of memory. Recognition accuracy was significantly diminished relative to full attention, following DA conditions at encoding, regardless of relatedness of distractors to study words. However, response times (RTs) were slower with related compared to unrelated distractors. Similarly, under DA at retrieval, recognition RTs were slower when distractors were semantically related than unrelated to target words. Unlike the effect from DA at encoding, recognition accuracy was worse under DA at retrieval when the distractors were related compared to unrelated to the target words. Results suggest that availability of general attentional resources is critical for successful encoding, whereas successful retrieval is particularly reliant on access to a semantic code, making it sensitive to related distractors under DA conditions.

An Autonomous Sensor System Architecture for Active Flow and Noise Control Feedback

NASA Technical Reports Server (NTRS)

Humphreys, William M, Jr.; Culliton, William G.

2008-01-01

Multi-channel sensor fusion represents a powerful technique to simply and efficiently extract information from complex phenomena. While the technique has traditionally been used for military target tracking and situational awareness, a study has been successfully completed that demonstrates that sensor fusion can be applied equally well to aerodynamic applications. A prototype autonomous hardware processor was successfully designed and used to detect in real-time the two-dimensional flow reattachment location generated by a simple separated-flow wind tunnel model. The success of this demonstration illustrates the feasibility of using autonomous sensor processing architectures to enhance flow control feedback signal generation.

Vagus nerve stimulation: state of the art of stimulation and recording strategies to address autonomic function neuromodulation

NASA Astrophysics Data System (ADS)

Guiraud, David; Andreu, David; Bonnet, Stéphane; Carrault, Guy; Couderc, Pascal; Hagège, Albert; Henry, Christine; Hernandez, Alfredo; Karam, Nicole; Le Rolle, Virginie; Mabo, Philippe; Maciejasz, Paweł; Malbert, Charles-Henri; Marijon, Eloi; Maubert, Sandrine; Picq, Chloé; Rossel, Olivier; Bonnet, Jean-Luc

2016-08-01

Objective. Neural signals along the vagus nerve (VN) drive many somatic and autonomic functions. The clinical interest of VN stimulation (VNS) is thus potentially huge and has already been demonstrated in epilepsy. However, side effects are often elicited, in addition to the targeted neuromodulation. Approach. This review examines the state of the art of VNS applied to two emerging modulations of autonomic function: heart failure and obesity, especially morbid obesity. Main results. We report that VNS may benefit from improved stimulation delivery using very advanced technologies. However, most of the results from fundamental animal studies still need to be demonstrated in humans.

The research of multi-frame target recognition based on laser active imaging

NASA Astrophysics Data System (ADS)

Wang, Can-jin; Sun, Tao; Wang, Tin-feng; Chen, Juan

2013-09-01

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

The Last Meter: Blind Visual Guidance to a Target.

PubMed

Manduchi, Roberto; Coughlan, James M

2014-01-01

Smartphone apps can use object recognition software to provide information to blind or low vision users about objects in the visual environment. A crucial challenge for these users is aiming the camera properly to take a well-framed picture of the desired target object. We investigate the effects of two fundamental constraints of object recognition - frame rate and camera field of view - on a blind person's ability to use an object recognition smartphone app. The app was used by 18 blind participants to find visual targets beyond arm's reach and approach them to within 30 cm. While we expected that a faster frame rate or wider camera field of view should always improve search performance, our experimental results show that in many cases increasing the field of view does not help, and may even hurt, performance. These results have important implications for the design of object recognition systems for blind users.

Autonomous In-Situ Resources Prospector

NASA Technical Reports Server (NTRS)

Dissly, R. W.; Buehler, M. G.; Schaap, M. G.; Nicks, D.; Taylor, G. J.; Castano, R.; Suarez, D.

2004-01-01

This presentation will describe the concept of an autonomous, intelligent, rover-based rapid surveying system to identify and map several key lunar resources to optimize their ISRU (In Situ Resource Utilization) extraction potential. Prior to an extraction phase for any target resource, ground-based surveys are needed to provide confirmation of remote observation, to quantify and map their 3-D distribution, and to locate optimal extraction sites (e.g. ore bodies) with precision to maximize their economic benefit. The system will search for and quantify optimal minerals for oxygen production feedstock, water ice, and high glass-content regolith that can be used for building materials. These are targeted because of their utility and because they are, or are likely to be, variable in quantity over spatial scales accessible to a rover (i.e., few km). Oxygen has benefits for life support systems and as an oxidizer for propellants. Water is a key resource for sustainable exploration, with utility for life support, propellants, and other industrial processes. High glass-content regolith has utility as a feedstock for building materials as it readily sinters upon heating into a cohesive matrix more readily than other regolith materials or crystalline basalts. Lunar glasses are also a potential feedstock for oxygen production, as many are rich in iron and titanium oxides that are optimal for oxygen extraction. To accomplish this task, a system of sensors and decision-making algorithms for an autonomous prospecting rover is described. One set of sensors will be located in the wheel tread of the robotic search vehicle providing contact sensor data on regolith composition. Another set of instruments will be housed on the platform of the rover, including VIS-NIR imagers and spectrometers, both for far-field context and near-field characterization of the regolith in the immediate vicinity of the rover. Also included in the sensor suite are a neutron spectrometer, ground-penetrating radar, and an instrumented cone penetrometer for subsurface assessment. Output from these sensors will be evaluated autonomously in real-time by decision-making software to evaluate if any of the targeted resources has been detected, and if so, to quantify their abundance. Algorithms for optimizing the mapping strategy based on target resource abundance and distribution are also included in the autonomous software. This approach emphasizes on-the-fly survey measurements to enable efficient and rapid prospecting of large areas, which will improve the economics of ISRU system approaches. The mature technology will enable autonomous rovers to create in-situ resource maps of lunar or other planetary surfaces, which will facilitate human and robotic exploration.

DNA "nano-claw": logic-based autonomous cancer targeting and therapy.

PubMed

You, Mingxu; Peng, Lu; Shao, Na; Zhang, Liqin; Qiu, Liping; Cui, Cheng; Tan, Weihong

2014-01-29

Cell types, both healthy and diseased, can be classified by inventories of their cell-surface markers. Programmable analysis of multiple markers would enable clinicians to develop a comprehensive disease profile, leading to more accurate diagnosis and intervention. As a first step to accomplish this, we have designed a DNA-based device, called "Nano-Claw". Combining the special structure-switching properties of DNA aptamers with toehold-mediated strand displacement reactions, this claw is capable of performing autonomous logic-based analysis of multiple cancer cell-surface markers and, in response, producing a diagnostic signal and/or targeted photodynamic therapy. We anticipate that this design can be widely applied in facilitating basic biomedical research, accurate disease diagnosis, and effective therapy.

Mechanisms for the target patterns formation in a stochastic bistable excitable medium

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

2018-04-01

We study the features of formation and evolution of spatiotemporal chaotic regime generated by autonomous pacemakers in excitable deterministic and stochastic bistable active media using the example of the FitzHugh - Nagumo biological neuron model under discrete medium conditions. The following possible mechanisms for the formation of autonomous pacemakers have been studied: 1) a temporal external force applied to a small region of the medium, 2) geometry of the solution region (the medium contains regions with Dirichlet or Neumann boundaries). In our work we explore the conditions for the emergence of pacemakers inducing target patterns in a stochastic bistable excitable system and propose the algorithm for their analysis.

Robust control of multi-jointed arm with a decentralized autonomous control mechanism

NASA Technical Reports Server (NTRS)

Kimura, Shinichi; Miyazaki, Ken; Suzuki, Yoshiaki

1994-01-01

A decentralized autonomous control mechanism applied to the control of three dimensional manipulators and its robustness to partial damage was assessed by computer simulation. Decentralized control structures are believed to be quite robust to time delay between the operator and the target system. A 10-jointed manipulator based on our control mechanism was able to continue its positioning task in three-dimensional space without revision of the control program, even after some of its joints were damaged. These results suggest that this control mechanism can be effectively applied to space telerobots, which are associated with serious time delay between the operator and the target system, and which cannot be easily repaired after being partially damaged.

"A" motor neuron disease.

PubMed

Vishnu, Venugopalan Y; Modi, Manish; Prabhakar, Sudesh; Bhansali, Anil; Goyal, Manoj Kumar

2014-01-15

Allgrove syndrome is a rare autosomal recessive disorder characterised by achalasia, alacrima, adrenal insufficiency, autonomic dysfunction and amyotrophy. The syndrome has been described in childhood and adult presentation, as in our case, is very rare. There is a considerable delay in diagnosis due to lack of awareness about the syndrome. We report a single case of a 36 year old man who was initially diagnosed and treated for achalasia cardia in our institute 14 years before. After 8 years he presented again with weakness and wasting predominantly distally. He had tongue fasciculations, brisk reflexes and extensor plantar. After supportive electrophysiological studies he was diagnosed as Amyotrophic lateral sclerosis. After 5 years he presented with generalised fatigue without any significant worsening of his neurological status. On reevaluation he had alacrimia, autonomic dysfunction and mild ACTH resistance. Allgrove syndrome may be an underdiagnosed cause of multisystem neurological disease due to the heterogeneous clinical presentation as well as for ignorance of clinician about the syndrome. Based on our case, we also believe that there does exist a subgroup of patients who follow a less severe and chronic course. Recognition of syndrome allows for treatment of autonomic dysfunction, adrenal insufficiency and dysphagia. © 2013.

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

Facial feedback and autonomic responsiveness reflect impaired emotional processing in Parkinson's Disease.

PubMed

Balconi, Michela; Pala, Francesca; Manenti, Rosa; Brambilla, Michela; Cobelli, Chiara; Rosini, Sandra; Benussi, Alberto; Padovani, Alessandro; Borroni, Barbara; Cotelli, Maria

2016-08-11

Emotional deficits are part of the non-motor features of Parkinson's disease but few attention has been paid to specific aspects such as subjective emotional experience and autonomic responses. This study aimed to investigate the mechanisms of emotional recognition in Parkinson's Disease (PD) using the following levels: explicit evaluation of emotions (Self-Assessment Manikin) and implicit reactivity (Skin Conductance Response; electromyographic measure of facial feedback of the zygomaticus and corrugator muscles). 20 PD Patients and 34 healthy controls were required to observe and evaluate affective pictures during physiological parameters recording. In PD, the appraisal process on both valence and arousal features of emotional cues were preserved, but we found significant impairment in autonomic responses. Specifically, in comparison to healthy controls, PD patients revealed lower Skin Conductance Response values to negative and high arousing emotional stimuli. In addition, the electromyographic measures showed defective responses exclusively limited to negative and high arousing emotional category: PD did not show increasing of corrugator activity in response to negative emotions as happened in heathy controls. PD subjects inadequately respond to the emotional categories which were considered more "salient": they had preserved appraisal process, but impaired automatic ability to distinguish between different emotional contexts.

Autonomic and subjective responsivity to emotional images in people with dissociative seizures.

PubMed

Pick, Susannah; Mellers, John D C; Goldstein, Laura H

2018-06-01

People with dissociative seizures (DS) report a range of difficulties in emotional functioning and exhibit altered responding to emotional facial expressions in experimental tasks. We extended this research by investigating subjective and autonomic reactivity (ratings of emotional valence, arousal and skin conductance responses [SCRs]) to general emotional images in 39 people with DS relative to 42 healthy control participants, whilst controlling for anxiety, depression, cognitive functioning and, where relevant, medication use. It was predicted that greater subjective negativity and arousal and increased SCRs in response to the affective pictures would be observed in the DS group. The DS group as a whole did not differ from controls in their subjective responses of valence and arousal. However, SCR amplitudes were greater in 'autonomic responders' with DS relative to 'autonomic responders' in the control group. A positive correlation was also observed between SCRs for highly arousing negative pictures and self-reported ictal autonomic arousal, in DS 'autonomic responders'. In the DS subgroup of autonomic 'non-responders', differences in subjective responses were observed for some conditions, compared to control 'non-responders'. The findings indicate unaffected subjective responses to emotional images in people with DS overall. However, within the group of people with DS, there may be subgroups characterized by differences in emotional responding. One subgroup (i.e., 'autonomic responders') exhibit heightened autonomic responses but intact subjective emotional experience, whilst another subgroup (i.e., 'autonomic non-responders') seem to experience greater subjective negativity and arousal for some emotional stimuli, despite less frequent autonomic reactions. The current results suggest that therapeutic interventions targeting awareness and regulation of physiological arousal and subjective emotional experience could be of value in some people with this disorder. © 2017 The Authors. Journal of Neuropsychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Modelling emergency decisions: recognition-primed decision making. The literature in relation to an ophthalmic critical incident.

PubMed

Bond, Susan; Cooper, Simon

2006-08-01

To review and reflect on the literature on recognition-primed decision (RPD) making and influences on emergency decisions with particular reference to an ophthalmic critical incident involving the sub-arachnoid spread of local anaesthesia following the peribulbar injection. This paper critics the literature on recognition-primed decision making, with particular reference to emergency situations. It illustrates the findings by focussing on an ophthalmic critical incident. Systematic literature review with critical incident reflection. Medline, CINAHL and PsychINFO databases were searched for papers on recognition-primed decision making (1996-2004) followed by the 'snowball method'. Studies were selected in accordance with preset criteria. A total of 12 papers were included identifying the recognition-primed decision making as a good theoretical description of acute emergency decisions. In addition, cognitive resources, situational awareness, stress, team support and task complexity were identified as influences on the decision process. Recognition-primed decision-making theory describes the decision processes of experts in time-bound emergency situations and is the foundation for a model of emergency decision making (Fig. 2). Decision theory and models, in this case related to emergency situations, inform practice and enhance clinical effectiveness. The critical incident described highlights the need for nurses to have a comprehensive and in-depth understanding of anaesthetic techniques as well as an ability to manage and resuscitate patients autonomously. In addition, it illustrates how the critical incidents should influence the audit cycle with improvements in patient safety.

Young people's comparative recognition and recall of an Australian Government Sexual Health Campaign.

PubMed

Lim, Megan S C; Gold, Judy; Bowring, Anna L; Pedrana, Alisa E; Hellard, Margaret E

2015-05-01

In 2009, the Australian Government's National Sexually Transmitted Infection Prevention Program launched a multi-million dollar sexual health campaign targeting young people. We assessed campaign recognition among a community sample of young people. Individuals aged 16-29 years self-completed a questionnaire at a music festival. Participants were asked whether they recognised the campaign image and attempted to match the correct campaign message. Recognition of two concurrent campaigns, GlaxoSmithKline's The Facts genital herpes campaign (targeting young women) and the Drama Downunder campaign (targeting gay men) were assessed simultaneously. Among 471 participants, just 29% recognised the National Sexually Transmitted Infection Prevention Program campaign. This compared to 52% recognising The Facts and 27% recognising Drama Downunder. Of 134 who recognised the National Sexually Transmitted Infection Prevention Program campaign, 27% correctly recalled the campaign messages compared to 61% of those recognising the Facts campaign, and 25% of those recognising the Drama Downunder campaign. There was no difference in National Sexually Transmitted Infection Prevention Program campaign recognition by gender or age. Campaign recognition and message recall of the National Sexually Transmitted Infection Prevention Program campaign was comparatively low. Future mass media sexual health campaigns targeting young people can aim for higher recognition and recall rates than that achieved by the National Sexually Transmitted Infection Prevention Program campaign. Alternative distribution channels and message styles should be considered to increase these rates. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Social appraisal influences recognition of emotions.

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

A benefit of context reinstatement to recognition memory in aging: the role of familiarity processes.

PubMed

Ward, Emma V; Maylor, Elizabeth A; Poirier, Marie; Korko, Malgorzata; Ruud, Jens C M

2017-11-01

Reinstatement of encoding context facilitates memory for targets in young and older individuals (e.g., a word studied on a particular background scene is more likely to be remembered later if it is presented on the same rather than a different scene or no scene), yet older adults are typically inferior at recalling and recognizing target-context pairings. This study examined the mechanisms of the context effect in normal aging. Age differences in word recognition by context condition (original, switched, none, new), and the ability to explicitly remember target-context pairings were investigated using word-scene pairs (Experiment 1) and word-word pairs (Experiment 2). Both age groups benefited from context reinstatement in item recognition, although older adults were significantly worse than young adults at identifying original pairings and at discriminating between original and switched pairings. In Experiment 3, participants were given a three-alternative forced-choice recognition task that allowed older individuals to draw upon intact familiarity processes in selecting original pairings. Performance was age equivalent. Findings suggest that heightened familiarity associated with context reinstatement is useful for boosting recognition memory in aging.

Diagnosing criterion-level effects on memory: what aspects of memory are enhanced by repeated retrieval?

PubMed

Vaughn, Kalif E; Rawson, Katherine A

2011-09-01

Previous research has shown that increasing the criterion level (i.e., the number of times an item must be correctly retrieved during practice) improves subsequent memory, but which specific components of memory does increased criterion level enhance? In two experiments, we examined the extent to which the criterion level affects associative memory, target memory, and cue memory. Participants studied Lithuanian-English word pairs via cued recall with restudy until items were correctly recalled one to five times. In Experiment 1, participants took one of four recall tests and one of three recognition tests after a 2-day delay. In Experiment 2, participants took only recognition tests after a 1-week delay. In both experiments, increasing the criterion level enhanced associative memory, as indicated by enhanced performance on forward and backward cued-recall tests and on tests of associative recognition. An increased criterion level also improved target memory, as indicated by enhanced free recall and recognition of targets, and improved cue memory, as indicated by enhanced free recall and recognition of cues.

When Age Matters: Differences in Facial Mimicry and Autonomic Responses to Peers' Emotions in Teenagers and Adults

PubMed Central

Ardizzi, Martina; Sestito, Mariateresa; Martini, Francesca; Umiltà, Maria Alessandra; Ravera, Roberto; Gallese, Vittorio

2014-01-01

Age-group membership effects on explicit emotional facial expressions recognition have been widely demonstrated. In this study we investigated whether Age-group membership could also affect implicit physiological responses, as facial mimicry and autonomic regulation, to observation of emotional facial expressions. To this aim, facial Electromyography (EMG) and Respiratory Sinus Arrhythmia (RSA) were recorded from teenager and adult participants during the observation of facial expressions performed by teenager and adult models. Results highlighted that teenagers exhibited greater facial EMG responses to peers' facial expressions, whereas adults showed higher RSA-responses to adult facial expressions. The different physiological modalities through which young and adults respond to peers' emotional expressions are likely to reflect two different ways to engage in social interactions with coetaneous. Findings confirmed that age is an important and powerful social feature that modulates interpersonal interactions by influencing low-level physiological responses. PMID:25337916

A Rare Cause of Hypothalamic Obesity, Rohhad Syndrome: 2 Cases.

PubMed

Şiraz, Ülkü Gül; Okdemir, Deniz; Direk, Gül; Akın, Leyla; Hatipoğlu, Nihal; Kendırcı, Mustafa; Kurtoğlu, Selim

2018-03-19

Rapid-onset obesity with hypoventilation, hypothalamic dysfunction and autonomic dysregulation (ROHHAD) syndrome is a rare disease that is difficult to diagnosis and distinguish from genetic obesity syndromes. The underlying causes of the disease has not been fully explained. Hypothalamic dysfunction causes endocrine problems, respiratory dysfunction and autonomic alterations. There are around 80 reported patients due to lack of recognition. We present two female patient suspected of ROHHAD due to weight gain since early childhood. The presented symptoms, respiratory and circulatory dysfunction, hypothalamic hypernatremia, hypothalamo-pituitary hormonal disorders such as santral hypothyrodism, hyperprolactinemia and santral early puberty are completely matched the criteria of ROHHAD syndrome. ROHHAD syndrome should be considered in differential diagnosis since it is difficult to distinguish from causes of monogenic obesity. Early identification of the disease reduces morbidity of the syndrome and patients require regular follow-up by a multidisciplinary approach.

The Temporal Dynamics of Spoken Word Recognition in Adverse Listening Conditions

ERIC Educational Resources Information Center

Brouwer, Susanne; Bradlow, Ann R.

2016-01-01

This study examined the temporal dynamics of spoken word recognition in noise and background speech. In two visual-world experiments, English participants listened to target words while looking at four pictures on the screen: a target (e.g. "candle"), an onset competitor (e.g. "candy"), a rhyme competitor (e.g.…

Morpho-Semantic Processing in Word Recognition: Evidence from Balanced and Biased Ambiguous Morphemes

ERIC Educational Resources Information Center

Tsang, Yiu-Kei; Chen, Hsuan-Chih

2013-01-01

The role of morphemic meaning in Chinese word recognition was examined with the masked and unmasked priming paradigms. Target words contained ambiguous morphemes biased toward the dominant or the subordinate meanings. Prime words either contained the same ambiguous morphemes in the subordinate interpretations or were unrelated to the targets. In…

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Specific recognition of polyphenols by molecularly imprinted polymers based on a ternary deep eutectic solvent.

PubMed

Fu, Najing; Li, Liteng; Liu, Xiao; Fu, Nian; Zhang, Chenchen; Hu, Liandong; Li, Donghao; Tang, Baokun; Zhu, Tao

2017-12-29

Typically, a target compound is selected as a template for a molecularly imprinted polymer (MIP); however, some target compounds are not suitable as templates because of their poor solubility. Using the tailoring properties of a deep eutectic solvent (DES), the insoluble target compound caffeic acid was transformed into a ternary choline chloride-caffeic acid-ethylene glycol (ChCl-CA-EG) DES, which was then employed as a template to prepare MIPs. The ternary DES-based MIPs were characterized by Fourier transform infrared spectroscopy, elemental analysis, scanning electron microscopy, and atomic force microscopy. The effects of time, temperature, ionic strength, and pH on the recognition processes for four polyphenols (caffeic acid, protocatechuic acid, catechin, and epicatechin) by 13 ChCl-CA-EG ternary DES-based MIPs was investigated using high-performance liquid chromatography. The recognition specificity of the MIPs for CA was significantly better than that for the other polyphenols, and the MIPs exhibited obvious characteristics of chromatographic packing materials. In addition, the recognition processes mainly followed a second-order kinetics model and the Freundlich isotherm model, which together indicated that the MIPs mainly recognized the polyphenols by chemical interactions including ion exchange, electron exchange, and new bond formation. Furthermore, the specific recognition ability of the MIPs for polyphenols, which was better than those of C 18 , C 8 , or non-molecularly imprinted polymer adsorbents, was successfully applied to the recognition of polyphenols in a Radix asteris sample. The transformation of an insoluble target compound in a polymeric DES for MIP preparation and recognition is a novel and feasible strategy suitable for use in further MIP research developments. Copyright © 2017 Elsevier B.V. All rights reserved.

Autonomous landing and ingress of micro-air-vehicles in urban environments based on monocular vision

NASA Astrophysics Data System (ADS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-06-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

NASA Technical Reports Server (NTRS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-01-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

Optimization of interneuron function by direct coupling of cell migration and axonal targeting.

PubMed

Lim, Lynette; Pakan, Janelle M P; Selten, Martijn M; Marques-Smith, André; Llorca, Alfredo; Bae, Sung Eun; Rochefort, Nathalie L; Marín, Oscar

2018-06-18

Neural circuit assembly relies on the precise synchronization of developmental processes, such as cell migration and axon targeting, but the cell-autonomous mechanisms coordinating these events remain largely unknown. Here we found that different classes of interneurons use distinct routes of migration to reach the embryonic cerebral cortex. Somatostatin-expressing interneurons that migrate through the marginal zone develop into Martinotti cells, one of the most distinctive classes of cortical interneurons. For these cells, migration through the marginal zone is linked to the development of their characteristic layer 1 axonal arborization. Altering the normal migratory route of Martinotti cells by conditional deletion of Mafb-a gene that is preferentially expressed by these cells-cell-autonomously disrupts axonal development and impairs the function of these cells in vivo. Our results suggest that migration and axon targeting programs are coupled to optimize the assembly of inhibitory circuits in the cerebral cortex.

Active Collision Avoidance for Planetary Landers

NASA Technical Reports Server (NTRS)

Rickman, Doug; Hannan, Mike; Srinivasan, Karthik

2014-01-01

Present day robotic missions to other planets require precise, a priori knowledge of the terrain to pre-determine a landing spot that is safe. Landing sites can be miles from the mission objective, or, mission objectives may be tailored to suit landing sites. Future robotic exploration missions should be capable of autonomously identifying a safe landing target within a specified target area selected by mission requirements. Such autonomous landing sites must (1) 'see' the surface, (2) identify a target, and (3) land the vehicle. Recent advances in radar technology have resulted in small, lightweight, low power radars that are used for collision avoidance and cruise control systems in automobiles. Such radar systems can be adapted for use as active hazard avoidance systems for planetary landers. The focus of this CIF proposal is to leverage earlier work on collision avoidance systems for MSFC's Mighty Eagle lander and evaluate the use of automotive radar systems for collision avoidance in planetary landers.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2016-05-01

The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

Vision-based control for flight relative to dynamic environments

NASA Astrophysics Data System (ADS)

Causey, Ryan Scott

The concept of autonomous systems has been considered an enabling technology for a diverse group of military and civilian applications. The current direction for autonomous systems is increased capabilities through more advanced systems that are useful for missions that require autonomous avoidance, navigation, tracking, and docking. To facilitate this level of mission capability, passive sensors, such as cameras, and complex software are added to the vehicle. By incorporating an on-board camera, visual information can be processed to interpret the surroundings. This information allows decision making with increased situational awareness without the cost of a sensor signature, which is critical in military applications. The concepts presented in this dissertation facilitate the issues inherent to vision-based state estimation of moving objects for a monocular camera configuration. The process consists of several stages involving image processing such as detection, estimation, and modeling. The detection algorithm segments the motion field through a least-squares approach and classifies motions not obeying the dominant trend as independently moving objects. An approach to state estimation of moving targets is derived using a homography approach. The algorithm requires knowledge of the camera motion, a reference motion, and additional feature point geometry for both the target and reference objects. The target state estimates are then observed over time to model the dynamics using a probabilistic technique. The effects of uncertainty on state estimation due to camera calibration are considered through a bounded deterministic approach. The system framework focuses on an aircraft platform of which the system dynamics are derived to relate vehicle states to image plane quantities. Control designs using standard guidance and navigation schemes are then applied to the tracking and homing problems using the derived state estimation. Four simulations are implemented in MATLAB that build on the image concepts present in this dissertation. The first two simulations deal with feature point computations and the effects of uncertainty. The third simulation demonstrates the open-loop estimation of a target ground vehicle in pursuit whereas the four implements a homing control design for the Autonomous Aerial Refueling (AAR) using target estimates as feedback.

Global Positioning System Synchronized Active Light Autonomous Docking System

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor); Bell, Joseph L. (Inventor)

1996-01-01

A Global Positioning System Synchronized Active Light Autonomous Docking System (GPSSALADS) for automatically docking a chase vehicle with a target vehicle comprising at least one active light emitting target which is operatively attached to the target vehicle. The target includes a three-dimensional array of concomitantly flashing lights which flash at a controlled common frequency. The GPSSALADS further comprises a visual tracking sensor operatively attached to the chase vehicle for detecting and tracking the target vehicle. Its performance is synchronized with the flash frequency of the lights by a synchronization means which is comprised of first and second internal clocks operatively connected to the active light target and visual tracking sensor, respectively, for providing timing control signals thereto, respectively. The synchronization means further includes first and second Global Positioning System receivers operatively connected to the first and second internal clocks, respectively, for repeatedly providing simultaneous synchronization pulses to the internal clocks, respectively. In addition, the GPSSALADS includes a docking process controller means which is operatively attached to the chase vehicle and is responsive to the visual tracking sensor for producing commands for the guidance and propulsion system of the chase vehicle.

Global Positioning System Synchronized Active Light Autonomous Docking System

NASA Technical Reports Server (NTRS)

Howard, Richard (Inventor)

1994-01-01

A Global Positioning System Synchronized Active Light Autonomous Docking System (GPSSALADS) for automatically docking a chase vehicle with a target vehicle comprises at least one active light emitting target which is operatively attached to the target vehicle. The target includes a three-dimensional array of concomitantly flashing lights which flash at a controlled common frequency. The GPSSALADS further comprises a visual tracking sensor operatively attached to the chase vehicle for detecting and tracking the target vehicle. Its performance is synchronized with the flash frequency of the lights by a synchronization means which is comprised of first and second internal clocks operatively connected to the active light target and visual tracking sensor, respectively, for providing timing control signals thereto, respectively. The synchronization means further includes first and second Global Positioning System receivers operatively connected to the first and second internal clocks, respectively, for repeatedly providing simultaneous synchronization pulses to the internal clocks, respectively. In addition, the GPSSALADS includes a docking process controller means which is operatively attached to the chase vehicle and is responsive to the visual tracking sensor for producing commands for the guidance and propulsion system of the chase vehicle.

Object classification for obstacle avoidance

NASA Astrophysics Data System (ADS)

Regensburger, Uwe; Graefe, Volker

1991-03-01

Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.

The 4-D approach to visual control of autonomous systems

NASA Technical Reports Server (NTRS)

Dickmanns, Ernst D.

1994-01-01

Development of a 4-D approach to dynamic machine vision is described. Core elements of this method are spatio-temporal models oriented towards objects and laws of perspective projection in a foward mode. Integration of multi-sensory measurement data was achieved through spatio-temporal models as invariants for object recognition. Situation assessment and long term predictions were allowed through maintenance of a symbolic 4-D image of processes involving objects. Behavioral capabilities were easily realized by state feedback and feed-foward control.

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework.

PubMed

Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu

2016-04-19

Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

Influence of Deep Breathing on Heart Rate Variability in Parkinson's Disease: Co-relation with Severity of Disease and Non-Motor Symptom Scale Score.

PubMed

Bidikar, Mukta Pritam; Jagtap, Gayatri J; Chakor, Rahul T

2014-07-01

Dysautonomia and non-motor symptoms (NMS) in Parkinson's disease (PD) are frequent, disabling and reduce quality of life of patient. There is a paucity of studies on autonomic dysfunction in PD in Indian population. The study aimed to evaluate autonomic dysfunction in PD patients and co-relate the findings with severity of PD and Non-Motor Symptoms Scale (NMSS) score. We evaluated autonomic function in 30 diagnosed patients of PD (age 55-70 years) and 30 healthy age-matched controls by 3 min deep breathing test (DBT). NMSS was used to identify non-motor symptoms and Hoehn and Yahr (HY) Scale to grade severity of PD. The DBT findings were co-related with severity of PD (HY staging) and NMSS score. DBT was found to be abnormal in 40% while it was on borderline in 33.3% of PD patients. There was a statistically significant difference (p<0.01) between patients and control group for the DBT. NMS were reported across all the stages of PD but with variable frequency and severity for individual symptom. A negative co-relation was found between results of deep breathing test and clinical severity of disease and NMSS score. Abnormalities of autonomic function and NMS were integral and present across all the stages of PD patients. Early recognition and treatment of these may decrease morbidity and improve quality of life of PD patients.

Word Recognition is Affected by the Meaning of Orthographic Neighbours: Evidence from Semantic Decision Tasks

ERIC Educational Resources Information Center

Boot, Inge; Pecher, Diane

2008-01-01

Many models of word recognition predict that neighbours of target words will be activated during word processing. Cascaded models can make the additional prediction that semantic features of those neighbours get activated before the target has been uniquely identified. In two semantic decision tasks neighbours that were congruent (i.e., from the…

Autonomous learning by simple dynamical systems with a discrete-time formulation

NASA Astrophysics Data System (ADS)

Bilen, Agustín M.; Kaluza, Pablo

2017-05-01

We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

PubMed

Ren, Weitong; Ji, Dongqing; Xu, Xiulian

2018-01-01

The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

An Unsolved Mystery: The Target-Recognizing RNA Species of MicroRNA Genes

PubMed Central

Chen, Chang-Zheng

2013-01-01

MicroRNAs (miRNAs) are an abundant class of endogenous ~ 21-nucleotide (nt) RNAs. These small RNAs are produced from long primary miRNA transcripts — pri-miRNAs — through sequential endonucleolytic maturation steps that yield precursor miRNA (pre-miRNA) intermediates and then the mature miRNAs. The mature miRNAs are loaded into the RNA-induced silencing complexes (RISC), and guide RISC to target mRNAs for cleavage and/or translational repression. This paradigm, which represents one of major discoveries of modern molecular biology, is built on the assumption that mature miRNAs are the only species produced from miRNA genes that recognize targets. This assumption has guided the miRNA field for more than a decade and has led to our current understanding of the mechanisms of target recognition and repression by miRNAs. Although progress has been made, fundamental questions remain unanswered with regard to the principles of target recognition and mechanisms of repression. Here I raise questions about the assumption that mature miRNAs are the only target-recognizing species produced from miRNA genes and discuss the consequences of working under an incomplete or incorrect assumption. Moreover, I present evolution-based and experimental evidence that support the roles of pri-/pre-miRNAs in target recognition and repression. Finally, I propose a conceptual framework that integrates the functions of pri-/pre-miRNAs and mature miRNAs in target recognition and repression. The integrated framework opens experimental enquiry and permits interpretation of fundamental problems that have so far been precluded. PMID:23685275

The method of micro-motion cycle feature extraction based on confidence coefficient evaluation criteria

NASA Astrophysics Data System (ADS)

Tang, Chuanzi; Ren, Hongmei; Bo, Li; Jing, Huang

2017-11-01

In radar target recognition, the micro motion characteristics of target is one of the characteristics that researchers pay attention to at home and abroad, in which the characteristics of target precession cycle is one of the important characteristics of target movement characteristics. Periodic feature extraction methods have been studied for years, the complex shape of the target and the scattering center stack lead to random fluctuations of the RCS. These random fluctuations also exist certain periodicity, which has a great influence on the target recognition result. In order to solve the problem, this paper proposes a extraction method of micro-motion cycle feature based on confidence coefficient evaluation criteria.

Bilevel shared control for teleoperators

NASA Technical Reports Server (NTRS)

Hayati, Samad A. (Inventor); Venkataraman, Subramanian T. (Inventor)

1992-01-01

A shared system is disclosed for robot control including integration of the human and autonomous input modalities for an improved control. Autonomously planned motion trajectories are modified by a teleoperator to track unmodelled target motions, while nominal teleoperator motions are modified through compliance to accommodate geometric errors autonomously in the latter. A hierarchical shared system intelligently shares control over a remote robot between the autonomous and teleoperative portions of an overall control system. Architecture is hierarchical, and consists of two levels. The top level represents the task level, while the bottom, the execution level. In space applications, the performance of pure teleoperation systems depend significantly on the communication time delays between the local and the remote sites. Selection/mixing matrices are provided with entries which reflect how each input's signals modality is weighted. The shared control minimizes the detrimental effects caused by these time delays between earth and space.

Autoantibody-mediated bowel and bladder dysfunction in a patient with chronic, nondiabetic neuropathy.

PubMed

Jackson, Michael W; Gordon, Thomas P; McCombe, Pamela A

2008-04-01

Physiological techniques can be used to detect novel autoantibodies causing alteration of autonomic function after passive transfer to mice. Previously, such antibodies have been detected in patients with type I diabetes mellitus, myasthenia gravis, and Sjogren's syndrome. We now describe a patient with an idiopathic nondiabetic neuropathy with prominent autonomic symptoms, including bladder and bowel dysfunction. Physiological assays of whole colon and bladder were used to determine the presence in the patient serum of functional autoantibodies capable of mediating autonomic dysfunction. Immunoglobulin G (IgG) from this patient was able to disrupt bladder and bowel function on passive transfer to mice. This is a new pattern of autoantibody-mediated abnormality. Although the target antigen is unknown, it is likely to be a cell-surface receptor or ion channel. This case highlights the usefulness of passive transfer studies in detecting functional antibodies in patients with autonomic neuropathy.

Draper Laboratory small autonomous aerial vehicle

NASA Astrophysics Data System (ADS)

DeBitetto, Paul A.; Johnson, Eric N.; Bosse, Michael C.; Trott, Christian A.

1997-06-01

The Charles Stark Draper Laboratory, Inc. and students from Massachusetts Institute of Technology and Boston University have cooperated to develop an autonomous aerial vehicle that won the 1996 International Aerial Robotics Competition. This paper describes the approach, system architecture and subsystem designs for the entry. This entry represents a combination of many technology areas: navigation, guidance, control, vision processing, human factors, packaging, power, real-time software, and others. The aerial vehicle, an autonomous helicopter, performs navigation and control functions using multiple sensors: differential GPS, inertial measurement unit, sonar altimeter, and a flux compass. The aerial transmits video imagery to the ground. A ground based vision processor converts the image data into target position and classification estimates. The system was designed, built, and flown in less than one year and has provided many lessons about autonomous vehicle systems, several of which are discussed. In an appendix, our current research in augmenting the navigation system with vision- based estimates is presented.

Age differences in accuracy and choosing in eyewitness identification and face recognition.

PubMed

Searcy, J H; Bartlett, J C; Memon, A

1999-05-01

Studies of aging and face recognition show age-related increases in false recognitions of new faces. To explore implications of this false alarm effect, we had young and senior adults perform (1) three eye-witness identification tasks, using both target present and target absent lineups, and (2) and old/new recognition task in which a study list of faces was followed by a test including old and new faces, along with conjunctions of old faces. Compared with the young, seniors had lower accuracy and higher choosing rates on the lineups, and they also falsely recognized more new faces on the recognition test. However, after screening for perceptual processing deficits, there was no age difference in false recognition of conjunctions, or in discriminating old faces from conjunctions. We conclude that the false alarm effect generalizes to lineup identification, but does not extend to conjunction faces. The findings are consistent with age-related deficits in recollection of context and relative age invariance in perceptual integrative processes underlying the experience of familiarity.

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

Autonomous microsystems for ground observation (AMIGO)

NASA Astrophysics Data System (ADS)

Laou, Philips

2005-05-01

This paper reports the development of a prototype autonomous surveillance microsystem AMIGO that can be used for remote surveillance. Each AMIGO unit is equipped with various sensors and electronics. These include passive infrared motion sensor, acoustic sensor, uncooled IR camera, electronic compass, global positioning system (GPS), and spread spectrum wireless transceiver. The AMIGO unit was configured to multipoint (AMIGO units) to point (base station) communication mode. In addition, field trials were conducted with AMIGO in various scenarios. These scenarios include personnel and vehicle intrusion detection (motion or sound) and target imaging; determination of target GPS position by triangulation; GPS position real time tracking; entrance event counting; indoor surveillance; and aerial surveillance on a radio controlled model plane. The architecture and test results of AMIGO will be presented.

Machine vision and the OMV

NASA Technical Reports Server (NTRS)

Mcanulty, M. A.

1986-01-01

The orbital Maneuvering Vehicle (OMV) is intended to close with orbiting targets for relocation or servicing. It will be controlled via video signals and thruster activation based upon Earth or space station directives. A human operator is squarely in the middle of the control loop for close work. Without directly addressing future, more autonomous versions of a remote servicer, several techniques that will doubtless be important in a future increase of autonomy also have some direct application to the current situation, particularly in the area of image enhancement and predictive analysis. Several techniques are presentet, and some few have been implemented, which support a machine vision capability proposed to be adequate for detection, recognition, and tracking. Once feasibly implemented, they must then be further modified to operate together in real time. This may be achieved by two courses, the use of an array processor and some initial steps toward data reduction. The methodology or adapting to a vector architecture is discussed in preliminary form, and a highly tentative rationale for data reduction at the front end is also discussed. As a by-product, a working implementation of the most advanced graphic display technique, ray-casting, is described.

Autonomous vehicle navigation utilizing fuzzy controls concepts for a next generation wheelchair.

PubMed

Hansen, J D; Barrett, S F; Wright, C H G; Wilcox, M

2008-01-01

Three different positioning techniques were investigated to create an autonomous vehicle that could accurately navigate towards a goal: Global Positioning System (GPS), compass dead reckoning, and Ackerman steering. Each technique utilized a fuzzy logic controller that maneuvered a four-wheel car towards a target. The reliability and the accuracy of the navigation methods were investigated by modeling the algorithms in software and implementing them in hardware. To implement the techniques in hardware, positioning sensors were interfaced to a remote control car and a microprocessor. The microprocessor utilized the sensor measurements to orient the car with respect to the target. Next, a fuzzy logic control algorithm adjusted the front wheel steering angle to minimize the difference between the heading and bearing. After minimizing the heading error, the car maintained a straight steering angle along its path to the final destination. The results of this research can be used to develop applications that require precise navigation. The design techniques can also be implemented on alternate platforms such as a wheelchair to assist with autonomous navigation.

Coordination of Word Recognition and Oculomotor Control During Reading: The Role of Implicit Lexical Decisions

PubMed Central

Choi, Wonil; Gordon, Peter C.

2013-01-01

The coordination of word-recognition and oculomotor processes during reading was evaluated in two eye-tracking experiments that examined how word skipping, where a word is not fixated during first-pass reading, is affected by the lexical status of a letter string in the parafovea and ease of recognizing that string. Ease of lexical recognition was manipulated through target-word frequency (Experiment 1) and through repetition priming between prime-target pairs embedded in a sentence (Experiment 2). Using the gaze-contingent boundary technique the target word appeared in the parafovea either with full preview or with transposed-letter (TL) preview. The TL preview strings were nonwords in Experiment 1 (e.g., bilnk created from the target blink), but were words in Experiment 2 (e.g., sacred created from the target scared). Experiment 1 showed greater skipping for high-frequency than low-frequency target words in the full preview condition but not in the TL preview (nonword) condition. Experiment 2 showed greater skipping for target words that repeated an earlier prime word than for those that did not, with this repetition priming occurring both with preview of the full target and with preview of the target’s TL neighbor word. However, time to progress from the word after the target was greater following skips of the TL preview word, whose meaning was anomalous in the sentence context, than following skips of the full preview word whose meaning fit sensibly into the sentence context. Together, the results support the idea that coordination between word-recognition and oculomotor processes occurs at the level of implicit lexical decisions. PMID:23106372

A novel Heart Rate Variability analysis using Lagged Poincaré plot: A study on hedonic visual elicitation.

PubMed

Nardelli, M; Greco, A; Valenza, G; Lanata, A; Bailon, R; Scilingo, E P

2017-07-01

This paper reports on a novel method for the analysis of Heart Rate Variability (HRV) through Lagged Poincaré Plot (LPP) theory. Specifically a hybrid method, LPP symb , including LPP quantifiers and related symbolic dynamics was proposed. LPP has been applied to investigate the autonomic response to pleasant and unpleasant pictures extracted from the International Affective Picture System (IAPS). IAPS pictures are standardized in terms of level of arousal, i.e. the intensity of the evoked emotion, and valence, i.e. the level of pleasantness/unpleasantness, according to the Circumplex model of Affects (CMA). Twenty-two healthy subjects were enrolled in the experiment, which comprised four sessions with increasing arousal level. Within each session valence increased from positive to negative. An ad-hoc pattern recognition algorithm using a Leave-One-Subject-Out (LOSO) procedure based on a Quadratic Discriminant Classifier (QDC) was implemented. Our pattern recognition system was able to classify pleasant and unpleasant sessions with an accuracy of 71.59%. Therefore, we can suggest the use of the LPP symb for emotion recognition.

Experiments and improvements of ear recognition based on local texture descriptors

NASA Astrophysics Data System (ADS)

Benzaoui, Amir; Adjabi, Insaf; Boukrouche, Abdelhani

2017-04-01

The morphology of the human ear presents rich and stable information embedded on the curved 3-D surface and has as a result attracted considerable attention from forensic scientists and engineers as a biometric recognition modality. However, recognizing a person's identity from the morphology of the human ear in unconstrained environments, with insufficient and incomplete training data, strong person-specificity, and high within-range variance, can be very challenging. Following our previous work on ear recognition based on local texture descriptors, we propose to use anatomical and embryological information about the human ear in order to find the autonomous components and the locations where large interindividual variations can be detected. Embryology is particularly relevant to our approach as it provides information on the possible changes that can be observed in the external structure of the ear. We experimented with three publicly available databases, namely: IIT Delhi-1, IIT Delhi-2, and USTB-1, consisting of several ear benchmarks acquired under varying conditions and imaging qualities. The experiments show excellent results, beyond the state of the art.

Single-Command Approach and Instrument Placement by a Robot on a Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2005-01-01

AUTOAPPROACH is a computer program that enables a mobile robot to approach a target autonomously, starting from a distance of as much as 10 m, in response to a single command. AUTOAPPROACH is used in conjunction with (1) software that analyzes images acquired by stereoscopic cameras aboard the robot and (2) navigation and path-planning software that utilizes odometer readings along with the output of the image-analysis software. Intended originally for application to an instrumented, wheeled robot (rover) in scientific exploration of Mars, AUTOAPPROACH could be adapted to terrestrial applications, notably including the robotic removal of land mines and other unexploded ordnance. A human operator generates the approach command by selecting the target in images acquired by the robot cameras. The approach path consists of multiple legs. Feature points are derived from images that contain the target and are thereafter tracked to correct odometric errors and iteratively refine estimates of the position and orientation of the robot relative to the target on successive legs. The approach is terminated when the robot attains the position and orientation required for placing a scientific instrument at the target. The workspace of the robot arm is then autonomously checked for self/terrain collisions prior to the deployment of the scientific instrument onto the target.

Cognitive Predictors of Spoken Word Recognition in Children With and Without Developmental Language Disorders.

PubMed

Evans, Julia L; Gillam, Ronald B; Montgomery, James W

2018-05-10

This study examined the influence of cognitive factors on spoken word recognition in children with developmental language disorder (DLD) and typically developing (TD) children. Participants included 234 children (aged 7;0-11;11 years;months), 117 with DLD and 117 TD children, propensity matched for age, gender, socioeconomic status, and maternal education. Children completed a series of standardized assessment measures, a forward gating task, a rapid automatic naming task, and a series of tasks designed to examine cognitive factors hypothesized to influence spoken word recognition including phonological working memory, updating, attention shifting, and interference inhibition. Spoken word recognition for both initial and final accept gate points did not differ for children with DLD and TD controls after controlling target word knowledge in both groups. The 2 groups also did not differ on measures of updating, attention switching, and interference inhibition. Despite the lack of difference on these measures, for children with DLD, attention shifting and interference inhibition were significant predictors of spoken word recognition, whereas updating and receptive vocabulary were significant predictors of speed of spoken word recognition for the children in the TD group. Contrary to expectations, after controlling for target word knowledge, spoken word recognition did not differ for children with DLD and TD controls; however, the cognitive processing factors that influenced children's ability to recognize the target word in a stream of speech differed qualitatively for children with and without DLDs.

The cross-category effect: mere social categorization is sufficient to elicit an own-group bias in face recognition.

PubMed

Bernstein, Michael J; Young, Steven G; Hugenberg, Kurt

2007-08-01

Although the cross-race effect (CRE) is a well-established phenomenon, both perceptual-expertise and social-categorization models have been proposed to explain the effect. The two studies reported here investigated the extent to which categorizing other people as in-group versus out-group members is sufficient to elicit a pattern of face recognition analogous to that of the CRE, even when perceptual expertise with the stimuli is held constant. In Study 1, targets were categorized as members of real-life in-groups and out-groups (based on university affiliation), whereas in Study 2, targets were categorized into experimentally created minimal groups. In both studies, recognition performance was better for targets categorized as in-group members, despite the fact that perceptual expertise was equivalent for in-group and out-group faces. These results suggest that social-cognitive mechanisms of in-group and out-group categorization are sufficient to elicit performance differences for in-group and out-group face recognition.

Intrinsic Cholinergic Mechanisms Regulating Cerebral Blood Flow as a Target for Organophosphate Action

DTIC Science & Technology

1988-10-01

acetyltransferase (ChAT), the ACh- C= synthesizing enzyme. ChAT-immunoreactive cell bodies and processes were localized to autonomic or limbic nuclei throughout...the neuraxis and close appositions with brainstemn microvessels and ependymal cells . Moreover, theA DO , U03 Eoirlo oil ov wavs I 69LET9 SCCUmTYV...spinal preganglionic neurons of the intermediolateral cell columns ([ML). ChAT-immunoreactive cell bodies and processes were localized to autonomic or

Deployable reconnaissance from a VTOL UAS in urban environments

NASA Astrophysics Data System (ADS)

Barnett, Shane; Bird, John; Culhane, Andrew; Sharkasi, Adam; Reinholtz, Charles

2007-04-01

Reconnaissance collection in unknown or hostile environments can be a dangerous and life threatening task. To reduce this risk, the Unmanned Systems Group at Virginia Tech has produced a fully autonomous reconnaissance system able to provide live video reconnaissance from outside and inside unknown structures. This system consists of an autonomous helicopter which launches a small reconnaissance pod inside a building and an operator control unit (OCU) on a ground station. The helicopter is a modified Bergen Industrial Twin using a Rotomotion flight controller and can fly missions of up to one half hour. The mission planning OCU can control the helicopter remotely through teleoperation or fully autonomously by GPS waypoints. A forward facing camera and template matching aid in navigation by identifying the target building. Once the target structure is identified, vision algorithms will center the UAS adjacent to open windows or doorways. Tunable parameters in the vision algorithm account for varying launch distances and opening sizes. Launch of the reconnaissance pod may be initiated remotely through a human in the loop or autonomously. Compressed air propels the half pound stationary pod or the larger mobile pod into the open portals. Once inside the building, the reconnaissance pod will then transmit live video back to the helicopter. The helicopter acts as a repeater node for increased video range and simplification of communication back to the ground station.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Recognition Imaging of Acetylated Chromatin Using a DNA Aptamer

PubMed Central

Lin, Liyun; Fu, Qiang; Williams, Berea A.R.; Azzaz, Abdelhamid M.; Shogren-Knaak, Michael A.; Chaput, John C.; Lindsay, Stuart

2009-01-01

Histone acetylation plays an important role in the regulation of gene expression. A DNA aptamer generated by in vitro selection to be highly specific for histone H4 protein acetylated at lysine 16 was used as a recognition element for atomic force microscopy-based recognition imaging of synthetic nucleosomal arrays with precisely controlled acetylation. The aptamer proved to be reasonably specific at recognizing acetylated histones, with recognition efficiencies of 60% on-target and 12% off-target. Though this selectivity is much poorer than the >2000:1 equilibrium specificity of the aptamer, it is a large improvement on the performance of a ChIP-quality antibody, which is not selective at all in this application, and it should permit high-fidelity recognition with repeated imaging. The ability to image the precise location of posttranslational modifications may permit nanometer-scale investigation of their effect on chromatin structure. PMID:19751687

Simulation Trial Results for the Cooperative Autonomous Underwater Vehicle Demonstration (SA15)

DTIC Science & Technology

2013-05-01

acknowl- edges the location and then replies when it has found the target. Description Code Notes Hunt Target HHH pos where pos is the MGRS location of...the target to hunt Acknowledge AAA HHH pos where pos is the MGRS location of the target to hunt Found Target VVV 2.2.5 Meredith MMI (Singapore Control...phase, Reacquire, was initiated by the Meredith vehicle sending a Reacquire message with an MGRS coordinate to Mullaya (“ HHH ” pos). Mullaya would then

The effects of timbre on melody recognition are mediated by familiarity

NASA Astrophysics Data System (ADS)

McAuley, J. Devin; Ayala, Chris

2002-11-01

Two experiments examined the role of timbre in music recognition. In both experiments, participants rated the familiarity of a set of novel and well-known musical excerpts during a study phase and then were given a surprise old/new recognition test after a retention interval. The recognition test was comprised of the target melodies and an equal number of distractors; participants were instructed to respond yes to the targets and no to the distractors. In experiment 1, the timbre of the melodies was held constant throughout the study and then either stayed the same or switched to a different instrument sound during the test. In experiment 2, timbre varied randomly from trial to trial between the same two instruments used in experiment 1, yielding target melodies that were either mismatched or matched in their timbre. Switching timbre between study and test in experiment 1 was found to hurt the recognition of the novel melodies, but not the familiar melodies. The mediating effect of familiarity was eliminated in experiment 2 when timbre varied randomly from trial to trial rather than remaining constant. Possible reasons for the difference between studies will be discussed.

On certain development aspects of an ipsas-based system-target approach to evaluation of net asset sustainability level projects in high-rise construction

NASA Astrophysics Data System (ADS)

Kazaryan, Ruben

2018-03-01

Problems of accounting and reporting of net assets and the procedure of their formation taking into account the specifics of the economic and legal status of property of a non-commercial autonomous institution are some of the most controversial in the accounting for entities of the public sector. The study focuses on justification of accounting rules for net assets of public sector entities. The methods used in the study are as follows: comparison, synthesis, analysis, logical approach, and system approach. The article examines legal aspects and specifics of recognition of assets of public sector entities in accordance with IPSAS standards (International Public Sector Accounting Standards are a set of accounting standards issued by IPSASB (Council for International Financial Reporting Standards for Public Sector Organizations) used by state-owned enterprises worldwide in preparation of financial statements as of the 31st of August, 2015. The most crucial factor in the modeling of key performance indicators of the system-target approach to estimation of the sustainability level of net assets on the basis of IPSAS is a multicriterial evaluation of the basic management strategy for quality system elements used in operational and strategic planning projects operations in high-rise construction. We offer an alternative evaluation of assets due to be returned to the right holder (the state controller) in the event of liquidation of a public sector entity.

Human body contour data based activity recognition.

PubMed

Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

2013-01-01

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

First Results from a Hardware-in-the-Loop Demonstration of Closed-Loop Autonomous Formation Flying

NASA Technical Reports Server (NTRS)

Gill, E.; Naasz, Bo; Ebinuma, T.

2003-01-01

A closed-loop system for the demonstration of autonomous satellite formation flying technologies using hardware-in-the-loop has been developed. Making use of a GPS signal simulator with a dual radio frequency outlet, the system includes two GPS space receivers as well as a powerful onboard navigation processor dedicated to the GPS-based guidance, navigation, and control of a satellite formation in real-time. The closed-loop system allows realistic simulations of autonomous formation flying scenarios, enabling research in the fields of tracking and orbit control strategies for a wide range of applications. The autonomous closed-loop formation acquisition and keeping strategy is based on Lyapunov's direct control method as applied to the standard set of Keplerian elements. This approach not only assures global and asymptotic stability of the control but also maintains valuable physical insight into the applied control vectors. Furthermore, the approach can account for system uncertainties and effectively avoids a computationally expensive solution of the two point boundary problem, which renders the concept particularly attractive for implementation in onboard processors. A guidance law has been developed which strictly separates the relative from the absolute motion, thus avoiding the numerical integration of a target trajectory in the onboard processor. Moreover, upon using precise kinematic relative GPS solutions, a dynamical modeling or filtering is avoided which provides for an efficient implementation of the process on an onboard processor. A sample formation flying scenario has been created aiming at the autonomous transition of a Low Earth Orbit satellite formation from an initial along-track separation of 800 m to a target distance of 100 m. Assuming a low-thrust actuator which may be accommodated on a small satellite, a typical control accuracy of less than 5 m has been achieved which proves the applicability of autonomous formation flying techniques to formations of satellites as close as 50 m.

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1998-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest Citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1997-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Tree-structured sensor fusion architecture for distributed sensor networks

NASA Astrophysics Data System (ADS)

Iyengar, S. Sitharama; Kashyap, Rangasami L.; Madan, Rabinder N.; Thomas, Daryl D.

1990-10-01

An assessment of numerous activities in the field of multisensor target recognition reveals several trends and conditions which are cause for concern. .These concerns are analyzed in terms of their potential impact on the ultimate employment of automatic target recognition in military systems. Suggestions for additional investigation and guidance for current activities are presented with respect to some of the identified concerns.

Automatic integration of social information in emotion recognition.

PubMed

Mumenthaler, Christian; Sander, David

2015-04-01

This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. (c) 2015 APA, all rights reserved).

Research and Development of Target Recognition and Location Crawling Platform based on Binocular Vision

NASA Astrophysics Data System (ADS)

Xu, Weidong; Lei, Zhu; Yuan, Zhang; Gao, Zhenqing

2018-03-01

The application of visual recognition technology in industrial robot crawling and placing operation is one of the key tasks in the field of robot research. In order to improve the efficiency and intelligence of the material sorting in the production line, especially to realize the sorting of the scattered items, the robot target recognition and positioning crawling platform based on binocular vision is researched and developed. The images were collected by binocular camera, and the images were pretreated. Harris operator was used to identify the corners of the images. The Canny operator was used to identify the images. Hough-chain code recognition was used to identify the images. The target image in the image, obtain the coordinates of each vertex of the image, calculate the spatial position and posture of the target item, and determine the information needed to capture the movement and transmit it to the robot control crawling operation. Finally, In this paper, we use this method to experiment the wrapping problem in the express sorting process The experimental results show that the platform can effectively solve the problem of sorting of loose parts, so as to achieve the purpose of efficient and intelligent sorting.

[Representation of letter position in visual word recognition process].

PubMed

Makioka, S

1994-08-01

Two experiments investigated the representation of letter position in visual word recognition process. In Experiment 1, subjects (12 undergraduates and graduates) were asked to detect a target word in a briefly-presented probe. Probes consisted of two kanji words. The latters which formed targets (critical letters) were always contained in probes. (e.g. target: [symbol: see text] probe: [symbol: see text]) High false alarm rate was observed when critical letters occupied the same within-word relative position (left or right within the word) in the probe words as in the target word. In Experiment 2 (subject were ten undergraduates and graduates), spaces adjacent to probe words were replaced by randomly chosen hiragana letters (e.g. [symbol: see text]), because spaces are not used to separate words in regular Japanese sentences. In addition to the effect of within-word relative position as in Experiment 1, the effect of between-word relative position (left or right across the probe words) was observed. These results suggest that information about within-word relative position of a letter is used in word recognition process. The effect of within-word relative position was explained by a connectionist model of word recognition.

Brain Circuitry Supporting Multi-Organ Autonomic Outflow in Response to Nausea.

PubMed

Sclocco, Roberta; Kim, Jieun; Garcia, Ronald G; Sheehan, James D; Beissner, Florian; Bianchi, Anna M; Cerutti, Sergio; Kuo, Braden; Barbieri, Riccardo; Napadow, Vitaly

2016-02-01

While autonomic outflow is an important co-factor of nausea physiology, central control of this outflow is poorly understood. We evaluated sympathetic (skin conductance level) and cardiovagal (high-frequency heart rate variability) modulation, collected synchronously with functional MRI (fMRI) data during nauseogenic visual stimulation aimed to induce vection in susceptible individuals. Autonomic data guided analysis of neuroimaging data, using a stimulus-based (analysis windows set by visual stimulation protocol) and percept-based (windows set by subjects' ratings) approach. Increased sympathetic and decreased parasympathetic modulation was associated with robust and anti-correlated brain activity in response to nausea. Specifically, greater autonomic response was associated with reduced fMRI signal in brain regions such as the insula, suggesting an inhibitory relationship with premotor brainstem nuclei. Interestingly, some sympathetic/parasympathetic specificity was noted. Activity in default mode network and visual motion areas was anti-correlated with parasympathetic outflow at peak nausea. In contrast, lateral prefrontal cortical activity was anti-correlated with sympathetic outflow during recovery, soon after cessation of nauseogenic stimulation. These results suggest divergent central autonomic control for sympathetic and parasympathetic response to nausea. Autonomic outflow and the central autonomic network underlying ANS response to nausea may be an important determinant of overall nausea intensity and, ultimately, a potential therapeutic target. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An intelligent algorithm for autonomous scientific sampling with the VALKYRIE cryobot

NASA Astrophysics Data System (ADS)

Clark, Evan B.; Bramall, Nathan E.; Christner, Brent; Flesher, Chris; Harman, John; Hogan, Bart; Lavender, Heather; Lelievre, Scott; Moor, Joshua; Siegel, Vickie

2018-07-01

The development of algorithms for agile science and autonomous exploration has been pursued in contexts ranging from spacecraft to planetary rovers to unmanned aerial vehicles to autonomous underwater vehicles. In situations where time, mission resources and communications are limited and the future state of the operating environment is unknown, the capability of a vehicle to dynamically respond to changing circumstances without human guidance can substantially improve science return. Such capabilities are difficult to achieve in practice, however, because they require intelligent reasoning to utilize limited resources in an inherently uncertain environment. Here we discuss the development, characterization and field performance of two algorithms for autonomously collecting water samples on VALKYRIE (Very deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice Explorer), a glacier-penetrating cryobot deployed to the Matanuska Glacier, Alaska (Mission Control location: 61°42'09.3''N 147°37'23.2''W). We show performance on par with human performance across a wide range of mission morphologies using simulated mission data, and demonstrate the effectiveness of the algorithms at autonomously collecting samples with high relative cell concentration during field operation. The development of such algorithms will help enable autonomous science operations in environments where constant real-time human supervision is impractical, such as penetration of ice sheets on Earth and high-priority planetary science targets like Europa.

Autonomous Surface Sample Acquisition for Planetary and Lunar Exploration

NASA Astrophysics Data System (ADS)

Barnes, D. P.

2007-08-01

Surface science sample acquisition is a critical activity within any planetary and lunar exploration mission, and our research is focused upon the design, implementation, experimentation and demonstration of an onboard autonomous surface sample acquisition capability for a rover equipped with a robotic arm upon which are mounted appropriate science instruments. Images captured by a rover stereo camera system can be processed using shape from stereo methods and a digital elevation model (DEM) generated. We have developed a terrain feature identification algorithm that can determine autonomously from DEM data suitable regions for instrument placement and/or surface sample acquisition. Once identified, surface normal data can be generated autonomously which are then used to calculate an arm trajectory for instrument placement and sample acquisition. Once an instrument placement and sample acquisition trajectory has been calculated, a collision detection algorithm is required to ensure the safe operation of the arm during sample acquisition.We have developed a novel adaptive 'bounding spheres' approach to this problem. Once potential science targets have been identified, and these are within the reach of the arm and will not cause any undesired collision, then the 'cost' of executing the sample acquisition activity is required. Such information which includes power expenditure and duration can be used to select the 'best' target from a set of potential targets. We have developed a science sample acquisition resource requirements calculation that utilises differential inverse kinematics methods to yield a high fidelity result, thus improving upon simple 1st order approximations. To test our algorithms a new Planetary Analogue Terrain (PAT) Laboratory has been created that has a terrain region composed of Mars Soil Simulant-D from DLR Germany, and rocks that have been fully characterised in the laboratory. These have been donated by the UK Planetary Analogue Field Study network, and constitute the science targets for our autonomous sample acquisition work. Our PAT Lab. terrain has been designed to support our new rover chassis which is based upon the ExoMars rover Concept-E mechanics which were investigated during the ESA ExoMars Phase A study. The rover has 6 wheel drives, 6 wheels steering, and a 6 wheel walking capability. Mounted on the rover chassis is the UWA robotic arm and mast. We have designed and built a PanCam system complete with a computer controlled pan and tilt mechanism. The UWA PanCam is based upon the ExoMars PanCam (Phase A study) and hence supports two Wide Angle Cameras (WAC - 64 degree FOV), and a High Resolution Camera (HRC - 5 degree FOV). WAC separation is 500 mm. Software has been developed to capture images which form the data input into our on-board autonomous surface sample acquisition algorithms.

Family 46 Carbohydrate-binding Modules Contribute to the Enzymatic Hydrolysis of Xyloglucan and β-1,3-1,4-Glucans through Distinct Mechanisms.

PubMed

Venditto, Immacolata; Najmudin, Shabir; Luís, Ana S; Ferreira, Luís M A; Sakka, Kazuo; Knox, J Paul; Gilbert, Harry J; Fontes, Carlos M G A

2015-04-24

Structural carbohydrates comprise an extraordinary source of energy that remains poorly utilized by the biofuel sector as enzymes have restricted access to their substrates within the intricacy of plant cell walls. Carbohydrate active enzymes (CAZYmes) that target recalcitrant polysaccharides are modular enzymes containing noncatalytic carbohydrate-binding modules (CBMs) that direct enzymes to their cognate substrate, thus potentiating catalysis. In general, CBMs are functionally and structurally autonomous from their associated catalytic domains from which they are separated through flexible linker sequences. Here, we show that a C-terminal CBM46 derived from BhCel5B, a Bacillus halodurans endoglucanase, does not interact with β-glucans independently but, uniquely, acts cooperatively with the catalytic domain of the enzyme in substrate recognition. The structure of BhCBM46 revealed a β-sandwich fold that abuts onto the region of the substrate binding cleft upstream of the active site. BhCBM46 as a discrete entity is unable to bind to β-glucans. Removal of BhCBM46 from BhCel5B, however, abrogates binding to β-1,3-1,4-glucans while substantially decreasing the affinity for decorated β-1,4-glucan homopolymers such as xyloglucan. The CBM46 was shown to contribute to xyloglucan hydrolysis only in the context of intact plant cell walls, but it potentiates enzymatic activity against purified β-1,3-1,4-glucans in solution or within the cell wall. This report reveals the mechanism by which a CBM can promote enzyme activity through direct interaction with the substrate or by targeting regions of the plant cell wall where the target glucan is abundant. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Impaired social response reversal. A case of 'acquired sociopathy'.

PubMed

Blair, R J; Cipolotti, L

2000-06-01

In this study, we report a patient (J.S.) who, following trauma to the right frontal region, including the orbitofrontal cortex, presented with 'acquired sociopathy'. His behaviour was notably aberrant and marked by high levels of aggression and a callous disregard for others. A series of experimental investigations were conducted to address the cognitive dysfunction that might underpin his profoundly aberrant behaviour. His performance was contrasted with that of a second patient (C.L.A.), who also presented with a grave dysexecutive syndrome but no socially aberrant behaviour, and five inmates of Wormwood Scrubs prison with developmental psychopathy. While J.S. showed no reversal learning impairment, he presented with severe difficulty in emotional expression recognition, autonomic responding and social cognition. Unlike the comparison populations, J.S. showed impairment in: the recognition of, and autonomic responding to, angry and disgusted expressions; attributing the emotions of fear, anger and embarrassment to story protagonists; and the identification of violations of social behaviour. The findings are discussed with reference to models regarding the role of the orbitofrontal cortex in the control of aggression. It is suggested that J.S.'s impairment is due to a reduced ability to generate expectations of others' negative emotional reactions, in particular anger. In healthy individuals, these representations act to suppress behaviour that is inappropriate in specific social contexts. Moreover, it is proposed that the orbitofrontal cortex may be implicated specifically either in the generation of these expectations or the use of these expectations to suppress inappropriate behaviour.

Multimode and multistate ladder oscillator and frequency recognition device

NASA Technical Reports Server (NTRS)

Aumann, Herbert M. (Inventor)

1976-01-01

A ladder oscillator composed of capacitive and inductive impedances connected together to form a ladder network which has a chosen number N oscillation modes at N different frequencies. Each oscillation mode is characterized by a unique standing wave voltage pattern along the nodes of the ladder oscillator, with the mode in which the ladder oscillator is oscillating being determinable from the amplitudes or phase of the oscillations at the nodes. A logic circuit may be connected to the nodes of the oscillator to compare the phases of selected nodes and thereby determine which mode the oscillator is oscillating in. A ladder oscillator composed of passive capacitive and inductive impedances can be utilized as a frequency recognition device, since the passive ladder oscillator will display the characteristic standing wave patterns if an input signal impressed upon the ladder oscillator is close to one of the mode frequencies of the oscillator. A CL ladder oscillator having series capacitive impedances and shunt inductive impedances can exhibit sustained and autonomous oscillations if active nonlinear devices are connected in parallel with the shunt inductive impedances. The active CL ladder oscillator can be synchronized to input frequencies impressed upon the oscillator, and will continue to oscillate after the input signal has been removed at a mode frequency which is, in general, nearest to the input signal frequency. Autonomous oscillations may also be obtained as desired from the active CL ladder oscillator at the mode frequencies.

Braking distance algorithm for autonomous cars using road surface recognition

NASA Astrophysics Data System (ADS)

Kavitha, C.; Ashok, B.; Nanthagopal, K.; Desai, Rohan; Rastogi, Nisha; Shetty, Siddhanth

2017-11-01

India is yet to accept semi/fully - autonomous cars and one of the reasons, was loss of control on bad roads. For a better handling on these roads we require advanced braking and that can be done by adapting electronics into the conventional type of braking. In Recent years, the automation in braking system led us to various benefits like traction control system, anti-lock braking system etc. This research work describes and experiments the method for recognizing road surface profile and calculating braking distance. An ultra-sonic surface recognition sensor, mounted underneath the car will send a high frequency wave on to the road surface, which is received by a receiver with in the sensor, it calculates the time taken for the wave to rebound and thus calculates the distance from the point where sensor is mounted. A displacement graph will be plotted based on the output of the sensor. A relationship can be derived between the displacement plot and roughness index through which the friction coefficient can be derived in Matlab for continuous calculation throughout the distance travelled. Since it is a non-contact type of profiling, it is non-destructive. The friction coefficient values received in real-time is used to calculate optimum braking distance. This system, when installed on normal cars can also be used to create a database of road surfaces, especially in cities, which can be shared with other cars. This will help in navigation as well as making the cars more efficient.

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

A multimodal interface for real-time soldier-robot teaming

NASA Astrophysics Data System (ADS)

Barber, Daniel J.; Howard, Thomas M.; Walter, Matthew R.

2016-05-01

Recent research and advances in robotics have led to the development of novel platforms leveraging new sensing capabilities for semantic navigation. As these systems becoming increasingly more robust, they support highly complex commands beyond direct teleoperation and waypoint finding facilitating a transition away from robots as tools to robots as teammates. Supporting future Soldier-Robot teaming requires communication capabilities on par with human-human teams for successful integration of robots. Therefore, as robots increase in functionality, it is equally important that the interface between the Soldier and robot advances as well. Multimodal communication (MMC) enables human-robot teaming through redundancy and levels of communications more robust than single mode interaction. Commercial-off-the-shelf (COTS) technologies released in recent years for smart-phones and gaming provide tools for the creation of portable interfaces incorporating MMC through the use of speech, gestures, and visual displays. However, for multimodal interfaces to be successfully used in the military domain, they must be able to classify speech, gestures, and process natural language in real-time with high accuracy. For the present study, a prototype multimodal interface supporting real-time interactions with an autonomous robot was developed. This device integrated COTS Automated Speech Recognition (ASR), a custom gesture recognition glove, and natural language understanding on a tablet. This paper presents performance results (e.g. response times, accuracy) of the integrated device when commanding an autonomous robot to perform reconnaissance and surveillance activities in an unknown outdoor environment.

Rapid extraction of gist from visual text and its influence on word recognition.

PubMed

Asano, Michiko; Yokosawa, Kazuhiko

2011-01-01

Two experiments explored rapid extraction of gist from a visual text and its influence on word recognition. In both, a short text (sentence) containing a target word was presented for 200 ms and was followed by a target recognition task. Results showed that participants recognized contextually anomalous word targets less frequently than contextually consistent counterparts (Experiment 1). This context effect was obtained when sentences contained the same semantic content but with disrupted syntactic structure (Experiment 2). Results demonstrate that words in a briefly presented visual sentence are processed in parallel and that rapid extraction of sentence gist relies on a primitive representation of sentence context (termed protocontext) that is semantically activated by the simultaneous presentation of multiple words (i.e., a sentence) before syntactic processing.

Antibody-Unfolding and Metastable-State Binding in Force Spectroscopy and Recognition Imaging

PubMed Central

Kaur, Parminder; Qiang-Fu; Fuhrmann, Alexander; Ros, Robert; Kutner, Linda Obenauer; Schneeweis, Lumelle A.; Navoa, Ryman; Steger, Kirby; Xie, Lei; Yonan, Christopher; Abraham, Ralph; Grace, Michael J.; Lindsay, Stuart

2011-01-01

Force spectroscopy and recognition imaging are important techniques for characterizing and mapping molecular interactions. In both cases, an antibody is pulled away from its target in times that are much less than the normal residence time of the antibody on its target. The distribution of pulling lengths in force spectroscopy shows the development of additional peaks at high loading rates, indicating that part of the antibody frequently unfolds. This propensity to unfold is reversible, indicating that exposure to high loading rates induces a structural transition to a metastable state. Weakened interactions of the antibody in this metastable state could account for reduced specificity in recognition imaging where the loading rates are always high. The much weaker interaction between the partially unfolded antibody and target, while still specific (as shown by control experiments), results in unbinding on millisecond timescales, giving rise to rapid switching noise in the recognition images. At the lower loading rates used in force spectroscopy, we still find discrepancies between the binding kinetics determined by force spectroscopy and those determined by surface plasmon resonance—possibly a consequence of the short tethers used in recognition imaging. Recognition imaging is nonetheless a powerful tool for interpreting complex atomic force microscopy images, so long as specificity is calibrated in situ, and not inferred from equilibrium binding kinetics. PMID:21190677

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

The Other in Me: Interpersonal Multisensory Stimulation Changes the Mental Representation of the Self

PubMed Central

Tajadura-Jiménez, Ana; Grehl, Stephanie; Tsakiris, Manos

2012-01-01

Background Recent studies have shown that the well-known effect of multisensory stimulation on body-awareness can be extended to self-recognition. Seeing someone else’s face being touched at the same time as one’s own face elicits changes in the mental representation of the self-face. We sought to further elucidate the underlying mechanisms and the effects of interpersonal multisensory stimulation (IMS) on the mental representation of the self and others. Methodology/Principal Findings Participants saw an unfamiliar face being touched synchronously or asynchronously with their own face, as if they were looking in the mirror. Following synchronous, but not asynchronous, IMS, participants assimilated features of the other’s face in the mental representation of their own face as evidenced by the change in the point of subjective equality for morphed pictures of the two faces. Interestingly, synchronous IMS resulted in a unidirectional change in the self-other distinction, affecting recognition of one’s own face, but not recognition of the other’s face. The participants’ autonomic responses to objects approaching the other’s face were higher following synchronous than asynchronous IMS, but this increase was not specific to the pattern of IMS in interaction with the viewed object. Finally, synchronous, as compared to asynchronous, IMS resulted in significant differences in participants’ ratings of their experience, but unlike other bodily illusions, positive changes in subjective experience were related to the perceived physical similarity between the two faces, and not to identification. Conclusions/Significance Synchronous IMS produces quantifiable changes in the mental representations of one’s face, as measured behaviorally. Changes in autonomic responses and in the subjective experience of self-identification were broadly consistent with patterns observed in other bodily illusions, but less robust. Overall, shared multisensory experiences between self and other can change the mental representation of one’s identity, and the perceived similarity of others relative to one’s self. PMID:22866177

Autonomous Commanding of the WIRE Spacecraft

NASA Technical Reports Server (NTRS)

Prior, Mike; Walyus, Keith; Saylor, Rick

1999-01-01

This paper presents the end-to-end design architecture for an autonomous commanding capability to be used on the Wide Field Infrared Explorer (WIRE) mission for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented an autonomous command loading capability. This capability allows completely unattended operations over a typical two- day weekend period. The key factors driving design and implementation of this capability were: 1) Integration with already existing ground system autonomous capabilities and systems, 2) The desire to evolve autonomous operations capabilities based upon previous SMEX operations experience 3) Integration with ground station operations - both autonomous and man-tended, 4) Low cost and quick implementation, and 5) End-to-end system robustness. A trade-off study was performed to examine these factors in light of the low-cost, higher-risk SMEX mission philosophy. The study concluded that a STOL (Spacecraft Test and Operations Language) based script, highly integrated with other scripts used to perform autonomous operations, was best suited given the budget and goals of the mission. Each of these factors is discussed to provide an overview of the autonomous operations capabilities implemented for the mission. The capabilities implemented on the WIRE mission are an example of a low-cost, robust, and efficient method for autonomous command loading when implemented with other autonomous features of the ground system. They can be used as a design and implementation template by other small satellite missions interested in evolving toward autonomous and lower cost operations.

Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Mount, Frances; Carreon, Patricia; Torney, Susan E.

2001-01-01

The Engineering and Mission Operations Directorates at NASA Johnson Space Center are combining laboratories and expertise to establish the Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations. This is a testbed for human centered design, development and evaluation of intelligent autonomous and assistant systems that will be needed for human exploration and development of space. This project will improve human-centered analysis, design and evaluation methods for developing intelligent software. This software will support human-machine cognitive and collaborative activities in future interplanetary work environments where distributed computer and human agents cooperate. We are developing and evaluating prototype intelligent systems for distributed multi-agent mixed-initiative operations. The primary target domain is control of life support systems in a planetary base. Technical approaches will be evaluated for use during extended manned tests in the target domain, the Bioregenerative Advanced Life Support Systems Test Complex (BIO-Plex). A spinoff target domain is the International Space Station (ISS) Mission Control Center (MCC). Prodl}cts of this project include human-centered intelligent software technology, innovative human interface designs, and human-centered software development processes, methods and products. The testbed uses adjustable autonomy software and life support systems simulation models from the Adjustable Autonomy Testbed, to represent operations on the remote planet. Ground operations prototypes and concepts will be evaluated in the Exploration Planning and Operations Center (ExPOC) and Jupiter Facility.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Design of an algorithm for autonomous docking with a freely tumbling target

NASA Astrophysics Data System (ADS)

Nolet, Simon; Kong, Edmund; Miller, David W.

2005-05-01

For complex unmanned docking missions, limited communication bandwidth and delays do not allow ground operators to have immediate access to all real-time state information and hence prevent them from playing an active role in the control loop. Advanced control algorithms are needed to make mission critical decisions to ensure safety of both spacecraft during close proximity maneuvers. This is especially true when unexpected contingencies occur. These algorithms will enable multiple space missions, including servicing of damaged spacecraft and missions to Mars. A key characteristic of spacecraft servicing missions is that the target spacecraft is likely to be freely tumbling due to various mechanical failures or fuel depletion. Very few technical references in the literature can be found on autonomous docking with a freely tumbling target and very few such maneuvers have been attempted. The MIT Space Systems Laboratory (SSL) is currently performing research on the subject. The objective of this research is to develop a control architecture that will enable safe and fuel-efficient docking of a thruster based spacecraft with a freely tumbling target in presence of obstacles and contingencies. The approach is to identify, select and implement state estimation, fault detection, isolation and recovery, optimal path planning and thruster management algorithms that, once properly integrated, can accomplish such a maneuver autonomously. Simulations and demonstrations on the SPHERES testbed developed by the MIT SSL will be executed to assess the performance of different combinations of algorithms. To date, experiments have been carried out at the MIT SSL 2-D Laboratory and at the NASA Marshall Space Flight Center (MSFC) flat floor.

Fuzzy Behavior Modulation with Threshold Activation for Autonomous Vehicle Navigation

NASA Technical Reports Server (NTRS)

Tunstel, Edward

2000-01-01

This paper describes fuzzy logic techniques used in a hierarchical behavior-based architecture for robot navigation. An architectural feature for threshold activation of fuzzy-behaviors is emphasized, which is potentially useful for tuning navigation performance in real world applications. The target application is autonomous local navigation of a small planetary rover. Threshold activation of low-level navigation behaviors is the primary focus. A preliminary assessment of its impact on local navigation performance is provided based on computer simulations.

An AI Approach to Ground Station Autonomy for Deep Space Communications

NASA Technical Reports Server (NTRS)

Fisher, Forest; Estlin, Tara; Mutz, Darren; Paal, Leslie; Law, Emily; Stockett, Mike; Golshan, Nasser; Chien, Steve

1998-01-01

This paper describes an architecture for an autonomous deep space tracking station (DS-T). The architecture targets fully automated routine operations encompassing scheduling and resource allocation, antenna and receiver predict generation. track procedure generation from service requests, and closed loop control and error recovery for the station subsystems. This architecture has been validated by the construction of a prototype DS-T station, which has performed a series of demonstrations of autonomous ground station control for downlink services with NASA's Mars Global Surveyor (MGS).

Autonomous Instrument Placement for Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Leger, P. Chris; Maimone, Mark

2009-01-01

Autonomous Instrument Placement (AutoPlace) is onboard software that enables a Mars Exploration Rover to act autonomously in using its manipulator to place scientific instruments on or near designated rock and soil targets. Prior to the development of AutoPlace, it was necessary for human operators on Earth to plan every motion of the manipulator arm in a time-consuming process that included downlinking of images from the rover, analysis of images and creation of commands, and uplinking of commands to the rover. AutoPlace incorporates image analysis and planning algorithms into the onboard rover software, eliminating the need for the downlink/uplink command cycle. Many of these algorithms are derived from the existing groundbased image analysis and planning algorithms, with modifications and augmentations for onboard use.

Small Body Exploration Technologies as Precursors for Interstellar Robotics

NASA Astrophysics Data System (ADS)

Noble, R. J.; Sykes, M. V.

The scientific activities undertaken to explore our Solar System will be very similar to those required someday at other stars. The systematic exploration of primitive small bodies throughout our Solar System requires new technologies for autonomous robotic spacecraft. These diverse celestial bodies contain clues to the early stages of the Solar System's evolution, as well as information about the origin and transport of water-rich and organic material, the essential building blocks for life. They will be among the first objects studied at distant star systems. The technologies developed to address small body and outer planet exploration will form much of the technical basis for designing interstellar robotic explorers. The Small Bodies Assessment Group, which reports to NASA, initiated a Technology Forum in 2011 that brought together scientists and technologists to discuss the needs and opportunities for small body robotic exploration in the Solar System. Presentations and discussions occurred in the areas of mission and spacecraft design, electric power, propulsion, avionics, communications, autonomous navigation, remote sensing and surface instruments, sampling, intelligent event recognition, and command and sequencing software. In this paper, the major technology themes from the Technology Forum are reviewed, and suggestions are made for developments that will have the largest impact on realizing autonomous robotic vehicles capable of exploring other star systems.

Small Body Exploration Technologies as Precursors for Interstellar Robotics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noble, Robert; /SLAC; Sykes, Mark V.

The scientific activities undertaken to explore our Solar System will be the same as required someday at other stars. The systematic exploration of primitive small bodies throughout our Solar System requires new technologies for autonomous robotic spacecraft. These diverse celestial bodies contain clues to the early stages of the Solar System's evolution as well as information about the origin and transport of water-rich and organic material, the essential building blocks for life. They will be among the first objects studied at distant star systems. The technologies developed to address small body and outer planet exploration will form much of themore » technical basis for designing interstellar robotic explorers. The Small Bodies Assessment Group, which reports to NASA, initiated a Technology Forum in 2011 that brought together scientists and technologists to discuss the needs and opportunities for small body robotic exploration in the Solar System. Presentations and discussions occurred in the areas of mission and spacecraft design, electric power, propulsion, avionics, communications, autonomous navigation, remote sensing and surface instruments, sampling, intelligent event recognition, and command and sequencing software. In this paper, the major technology themes from the Technology Forum are reviewed, and suggestions are made for developments that will have the largest impact on realizing autonomous robotic vehicles capable of exploring other star systems.« less

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

mTOR Signaling Confers Resistance to Targeted Cancer Drugs.

PubMed

Guri, Yakir; Hall, Michael N

2016-11-01

Cancer is a complex disease and a leading cause of death worldwide. Extensive research over decades has led to the development of therapies that target cancer-specific signaling pathways. However, the clinical benefits of such drugs are at best transient due to tumors displaying intrinsic or adaptive resistance. The underlying compensatory pathways that allow cancer cells to circumvent a drug blockade are poorly understood. We review here recent studies suggesting that mammalian TOR (mTOR) signaling is a major compensatory pathway conferring resistance to many cancer drugs. mTOR-mediated resistance can be cell-autonomous or non-cell-autonomous. These findings suggest that mTOR signaling should be monitored routinely in tumors and that an mTOR inhibitor should be considered as a co-therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Voice gender and the segregation of competing talkers: Perceptual learning in cochlear implant simulations

PubMed Central

Sullivan, Jessica R.; Assmann, Peter F.; Hossain, Shaikat; Schafer, Erin C.

2017-01-01

Two experiments explored the role of differences in voice gender in the recognition of speech masked by a competing talker in cochlear implant simulations. Experiment 1 confirmed that listeners with normal hearing receive little benefit from differences in voice gender between a target and masker sentence in four- and eight-channel simulations, consistent with previous findings that cochlear implants deliver an impoverished representation of the cues for voice gender. However, gender differences led to small but significant improvements in word recognition with 16 and 32 channels. Experiment 2 assessed the benefits of perceptual training on the use of voice gender cues in an eight-channel simulation. Listeners were assigned to one of four groups: (1) word recognition training with target and masker differing in gender; (2) word recognition training with same-gender target and masker; (3) gender recognition training; or (4) control with no training. Significant improvements in word recognition were observed from pre- to post-test sessions for all three training groups compared to the control group. These improvements were maintained at the late session (one week following the last training session) for all three groups. There was an overall improvement in masked word recognition performance provided by gender mismatch following training, but the amount of benefit did not differ as a function of the type of training. The training effects observed here are consistent with a form of rapid perceptual learning that contributes to the segregation of competing voices but does not specifically enhance the benefits provided by voice gender cues. PMID:28372046

Supervised autonomous robotic soft tissue surgery.

PubMed

Shademan, Azad; Decker, Ryan S; Opfermann, Justin D; Leonard, Simon; Krieger, Axel; Kim, Peter C W

2016-05-04

The current paradigm of robot-assisted surgeries (RASs) depends entirely on an individual surgeon's manual capability. Autonomous robotic surgery-removing the surgeon's hands-promises enhanced efficacy, safety, and improved access to optimized surgical techniques. Surgeries involving soft tissue have not been performed autonomously because of technological limitations, including lack of vision systems that can distinguish and track the target tissues in dynamic surgical environments and lack of intelligent algorithms that can execute complex surgical tasks. We demonstrate in vivo supervised autonomous soft tissue surgery in an open surgical setting, enabled by a plenoptic three-dimensional and near-infrared fluorescent (NIRF) imaging system and an autonomous suturing algorithm. Inspired by the best human surgical practices, a computer program generates a plan to complete complex surgical tasks on deformable soft tissue, such as suturing and intestinal anastomosis. We compared metrics of anastomosis-including the consistency of suturing informed by the average suture spacing, the pressure at which the anastomosis leaked, the number of mistakes that required removing the needle from the tissue, completion time, and lumen reduction in intestinal anastomoses-between our supervised autonomous system, manual laparoscopic surgery, and clinically used RAS approaches. Despite dynamic scene changes and tissue movement during surgery, we demonstrate that the outcome of supervised autonomous procedures is superior to surgery performed by expert surgeons and RAS techniques in ex vivo porcine tissues and in living pigs. These results demonstrate the potential for autonomous robots to improve the efficacy, consistency, functional outcome, and accessibility of surgical techniques. Copyright © 2016, American Association for the Advancement of Science.

Virtual reality method to analyze visual recognition in mice.

PubMed

Young, Brent Kevin; Brennan, Jayden Nicole; Wang, Ping; Tian, Ning

2018-01-01

Behavioral tests have been extensively used to measure the visual function of mice. To determine how precisely mice perceive certain visual cues, it is necessary to have a quantifiable measurement of their behavioral responses. Recently, virtual reality tests have been utilized for a variety of purposes, from analyzing hippocampal cell functionality to identifying visual acuity. Despite the widespread use of these tests, the training requirement for the recognition of a variety of different visual targets, and the performance of the behavioral tests has not been thoroughly characterized. We have developed a virtual reality behavior testing approach that can essay a variety of different aspects of visual perception, including color/luminance and motion detection. When tested for the ability to detect a color/luminance target or a moving target, mice were able to discern the designated target after 9 days of continuous training. However, the quality of their performance is significantly affected by the complexity of the visual target, and their ability to navigate on a spherical treadmill. Importantly, mice retained memory of their visual recognition for at least three weeks after the end of their behavioral training.

Programmable RNA Cleavage and Recognition by a Natural CRISPR-Cas9 System from Neisseria meningitidis.

PubMed

Rousseau, Beth A; Hou, Zhonggang; Gramelspacher, Max J; Zhang, Yan

2018-03-01

The microbial CRISPR systems enable adaptive defense against mobile elements and also provide formidable tools for genome engineering. The Cas9 proteins are type II CRISPR-associated, RNA-guided DNA endonucleases that identify double-stranded DNA targets by sequence complementarity and protospacer adjacent motif (PAM) recognition. Here we report that the type II-C CRISPR-Cas9 from Neisseria meningitidis (Nme) is capable of programmable, RNA-guided, site-specific cleavage and recognition of single-stranded RNA targets and that this ribonuclease activity is independent of the PAM sequence. We define the mechanistic feature and specificity constraint for RNA cleavage by NmeCas9 and also show that nuclease null dNmeCas9 binds to RNA target complementary to CRISPR RNA. Finally, we demonstrate that NmeCas9-catalyzed RNA cleavage can be blocked by three families of type II-C anti-CRISPR proteins. These results fundamentally expand the targeting capacities of CRISPR-Cas9 and highlight the potential utility of NmeCas9 as a single platform to target both RNA and DNA. Copyright © 2018 Elsevier Inc. All rights reserved.

Experiences with a Barista Robot, FusionBot

NASA Astrophysics Data System (ADS)

Limbu, Dilip Kumar; Tan, Yeow Kee; Wong, Chern Yuen; Jiang, Ridong; Wu, Hengxin; Li, Liyuan; Kah, Eng Hoe; Yu, Xinguo; Li, Dong; Li, Haizhou

In this paper, we describe the implemented service robot, called FusionBot. The goal of this research is to explore and demonstrate the utility of an interactive service robot in a smart home environment, thereby improving the quality of human life. The robot has four main features: 1) speech recognition, 2) object recognition, 3) object grabbing and fetching and 4) communication with a smart coffee machine. Its software architecture employs a multimodal dialogue system that integrates different components, including spoken dialog system, vision understanding, navigation and smart device gateway. In the experiments conducted during the TechFest 2008 event, the FusionBot successfully demonstrated that it could autonomously serve coffee to visitors on their request. Preliminary survey results indicate that the robot has potential to not only aid in the general robotics but also contribute towards the long term goal of intelligent service robotics in smart home environment.

Spatial, Hysteretic, and Adaptive Host-Guest Chemistry in a Metal-Organic Framework with Open Watson-Crick Sites.

PubMed

Cai, Hong; Li, Mian; Lin, Xiao-Rong; Chen, Wei; Chen, Guang-Hui; Huang, Xiao-Chun; Li, Dan

2015-09-01

Biological and artificial molecules and assemblies capable of supramolecular recognition, especially those with nucleobase pairing, usually rely on autonomous or collective binding to function. Advanced site-specific recognition takes advantage of cooperative spatial effects, as in local folding in protein-DNA binding. Herein, we report a new nucleobase-tagged metal-organic framework (MOF), namely ZnBTCA (BTC=benzene-1,3,5-tricarboxyl, A=adenine), in which the exposed Watson-Crick faces of adenine residues are immobilized periodically on the interior crystalline surface. Systematic control experiments demonstrated the cooperation of the open Watson-Crick sites and spatial effects within the nanopores, and thermodynamic and kinetic studies revealed a hysteretic host-guest interaction attributed to mild chemisorption. We further exploited this behavior for adenine-thymine binding within the constrained pores, and a globally adaptive response of the MOF host was observed. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

Influence of Emotional Facial Expressions on 3-5-Year-Olds' Face Recognition

ERIC Educational Resources Information Center

Freitag, Claudia; Schwarzer, Gudrun

2011-01-01

Three experiments examined 3- and 5-year-olds' recognition of faces in constant and varied emotional expressions. Children were asked to identify repeatedly presented target faces, distinguishing them from distractor faces, during an immediate recognition test and during delayed assessments after 10 min and one week. Emotional facial expression…

Evaluation of target acquisition difficulty using recognition distance to measure required retinal area

NASA Astrophysics Data System (ADS)

Nilsson, Thomy H.

2001-09-01

The psychophysical method of limits was used to measure the distance at which observers could distinguish military vehicles photographed in natural landscapes. Obtained from the TNO-TM Search_2 dataset, these pictures either were rear-projected 35-mm slides or were presented on a computer monitor. Based on the rationale that more difficult vehicle targets would require more visual pathways for recognition, difficult of acquisition was defined in terms of the relative retinal area required for recognition. Relative retinal area was derived from the inverse square of the recognition distance of a particular vehicle relative to the distance of the vehicle that could be seen furthest away. Results are compared with data on the time required to find the vehicles in these pictures. These comparison indicate recognition distance thresholds can be a suitable means of defining standards for the effectiveness of vital graphic information; and the two methods are complementary with respect to distinguishing different degrees of acquisition difficulty, and together may provide a means to measure the total information processing required for recognition.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Redox polymer and probe DNA tethered to gold electrodes for enzyme-amplified amperometric detection of DNA hybridization.

PubMed

Kavanagh, Paul; Leech, Dónal

2006-04-15

The detection of nucleic acids based upon recognition surfaces formed by co-immobilization of a redox polymer mediator and DNA probe sequences on gold electrodes is described. The recognition surface consists of a redox polymer, [Os(2,2'-bipyridine)2(polyvinylimidazole)(10)Cl](+/2+), and a model single DNA strand cross-linked and tethered to a gold electrode via an anchoring self-assembled monolayer (SAM) of cysteamine. Hybridization between the immobilized probe DNA of the recognition surface and a biotin-conjugated target DNA sequence (designed from the ssrA gene of Listeria monocytogenes), followed by addition of an enzyme (glucose oxidase)-avidin conjugate, results in electrical contact between the enzyme and the mediating redox polymer. In the presence of glucose, the current generated due to the catalytic oxidation of glucose to gluconolactone is measured, and a response is obtained that is binding-dependent. The tethering of the probe DNA and redox polymer to the SAM improves the stability of the surface to assay conditions of rigorous washing and high salt concentration (1 M). These conditions eliminate nonspecific interaction of both the target DNA and the enzyme-avidin conjugate with the recognition surfaces. The sensor response increases linearly with increasing concentration of target DNA in the range of 1 x 10(-9) to 2 x 10(-6) M. The detection limit is approximately 1.4 fmol, (corresponding to 0.2 nM of target DNA). Regeneration of the recognition surface is possible by treatment with 0.25 M NaOH solution. After rehybridization of the regenerated surface with the target DNA sequence, >95% of the current is recovered, indicating that the redox polymer and probe DNA are strongly bound to the surface. These results demonstrate the utility of the proposed approach.

Key features for ATA / ATR database design in missile systems

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2017-05-01

Automatic target acquisition (ATA) and automatic target recognition (ATR) are two vital tasks for missile systems, and having a robust detection and recognition algorithm is crucial for overall system performance. In order to have a robust target detection and recognition algorithm, an extensive image database is required. Automatic target recognition algorithms use the database of images in training and testing steps of algorithm. This directly affects the recognition performance, since the training accuracy is driven by the quality of the image database. In addition, the performance of an automatic target detection algorithm can be measured effectively by using an image database. There are two main ways for designing an ATA / ATR database. The first and easy way is by using a scene generator. A scene generator can model the objects by considering its material information, the atmospheric conditions, detector type and the territory. Designing image database by using a scene generator is inexpensive and it allows creating many different scenarios quickly and easily. However the major drawback of using a scene generator is its low fidelity, since the images are created virtually. The second and difficult way is designing it using real-world images. Designing image database with real-world images is a lot more costly and time consuming; however it offers high fidelity, which is critical for missile algorithms. In this paper, critical concepts in ATA / ATR database design with real-world images are discussed. Each concept is discussed in the perspective of ATA and ATR separately. For the implementation stage, some possible solutions and trade-offs for creating the database are proposed, and all proposed approaches are compared to each other with regards to their pros and cons.

Model-based vision using geometric hashing

NASA Astrophysics Data System (ADS)

Akerman, Alexander, III; Patton, Ronald

1991-04-01

The Geometric Hashing technique developed by the NYU Courant Institute has been applied to various automatic target recognition applications. In particular, I-MATH has extended the hashing algorithm to perform automatic target recognition ofsynthetic aperture radar (SAR) imagery. For this application, the hashing is performed upon the geometric locations of dominant scatterers. In addition to being a robust model-based matching algorithm -- invariant under translation, scale, and 3D rotations of the target -- hashing is of particular utility because it can still perform effective matching when the target is partially obscured. Moreover, hashing is very amenable to a SIMD parallel processing architecture, and thus potentially realtime implementable.

Testing Saliency Parameters for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Pandya, Sagar

2012-01-01

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

DOEpatents

Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

2009-06-02

An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

Understanding Emotions in Frontotemporal Dementia: The Explicit and Implicit Emotional Cue Mismatch.

PubMed

Balconi, Michela; Cotelli, Maria; Brambilla, Michela; Manenti, Rosa; Cosseddu, Maura; Premi, Enrico; Gasparotti, Roberto; Zanetti, Orazio; Padovani, Alessandro; Borroni, Barbara

2015-01-01

Previous studies have reported significant deficits in emotion recognition among individuals along the frontotemporal dementia (FTD) spectrum. The basis of emotional impairment is still poorly understood and explicit (emotion appraisal) and implicit (autonomic system activity) responses have not been carefully evaluated. We investigated explicit evaluation of emotions by testing valence and arousal using self-report measures and we also assessed automatic responses to emotional cues, using autonomic measures (skin conductance response and heart rate). 16 behavioral variant FTD and 12 agrammatic variants of primary progressive aphasia patients were included. The performance of these patients was compared to a group of 14 patients with Alzheimer's disease and 20 healthy controls. Each subject was required to observe and evaluate affective pictures while autonomic parameters were recorded. FTD patients preserved a functional general competency in terms of valence (correct positive versus negative attribution) and arousal (correct dichotomy between high versus low arousal category) distinction. These patients showed significant changes in autonomic implicit response compared to the other groups. The mismatch between explicit and implicit responsiveness to emotional cues was found both in behavioral variant FTD and in agrammatic variants of primary progressive aphasia. Emotional responsiveness was related to the severity of behavioral abnormalities as measured by the Frontal Behavioral Inventory and associated with atrophy of the left putamen. The present findings indicate that FTD patients are able to explicitly "appraise" the emotion, but they cannot implicitly "feel" the emotion. This mismatch between the two levels may help explain the general emotional behavior impairment found in these patients.

Integrated approach for automatic target recognition using a network of collaborative sensors.

PubMed

Mahalanobis, Abhijit; Van Nevel, Alan

2006-10-01

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.

Research on Radar Micro-Doppler Feature Parameter Estimation of Propeller Aircraft

NASA Astrophysics Data System (ADS)

He, Zhihua; Tao, Feixiang; Duan, Jia; Luo, Jingsheng

2018-01-01

The micro-motion modulation effect of the rotated propellers to radar echo can be a steady feature for aircraft target recognition. Thus, micro-Doppler feature parameter estimation is a key to accurate target recognition. In this paper, the radar echo of rotated propellers is modelled and simulated. Based on which, the distribution characteristics of the micro-motion modulation energy in time, frequency and time-frequency domain are analyzed. The micro-motion modulation energy produced by the scattering points of rotating propellers is accumulated using the Inverse-Radon (I-Radon) transform, which can be used to accomplish the estimation of micro-modulation parameter. Finally, it is proved that the proposed parameter estimation method is effective with measured data. The micro-motion parameters of aircraft can be used as the features of radar target recognition.

Cultural differences in gaze and emotion recognition: Americans contrast more than Chinese.

PubMed

Stanley, Jennifer Tehan; Zhang, Xin; Fung, Helene H; Isaacowitz, Derek M

2013-02-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye-tracking data suggest that, for some emotions, Americans attended more to the target faces, and they made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Self-Assembled Smart Nanocarriers for Targeted Drug Delivery.

PubMed

Cui, Wei; Li, Junbai; Decher, Gero

2016-02-10

Nanostructured drug-carrier systems promise numerous benefits for drug delivery. They can be engineered to precisely control drug-release rates or to target specific sites within the body with a specific amount of therapeutic agent. However, to achieve the best therapeutic effects, the systems should be designed for carrying the optimum amount of a drug to the desired target where it should be released at the optimum rate for a specified time. Despite numerous attempts, fulfilling all of these requirements in a synergistic way remains a huge challenge. The trend in drug delivery is consequently directed toward integrated multifunctional carrier systems, providing selective recognition in combination with sustained or triggered release. Capsules as vesicular systems enable drugs to be confined for controlled release. Furthermore, carriers modified with recognition groups can enhance the capability of encapsulated drug efficacy. Here, recent advances are reviewed regarding designing and preparing assembled capsules with targeting ligands or size controllable for selective recognition in drug delivery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cultural Differences in Gaze and Emotion Recognition: Americans Contrast More than Chinese

PubMed Central

Tehan Stanley, Jennifer; Zhang, Xin; Fung, Helene H.; Isaacowitz, Derek M.

2014-01-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye tracking data suggest that, for some emotions, Americans attended more to the target faces and made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PMID:22889414

Square tracking sensor for autonomous helicopter hover stabilization

NASA Astrophysics Data System (ADS)

Oertel, Carl-Henrik

1995-06-01

Sensors for synthetic vision are needed to extend the mission profiles of helicopters. A special task for various applications is the autonomous position hold of a helicopter above a ground fixed or moving target. As a proof of concept for a general synthetic vision solution a restricted machine vision system, which is capable of locating and tracking a special target, was developed by the Institute of Flight Mechanics of Deutsche Forschungsanstalt fur Luft- und Raumfahrt e.V. (i.e., German Aerospace Research Establishment). This sensor, which is specialized to detect and track a square, was integrated in the fly-by-wire helicopter ATTHeS (i.e., Advanced Technology Testing Helicopter System). An existing model following controller for the forward flight condition was adapted for the hover and low speed requirements of the flight vehicle. The special target, a black square with a length of one meter, was mounted on top of a car. Flight tests demonstrated the automatic stabilization of the helicopter above the moving car by synthetic vision.

Development of an autonomous video rendezvous and docking system, phase 2

NASA Technical Reports Server (NTRS)

Tietz, J. C.; Richardson, T. E.

1983-01-01

The critical elements of an autonomous video rendezvous and docking system were built and used successfully in a physical laboratory simulation. The laboratory system demonstrated that a small, inexpensive electronic package and a flight computer of modest size can analyze television images to derive guidance information for spacecraft. In the ultimate application, the system would use a docking aid consisting of three flashing lights mounted on a passive target spacecraft. Television imagery of the docking aid would be processed aboard an active chase vehicle to derive relative positions and attitudes of the two spacecraft. The demonstration system used scale models of the target spacecraft with working docking aids. A television camera mounted on a 6 degree of freedom (DOF) simulator provided imagery of the target to simulate observations from the chase vehicle. A hardware video processor extracted statistics from the imagery, from which a computer quickly computed position and attitude. Computer software known as a Kalman filter derived velocity information from position measurements.

Design and Implementation of a Collision Avoidance System for the NPS autonomous Underwater Vehicle (AUV II) Utilizing Ultrasonic Sensors

DTIC Science & Technology

1991-09-01

exectti:n by providing geographic waypoints and tasks to the guidance system. The guidance system provides desired vehicle postures, ( x , y, z, 0), as...Maker Guidance System Patter ( x ,y,zlt) Recognition LOS Cross Track No Cubic Spiral Heading Spee Depth Mode Commands Navigation Autopilot System Systems...20log2r + 2otr (Eq 3.3) where ( x is the attenuation coefficient of sound in water at the frequency in use and r is the length of the transmission

The DFKI Competence Center for Ambient Assisted Living

NASA Astrophysics Data System (ADS)

Frey, Jochen; Stahl, Christoph; Röfer, Thomas; Krieg-Brückner, Bernd; Alexandersson, Jan

The DFKI Competence Center for Ambient Assisted Living (CCAAL) is a cross-project and cross-department virtual organization within the German Research Center for Artificial Intelligence coordinating and conducting research and development in the area of Ambient Assisted Living (AAL). Our demonstrators range from multimodal speech dialog systems to fully instrumented environments allowing the development of intelligent assistant systems, for instance an autonomous wheelchair, or the recognition and processing of everyday activities in a smart home. These innovative technologies are then tested, evaluated and demonstrated in DFKI's living labs.

An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.

2005-07-01

Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, further scaling the RCS. A Rician likelihood model compares the scaled RCS of the illuminated aircraft with those of the potential targets. To improve the robustness of the result, the algorithm jointly optimizes over feasible orientation profiles and target types via dynamic programming.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Association Between Autonomic Impairment and Structural Deficit in Parkinson Disease

PubMed Central

Chen, Meng-Hsiang; Lu, Cheng-Hsien; Chen, Pei-Chin; Tsai, Nai-Wen; Huang, Chih-Cheng; Chen, Hsiu-Ling; Yang, I-Hsiao; Yu, Chiun-Chieh; Lin, Wei-Che

2016-01-01

Abstract Patients with Parkinson disease (PD) have impaired autonomic function and altered brain structure. This study aimed to evaluate the relationship of gray matter volume (GMV) determined by voxel-based morphometry (VBM) to autonomic impairment in patients with PD. Whole-brain VBM analysis was performed on 3-dimensional T1-weighted images in 23 patients with PD and 15 sex- and age-matched healthy volunteers. The relationship of cardiovascular autonomic function (determined by survey) to baroreflex sensitivity (BRS) (determined from changes in heart rate and blood pressure during the early phase II of the Valsalva maneuver) was tested using least-squares regression analysis. The differences in GMV, autonomic parameters, and clinical data were correlated after adjusting for age and sex. Compared with controls, patients with PD had low BRS, suggesting worse cardiovascular autonomic function, and smaller GMV in several brain locations, including the right amygdala, left hippocampal formation, bilateral insular cortex, bilateral caudate nucleus, bilateral cerebellum, right fusiform, and left middle frontal gyri. The decreased GMVs of the selected brain regions were also associated with increased presence of epithelial progenitor cells (EPCs) in the circulation. In patients with PD, decrease in cardiovascular autonomic function and increase in circulating EPC level are associated with smaller GMV in several areas of the brain. Because of its possible role in the modulation of the circulatory EPC pool and baroreflex control, the left hippocampal formation may be a bio-target for disease-modifying therapy and treatment monitoring in PD. PMID:26986144

Association Between Autonomic Impairment and Structural Deficit in Parkinson Disease.

PubMed

Chen, Meng-Hsiang; Lu, Cheng-Hsien; Chen, Pei-Chin; Tsai, Nai-Wen; Huang, Chih-Cheng; Chen, Hsiu-Ling; Yang, I-Hsiao; Yu, Chiun-Chieh; Lin, Wei-Che

2016-03-01

Patients with Parkinson disease (PD) have impaired autonomic function and altered brain structure. This study aimed to evaluate the relationship of gray matter volume (GMV) determined by voxel-based morphometry (VBM) to autonomic impairment in patients with PD. Whole-brain VBM analysis was performed on 3-dimensional T1-weighted images in 23 patients with PD and 15 sex- and age-matched healthy volunteers. The relationship of cardiovascular autonomic function (determined by survey) to baroreflex sensitivity (BRS) (determined from changes in heart rate and blood pressure during the early phase II of the Valsalva maneuver) was tested using least-squares regression analysis. The differences in GMV, autonomic parameters, and clinical data were correlated after adjusting for age and sex. Compared with controls, patients with PD had low BRS, suggesting worse cardiovascular autonomic function, and smaller GMV in several brain locations, including the right amygdala, left hippocampal formation, bilateral insular cortex, bilateral caudate nucleus, bilateral cerebellum, right fusiform, and left middle frontal gyri. The decreased GMVs of the selected brain regions were also associated with increased presence of epithelial progenitor cells (EPCs) in the circulation. In patients with PD, decrease in cardiovascular autonomic function and increase in circulating EPC level are associated with smaller GMV in several areas of the brain. Because of its possible role in the modulation of the circulatory EPC pool and baroreflex control, the left hippocampal formation may be a bio-target for disease-modifying therapy and treatment monitoring in PD.

Fully Self-Contained Vision-Aided Navigation and Landing of a Micro Air Vehicle Independent from External Sensor Inputs

NASA Technical Reports Server (NTRS)

Brockers, Roland; Susca, Sara; Zhu, David; Matthies, Larry

2012-01-01

Direct-lift micro air vehicles have important applications in reconnaissance. In order to conduct persistent surveillance in urban environments, it is essential that these systems can perform autonomous landing maneuvers on elevated surfaces that provide high vantage points without the help of any external sensor and with a fully contained on-board software solution. In this paper, we present a micro air vehicle that uses vision feedback from a single down looking camera to navigate autonomously and detect an elevated landing platform as a surrogate for a roof top. Our method requires no special preparation (labels or markers) of the landing location. Rather, leveraging the planar character of urban structure, the landing platform detection system uses a planar homography decomposition to detect landing targets and produce approach waypoints for autonomous landing. The vehicle control algorithm uses a Kalman filter based approach for pose estimation to fuse visual SLAM (PTAM) position estimates with IMU data to correct for high latency SLAM inputs and to increase the position estimate update rate in order to improve control stability. Scale recovery is achieved using inputs from a sonar altimeter. In experimental runs, we demonstrate a real-time implementation running on-board a micro aerial vehicle that is fully self-contained and independent from any external sensor information. With this method, the vehicle is able to search autonomously for a landing location and perform precision landing maneuvers on the detected targets.

TALE-PvuII fusion proteins--novel tools for gene targeting.

PubMed

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity.

Spoken Word Recognition in Toddlers Who Use Cochlear Implants

PubMed Central

Grieco-Calub, Tina M.; Saffran, Jenny R.; Litovsky, Ruth Y.

2010-01-01

Purpose The purpose of this study was to assess the time course of spoken word recognition in 2-year-old children who use cochlear implants (CIs) in quiet and in the presence of speech competitors. Method Children who use CIs and age-matched peers with normal acoustic hearing listened to familiar auditory labels, in quiet or in the presence of speech competitors, while their eye movements to target objects were digitally recorded. Word recognition performance was quantified by measuring each child’s reaction time (i.e., the latency between the spoken auditory label and the first look at the target object) and accuracy (i.e., the amount of time that children looked at target objects within 367 ms to 2,000 ms after the label onset). Results Children with CIs were less accurate and took longer to fixate target objects than did age-matched children without hearing loss. Both groups of children showed reduced performance in the presence of the speech competitors, although many children continued to recognize labels at above-chance levels. Conclusion The results suggest that the unique auditory experience of young CI users slows the time course of spoken word recognition abilities. In addition, real-world listening environments may slow language processing in young language learners, regardless of their hearing status. PMID:19951921

Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

NASA Astrophysics Data System (ADS)

Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi

2018-04-01

Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

The incidental finding of elevated anti GQ1B antibodies in a patient with selective small fiber neuropathy.

PubMed

Favoni, Valentina; Liguori, Rocco; Incensi, Alex; Fileccia, Enrico; Donadio, Vincenzo

2018-05-15

Small fiber neuropathy (SFN) selectively affects small diameter sensory and/or autonomic axons. Pain and autonomic dysfunctions are the most common symptoms. SFN occurs in several autoimmune diseases and autoantibodies against neuronal proteins may play a role in SFN pathophysiology. Anti-GQ1b antibody has been associated with Miller Fisher syndrome, Bickerstaff's brainstem encephalitis, acute ophthalmoplegia, pharyngeal-cervical-brachial weakness and peripheral neuropathy involving large fibers. Isolated SFN associated with anti-GQ1b antibodies has not been previously reported. Here we report a 45-year-old woman presenting with highly positive anti-GQ1b titer and selective SFN without central nervous system or peripheral large nerve involvement. She improved upon administration of adalizumab. Further studies will clarify a possible pathogenetic role of antiganglioside antibodies in SFN. Moreover, the recognition of antiganglioside antibodies in SFN may have therapeutic consequences with patients who would benefit from immunotherapy. Copyright © 2018 Elsevier B.V. All rights reserved.

A design approach for small vision-based autonomous vehicles

NASA Astrophysics Data System (ADS)

Edwards, Barrett B.; Fife, Wade S.; Archibald, James K.; Lee, Dah-Jye; Wilde, Doran K.

2006-10-01

This paper describes the design of a small autonomous vehicle based on the Helios computing platform, a custom FPGA-based board capable of supporting on-board vision. Target applications for the Helios computing platform are those that require lightweight equipment and low power consumption. To demonstrate the capabilities of FPGAs in real-time control of autonomous vehicles, a 16 inch long R/C monster truck was outfitted with a Helios board. The platform provided by such a small vehicle is ideal for testing and development. The proof of concept application for this autonomous vehicle was a timed race through an environment with obstacles. Given the size restrictions of the vehicle and its operating environment, the only feasible on-board sensor is a small CMOS camera. The single video feed is therefore the only source of information from the surrounding environment. The image is then segmented and processed by custom logic in the FPGA that also controls direction and speed of the vehicle based on visual input.

On-rail solution for autonomous inspections in electrical substations

NASA Astrophysics Data System (ADS)

Silva, Bruno P. A.; Ferreira, Rafael A. M.; Gomes, Selson C.; Calado, Flavio A. R.; Andrade, Roberto M.; Porto, Matheus P.

2018-05-01

This work presents an alternative solution for autonomous inspections in electrical substations. The autonomous system is a robot that moves on rails, collects infrared and visible images of selected targets, also processes the data and predicts the components lifetime. The robot moves on rails to overcome difficulties found in not paved substations commonly encountered in Brazil. We take advantage of using rails to convey the data by them, minimizing the electromagnetic interference, and at the same time transmitting electrical energy to feed the autonomous system. As part of the quality control process, we compared thermographic inspections made by the robot with inspections made by a trained thermographer using a scientific camera Flir® SC660. The results have shown that the robot achieved satisfactory results, identifying components and measuring temperature accurately. The embodied routine considers the weather changes along the day, providing a standard result of the components thermal response, also gives the uncertainty of temperature measurement, contributing to the quality in the decision making process.

[Circadian blood pressure variation under several pathophysiological conditions including secondary hypertension].

PubMed

Imai, Yutaka; Hosaka, Miki; Satoh, Michihiro

2014-08-01

Abnormality of circadian blood pressure (BP) variation, i.e. non-dipper, riser, nocturnal hypertension etc, is brought by several pathophysiological conditions especially by secondary hypertension. These pathophysiological conditions are classified into several categories, i.e. disturbance of autonomic nervous system, metabolic disorder, endocrine disorder, disorder of Na and water excretion (e.g. sodium sensitivity), severe target organ damage and ischemia, cardiovascular complications and drug induced hypertension. Each pathophysiological condition which brings disturbance of circadian BP variation is included in several categories, e.g. diabetes mellitus is included in metabolic disorder, autonomic imbalance, sodium sensitivity and endocrine disorder. However, it seems that unified principle of the genesis of disturbance of circadian BP variation in many pathophysiological conditions is autonomic imbalance. Thus, it is concluded that disturbance of circadian BP variation is not purposive biological behavior but the result of autonomic imbalance which looks as if compensatory reaction such as exaggerated Na-water excretion during night in patient with Na-water retention who reveals disturbed circadian BP variation.

Correlations between psychometric schizotypy, scan path length, fixations on the eyes and face recognition.

PubMed

Hills, Peter J; Eaton, Elizabeth; Pake, J Michael

2016-01-01

Psychometric schizotypy in the general population correlates negatively with face recognition accuracy, potentially due to deficits in inhibition, social withdrawal, or eye-movement abnormalities. We report an eye-tracking face recognition study in which participants were required to match one of two faces (target and distractor) to a cue face presented immediately before. All faces could be presented with or without paraphernalia (e.g., hats, glasses, facial hair). Results showed that paraphernalia distracted participants, and that the most distracting condition was when the cue and the distractor face had paraphernalia but the target face did not, while there was no correlation between distractibility and participants' scores on the Schizotypal Personality Questionnaire (SPQ). Schizotypy was negatively correlated with proportion of time fixating on the eyes and positively correlated with not fixating on a feature. It was negatively correlated with scan path length and this variable correlated with face recognition accuracy. These results are interpreted as schizotypal traits being associated with a restricted scan path leading to face recognition deficits.

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

Borovička, Josef; Stoyanov, Simeon D.; Paunov, Vesselin N.

2013-08-01

We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called ``colloid antibodies'', were fabricated by partial fragmentation of silica shells obtained by templating the targeted microbial cells. We successfully demonstrated the shape and size recognition between such colloidal imprints and matching microbial cells. High percentage of binding events of colloidal imprints with the size matching target particles was achieved. We demonstrated selective binding of colloidal imprints to target microbial cells in a binary mixture of cells of different shapes and sizes, which also resulted in high binding selectivity. We explored the role of the electrostatic interactions between the target cells and their colloid imprints by pre-coating both of them with polyelectrolytes. Selective binding occurred predominantly in the case of opposite surface charges of the colloid cell imprint and the targeted cells. The mechanism of the recognition is based on the amplification of the surface adhesion in the case of shape and size match due to the increased contact area between the target cell and the colloidal imprint. We also tested the selective binding for colloid imprints of particles of fixed shape and varying sizes. The concept of cell recognition by colloid imprints could be used for development of colloid antibodies for shape-selective binding of microbes. Such colloid antibodies could be additionally functionalized with surface groups to enhance their binding efficiency to cells of specific shape and deliver a drug payload directly to their surface or allow them to be manipulated using external fields. They could benefit the pharmaceutical industry in developing selective antimicrobial therapies and formulations.

Development of an autonomous video rendezvous and docking system, phase 3

NASA Technical Reports Server (NTRS)

Tietz, J. C.

1984-01-01

Field-of-view limitations proved troublesome. Higher resolution was required. Side thrusters were too weak. The strategy logic was improved and the Kalman filter was augmented to estimate target attitude and tumble rate. Two separate filters were used. The new filter estimates target attitude and angular momentum. The Newton-Raphson iteration improves image interpretation.

Must analysis of meaning follow analysis of form? A time course analysis

PubMed Central

Feldman, Laurie B.; Milin, Petar; Cho, Kit W.; Moscoso del Prado Martín, Fermín; O’Connor, Patrick A.

2015-01-01

Many models of word recognition assume that processing proceeds sequentially from analysis of form to analysis of meaning. In the context of morphological processing, this implies that morphemes are processed as units of form prior to any influence of their meanings. Some interpret the apparent absence of differences in recognition latencies to targets (SNEAK) in form and semantically similar (sneaky-SNEAK) and in form similar and semantically dissimilar (sneaker-SNEAK) prime contexts at a stimulus onset asynchrony (SOA) of 48 ms as consistent with this claim. To determine the time course over which degree of semantic similarity between morphologically structured primes and their targets influences recognition in the forward masked priming variant of the lexical decision paradigm, we compared facilitation for the same targets after semantically similar and dissimilar primes across a range of SOAs (34–100 ms). The effect of shared semantics on recognition latency increased linearly with SOA when long SOAs were intermixed (Experiments 1A and 1B) and latencies were significantly faster after semantically similar than dissimilar primes at homogeneous SOAs of 48 ms (Experiment 2) and 34 ms (Experiment 3). Results limit the scope of form-then-semantics models of recognition and demonstrate that semantics influences even the very early stages of recognition. Finally, once general performance across trials has been accounted for, we fail to provide evidence for individual differences in morphological processing that can be linked to measures of reading proficiency. PMID:25852512

Must analysis of meaning follow analysis of form? A time course analysis.

PubMed

Feldman, Laurie B; Milin, Petar; Cho, Kit W; Moscoso Del Prado Martín, Fermín; O'Connor, Patrick A

2015-01-01

Many models of word recognition assume that processing proceeds sequentially from analysis of form to analysis of meaning. In the context of morphological processing, this implies that morphemes are processed as units of form prior to any influence of their meanings. Some interpret the apparent absence of differences in recognition latencies to targets (SNEAK) in form and semantically similar (sneaky-SNEAK) and in form similar and semantically dissimilar (sneaker-SNEAK) prime contexts at a stimulus onset asynchrony (SOA) of 48 ms as consistent with this claim. To determine the time course over which degree of semantic similarity between morphologically structured primes and their targets influences recognition in the forward masked priming variant of the lexical decision paradigm, we compared facilitation for the same targets after semantically similar and dissimilar primes across a range of SOAs (34-100 ms). The effect of shared semantics on recognition latency increased linearly with SOA when long SOAs were intermixed (Experiments 1A and 1B) and latencies were significantly faster after semantically similar than dissimilar primes at homogeneous SOAs of 48 ms (Experiment 2) and 34 ms (Experiment 3). Results limit the scope of form-then-semantics models of recognition and demonstrate that semantics influences even the very early stages of recognition. Finally, once general performance across trials has been accounted for, we fail to provide evidence for individual differences in morphological processing that can be linked to measures of reading proficiency.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Automated Target Planning for FUSE Using the SOVA Algorithm

NASA Technical Reports Server (NTRS)

Heatwole, Scott; Lanzi, R. James; Civeit, Thomas; Calvani, Humberto; Kruk, Jeffrey W.; Suchkov, Anatoly

2007-01-01

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Posterior Orbitofrontal and Anterior Cingulate Pathways to the Amygdala Target Inhibitory and Excitatory Systems with Opposite Functions.

PubMed

Zikopoulos, Basilis; Höistad, Malin; John, Yohan; Barbas, Helen

2017-05-17

The bidirectional dialogue of the primate posterior orbitofrontal cortex (pOFC) with the amygdala is essential in cognitive-emotional functions. The pOFC also sends a uniquely one-way excitatory pathway to the amygdalar inhibitory intercalated masses (IM), which inhibit the medial part of the central amygdalar nucleus (CeM). Inhibition of IM has the opposite effect, allowing amygdalar activation of autonomic structures and emotional arousal. Using multiple labeling approaches to identify pathways and their postsynaptic sites in the amygdala in rhesus monkeys, we found that the anterior cingulate cortex innervated mostly the basolateral and CeM amygdalar nuclei, poised to activate CeM for autonomic arousal. By contrast, a pathway from pOFC to IM exceeded all other pathways to the amygdala by density and size and proportion of large and efficient terminals. Moreover, whereas pOFC terminals in IM innervated each of the three distinct classes of inhibitory neurons, most targeted neurons expressing dopamine- and cAMP-regulated phosphoprotein (DARPP-32+), known to be modulated by dopamine. The predominant pOFC innervation of DARPP-32+ neurons suggests activation of IM and inhibition of CeM, resulting in modulated autonomic function. By contrast, inhibition of DARPP-32 neurons in IM by high dopamine levels disinhibits CeM and triggers autonomic arousal. The findings provide a mechanism to help explain how a strong pOFC pathway, which is poised to moderate activity of CeM, through IM, can be undermined by the high level of dopamine during stress, resulting in collapse of potent inhibitory mechanisms in the amygdala and heightened autonomic drive, as seen in chronic anxiety disorders. SIGNIFICANCE STATEMENT The dialogue between prefrontal cortex and amygdala allows thoughts and emotions to influence actions. The posterior orbitofrontal cortex sends a powerful pathway that targets a special class of amygdalar intercalated mass (IM) inhibitory neurons, whose wiring may help modulate autonomic function. By contrast, the anterior cingulate cortex innervates other amygdalar parts, activating circuits to help avoid danger. Most IM neurons in primates label for the protein DARPP-32, known to be activated or inhibited based on the level of dopamine. Stress markedly increases dopamine release and inhibits IM neurons, compromises prefrontal control of the amygdala, and sets off a general alarm system as seen in affective disorders, such as chronic anxiety and post-traumatic stress disorder. Copyright © 2017 the authors 0270-6474/17/375051-14$15.00/0.

A Novel Method of Autonomous Inspection for Transmission Line based on Cable Inspection Robot LiDAR Data

PubMed Central

Qin, Xinyan; Wu, Gongping; Fan, Fei; Ye, Xuhui; Mei, Quanjie

2018-01-01

With the growth of the national economy, there is increasing demand for electricity, which forces transmission line corridors to become structurally complicated and extend to complex environments (e.g., mountains, forests). It is a great challenge to inspect transmission line in these regions. To address these difficulties, a novel method of autonomous inspection for transmission line is proposed based on cable inspection robot (CIR) LiDAR data, which mainly includes two steps: preliminary inspection and autonomous inspection. In preliminary inspection, the position and orientation system (POS) data is used for original point cloud dividing, ground point filtering, and structured partition. A hierarchical classification strategy is established to identify the classes and positions of the abnormal points. In autonomous inspection, CIR can autonomously reach the specified points through inspection planning. These inspection targets are imaged with PTZ (pan, tilt, zoom) cameras by coordinate transformation. The feasibility and effectiveness of the proposed method are verified by test site experiments and actual line experiments, respectively. The proposed method greatly reduces manpower and improves inspection accuracy, providing a theoretical basis for intelligent inspection of transmission lines in the future. PMID:29462865

Independent Associations and Interactions of Perceived Neighborhood and Psychosocial Constructs on Adults' Physical Activity.

PubMed

Dwyer, Laura A; Patel, Minal; Nebeling, Linda C; Oh, April Y

2018-05-01

Neighborhood and psychosocial variables are related to physical activity (PA), yet interactions between these factors in predicting PA are infrequently studied. This analysis examines the independent associations and interactions between self-reported neighborhood and psychosocial variables in relation to moderate to vigorous PA (MVPA) among adults from a US panel sample. In adjusted models, neighborhood social capital was positively associated with meeting MVPA guidelines. Fewer barriers, greater self-efficacy, and greater autonomous motivation also corresponded with greater odds of meeting MVPA guidelines. An interaction between social capital and autonomous motivation showed that social capital was only associated with MVPA when autonomous motivation was high. Participants who reported both high autonomous motivation and high social capital were most likely to meet MVPA guidelines. Neighborhood social capital, barriers, self-efficacy, and autonomous motivation may be important correlates in promoting adults' PA. Future directions include using objective neighborhood and PA data in similar analyses and investigating associations of neighborhood and psychosocial variables with multiple PA activities. Intervention research to promote PA should also examine whether effects of interventions targeting psychosocial constructs are moderated by features of an individual's neighborhood or whether perceived social capital can be addressed in interventions in conjunction with psychosocial variables.

To Be or Not to Be in Thrall to the March of Smart Products

PubMed Central

Van den Hende, Ellis A.

2016-01-01

ABSTRACT This article explores how perceived disempowerment impacts the intention to adopt smart autonomous products. Empirically, the paper builds on three studies to show this impact. Study 1 explores the relevance of the perceived disempowerment in respect of smart autonomous products. Study 2 manipulates autonomy of smart products and finds that perceived disempowerment mediates the link between smart products’ autonomy and adoption intention. Study 3 indicates that an intervention design―that is, a product design that allows consumers to intervene in the actions of an autonomous smart product―can reduce their perceived disempowerment in respect of autonomous smart products. Further, Study 3 reveals that personal innovativeness moderates the role that an intervention design plays in product adoption: an intervention design shows a positive effect on adoption intention for individuals with low personal innovativeness, but for those with high personal innovativeness no effect of an intervention design is present on adoption intention. The authors suggest that managers consider consumers’ perceived disempowerment when designing autonomous smart products, because (1) perceived disempowerment reduces adoption and (2) when targeted at consumers with low personal innovativeness, an intervention design reduces their perceived disempowerment. PMID:27980356

A smart telerobotic system driven by monocular vision

NASA Technical Reports Server (NTRS)

Defigueiredo, R. J. P.; Maccato, A.; Wlczek, P.; Denney, B.; Scheerer, J.

1994-01-01

A robotic system that accepts autonomously generated motion and control commands is described. The system provides images from the monocular vision of a camera mounted on a robot's end effector, eliminating the need for traditional guidance targets that must be predetermined and specifically identified. The telerobotic vision system presents different views of the targeted object relative to the camera, based on a single camera image and knowledge of the target's solid geometry.

Collaboration in Associative Recognition Memory: Using Recalled Information to Defend "New" Judgments

ERIC Educational Resources Information Center

Clark, Steven E.; Abbe, Allison; Larson, Rakel P.

2006-01-01

S. E. Clark, A. Hori, A. Putnam, and T. J. Martin (2000) showed that collaboration on a recognition memory task produced facilitation in recognition of targets but had inconsistent and sometimes negative effects regarding distractors. They accounted for these results within the framework of a dual-process, recall-plus-familiarity model but…

Declines in Representational Quality and Strategic Retrieval Processes Contribute to Age-Related Increases in False Recognition

ERIC Educational Resources Information Center

Trelle, Alexandra N.; Henson, Richard N.; Green, Deborah A. E.; Simons, Jon S.

2017-01-01

In a Yes/No object recognition memory test with similar lures, older adults typically exhibit elevated rates of false recognition. However, the contributions of impaired retrieval, relative to reduced availability of target details, are difficult to disentangle using such a test. The present investigation sought to decouple these factors by…

The Slow Developmental Time Course of Real-Time Spoken Word Recognition

ERIC Educational Resources Information Center

Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

2015-01-01

This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

Amplitude (vu and rms) and Temporal (msec) Measures of Two Northwestern University Auditory Test No. 6 Recordings.

PubMed

Wilson, Richard H

2015-04-01

In 1940, a cooperative effort by the radio networks and Bell Telephone produced the volume unit (vu) meter that has been the mainstay instrument for monitoring the level of speech signals in commercial broadcasting and research laboratories. With the use of computers, today the amplitude of signals can be quantified easily using the root mean square (rms) algorithm. Researchers had previously reported that amplitude estimates of sentences and running speech were 4.8 dB higher when measured with a vu meter than when calculated with rms. This study addresses the vu-rms relation as applied to the carrier phrase and target word paradigm used to assess word-recognition abilities, the premise being that by definition the word-recognition paradigm is a special and different case from that described previously. The purpose was to evaluate the vu and rms amplitude relations for the carrier phrases and target words commonly used to assess word-recognition abilities. In addition, the relations with the target words between rms level and recognition performance were examined. Descriptive and correlational. Two recoded versions of the Northwestern University Auditory Test No. 6 were evaluated, the Auditec of St. Louis (Auditec) male speaker and the Department of Veterans Affairs (VA) female speaker. Using both visual and auditory cues from a waveform editor, the temporal onsets and offsets were defined for each carrier phrase and each target word. The rms amplitudes for those segments then were computed and expressed in decibels with reference to the maximum digitization range. The data were maintained for each of the four Northwestern University Auditory Test No. 6 word lists. Descriptive analyses were used with linear regressions used to evaluate the reliability of the measurement technique and the relation between the rms levels of the target words and recognition performances. Although there was a 1.3 dB difference between the calibration tones, the mean levels of the carrier phrases for the two recordings were -14.8 dB (Auditec) and -14.1 dB (VA) with standard deviations <1 dB. For the target words, the mean amplitudes were -19.9 dB (Auditec) and -18.3 dB (VA) with standard deviations ranging from 1.3 to 2.4 dB. The mean durations for the carrier phrases of both recordings were 593-594 msec, with the mean durations of the target words a little different, 509 msec (Auditec) and 528 msec (VA). Random relations were observed between the recognition performances and rms levels of the target words. Amplitude and temporal data for the individual words are provided. The rms levels of the carrier phrases closely approximated (±1 dB) the rms levels of the calibration tones, both of which were set to 0 vu (dB). The rms levels of the target words were 5-6 dB below the levels of the carrier phrases and were substantially more variable than the levels of the carrier phrases. The relation between the rms levels of the target words and recognition performances on the words was random. American Academy of Audiology.

Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

NASA Technical Reports Server (NTRS)

Frost, S. A.; Balas, M. J.

2010-01-01

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.

From scores to face templates: a model-based approach.

PubMed

Mohanty, Pranab; Sarkar, Sudeep; Kasturi, Rangachar

2007-12-01

Regeneration of templates from match scores has security and privacy implications related to any biometric authentication system. We propose a novel paradigm to reconstruct face templates from match scores using a linear approach. It proceeds by first modeling the behavior of the given face recognition algorithm by an affine transformation. The goal of the modeling is to approximate the distances computed by a face recognition algorithm between two faces by distances between points, representing these faces, in an affine space. Given this space, templates from an independent image set (break-in) are matched only once with the enrolled template of the targeted subject and match scores are recorded. These scores are then used to embed the targeted subject in the approximating affine (non-orthogonal) space. Given the coordinates of the targeted subject in the affine space, the original template of the targeted subject is reconstructed using the inverse of the affine transformation. We demonstrate our ideas using three, fundamentally different, face recognition algorithms: Principal Component Analysis (PCA) with Mahalanobis cosine distance measure, Bayesian intra-extrapersonal classifier (BIC), and a feature-based commercial algorithm. To demonstrate the independence of the break-in set with the gallery set, we select face templates from two different databases: Face Recognition Grand Challenge (FRGC) and Facial Recognition Technology (FERET) Database (FERET). With an operational point set at 1 percent False Acceptance Rate (FAR) and 99 percent True Acceptance Rate (TAR) for 1,196 enrollments (FERET gallery), we show that at most 600 attempts (score computations) are required to achieve a 73 percent chance of breaking in as a randomly chosen target subject for the commercial face recognition system. With similar operational set up, we achieve a 72 percent and 100 percent chance of breaking in for the Bayesian and PCA based face recognition systems, respectively. With three different levels of score quantization, we achieve 69 percent, 68 percent and 49 percent probability of break-in, indicating the robustness of our proposed scheme to score quantization. We also show that the proposed reconstruction scheme has 47 percent more probability of breaking in as a randomly chosen target subject for the commercial system as compared to a hill climbing approach with the same number of attempts. Given that the proposed template reconstruction method uses distinct face templates to reconstruct faces, this work exposes a more severe form of vulnerability than a hill climbing kind of attack where incrementally different versions of the same face are used. Also, the ability of the proposed approach to reconstruct actual face templates of the users increases privacy concerns in biometric systems.

Differential effects of MDMA and methylphenidate on social cognition.

PubMed

Schmid, Yasmin; Hysek, Cédric M; Simmler, Linda D; Crockett, Molly J; Quednow, Boris B; Liechti, Matthias E

2014-09-01

Social cognition is important in everyday-life social interactions. The social cognitive effects of 3,4-methylenedioxymethamphetamine (MDMA, 'ecstasy') and methylphenidate (both used for neuroenhancement and as party drugs) are largely unknown. We investigated the acute effects of MDMA (75 mg), methylphenidate (40 mg) and placebo using the Facial Emotion Recognition Task, Multifaceted Empathy Test, Movie for the Assessment of Social Cognition, Social Value Orientation Test and the Moral Judgment Task in a cross-over study in 30 healthy subjects. Additionally, subjective, autonomic, pharmacokinetic, endocrine and adverse drug effects were measured. MDMA enhanced emotional empathy for positive emotionally charged situations in the MET and tended to reduce the recognition of sad faces in the Facial Emotion Recognition Task. MDMA had no effects on cognitive empathy in the Multifaceted Empathy Test or social cognitive inferences in the Movie for the Assessment of Social Cognition. MDMA produced subjective 'empathogenic' effects, such as drug liking, closeness to others, openness and trust. In contrast, methylphenidate lacked such subjective effects and did not alter emotional processing, empathy or mental perspective-taking. MDMA but not methylphenidate increased the plasma levels of oxytocin and prolactin. None of the drugs influenced moral judgment. Effects on emotion recognition and emotional empathy were evident at a low dose of MDMA and likely contribute to the popularity of the drug. © The Author(s) 2014.

RoBlock: a prototype autonomous manufacturing cell

NASA Astrophysics Data System (ADS)

Baekdal, Lars K.; Balslev, Ivar; Eriksen, Rene D.; Jensen, Soren P.; Jorgensen, Bo N.; Kirstein, Brian; Kristensen, Bent B.; Olsen, Martin M.; Perram, John W.; Petersen, Henrik G.; Petersen, Morten L.; Ruhoff, Peter T.; Skjolstrup, Carl E.; Sorensen, Anders S.; Wagenaar, Jeroen M.

2000-10-01

RoBlock is the first phase of an internally financed project at the Institute aimed at building a system in which two industrial robots suspended from a gantry, as shown below, cooperate to perform a task specified by an external user, in this case, assembling an unstructured collection of colored wooden blocks into a specified 3D pattern. The blocks are identified and localized using computer vision and grasped with a suction cup mechanism. Future phases of the project will involve other processes such as grasping and lifting, as well as other types of robot such as autonomous vehicles or variable geometry trusses. Innovative features of the control software system include: The use of an advanced trajectory planning system which ensures collision avoidance based on a generalization of the method of artificial potential fields, the use of a generic model-based controller which learns the values of parameters, including static and kinetic friction, of a detailed mechanical model of itself by comparing actual with planned movements, the use of fast, flexible, and robust pattern recognition and 3D-interpretation strategies, integration of trajectory planning and control with the sensor systems in a distributed Java application running on a network of PC's attached to the individual physical components. In designing this first stage, the aim was to build in the minimum complexity necessary to make the system non-trivially autonomous and to minimize the technological risks. The aims of this project, which is planned to be operational during 2000, are as follows: To provide a platform for carrying out experimental research in multi-agent systems and autonomous manufacturing systems, to test the interdisciplinary cooperation architecture of the Maersk Institute, in which researchers in the fields of applied mathematics (modeling the physical world), software engineering (modeling the system) and sensor/actuator technology (relating the virtual and real worlds) could collaborate with systems integrators to construct intelligent, autonomous systems, and to provide a showpiece demonstrator in the entrance hall of the Institute's new building.

Image-algebraic design of multispectral target recognition algorithms

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.

1994-06-01

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

NASA Astrophysics Data System (ADS)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Toward sensor modular autonomy for persistent land intelligence surveillance and reconnaissance (ISR)

NASA Astrophysics Data System (ADS)

Thomas, Paul A.; Marshall, Gillian; Faulkner, David; Kent, Philip; Page, Scott; Islip, Simon; Oldfield, James; Breckon, Toby P.; Kundegorski, Mikolaj E.; Clark, David J.; Styles, Tim

2016-05-01

Currently, most land Intelligence, Surveillance and Reconnaissance (ISR) assets (e.g. EO/IR cameras) are simply data collectors. Understanding, decision making and sensor control are performed by the human operators, involving high cognitive load. Any automation in the system has traditionally involved bespoke design of centralised systems that are highly specific for the assets/targets/environment under consideration, resulting in complex, non-flexible systems that exhibit poor interoperability. We address a concept of Autonomous Sensor Modules (ASMs) for land ISR, where these modules have the ability to make low-level decisions on their own in order to fulfil a higher-level objective, and plug in, with the minimum of preconfiguration, to a High Level Decision Making Module (HLDMM) through a middleware integration layer. The dual requisites of autonomy and interoperability create challenges around information fusion and asset management in an autonomous hierarchical system, which are addressed in this work. This paper presents the results of a demonstration system, known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT), which was shown in realistic base protection scenarios with live sensors and targets. The SAPIENT system performed sensor cueing, intelligent fusion, sensor tasking, target hand-off and compensation for compromised sensors, without human control, and enabled rapid integration of ISR assets at the time of system deployment, rather than at design-time. Potential benefits include rapid interoperability for coalition operations, situation understanding with low operator cognitive burden and autonomous sensor management in heterogenous sensor systems.

Real-time polarization imaging algorithm for camera-based polarization navigation sensors.

PubMed

Lu, Hao; Zhao, Kaichun; You, Zheng; Huang, Kaoli

2017-04-10

Biologically inspired polarization navigation is a promising approach due to its autonomous nature, high precision, and robustness. Many researchers have built point source-based and camera-based polarization navigation prototypes in recent years. Camera-based prototypes can benefit from their high spatial resolution but incur a heavy computation load. The pattern recognition algorithm in most polarization imaging algorithms involves several nonlinear calculations that impose a significant computation burden. In this paper, the polarization imaging and pattern recognition algorithms are optimized through reduction to several linear calculations by exploiting the orthogonality of the Stokes parameters without affecting precision according to the features of the solar meridian and the patterns of the polarized skylight. The algorithm contains a pattern recognition algorithm with a Hough transform as well as orientation measurement algorithms. The algorithm was loaded and run on a digital signal processing system to test its computational complexity. The test showed that the running time decreased to several tens of milliseconds from several thousand milliseconds. Through simulations and experiments, it was found that the algorithm can measure orientation without reducing precision. It can hence satisfy the practical demands of low computational load and high precision for use in embedded systems.

Exploiting range imagery: techniques and applications

NASA Astrophysics Data System (ADS)

Armbruster, Walter

2009-07-01

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.

Autonomic, locomotor and cardiac abnormalities in a mouse model of muscular dystrophy: targeting the renin-angiotensin system.

PubMed

Sabharwal, Rasna; Chapleau, Mark W

2014-04-01

New Findings What is the topic of this review? This symposium report summarizes autonomic, cardiac and skeletal muscle abnormalities in sarcoglycan-δ-deficient mice (Sgcd-/-), a mouse model of limb girdle muscular dystrophy, with emphasis on the roles of autonomic dysregulation and activation of the renin-angiotensin system at a young age. What advances does it highlight? The contributions of the autonomic nervous system and the renin-angiotensin system to the pathogenesis of muscular dystrophy are highlighted. Results demonstrate that autonomic dysregulation precedes and predicts later development of cardiac dysfunction in Sgcd-/- mice and that treatment of young Sgcd-/- mice with the angiotensin type 1 receptor antagonist losartan or with angiotensin-(1-7) abrogates the autonomic dysregulation, attenuates skeletal muscle pathology and increases spontaneous locomotor activity. Muscular dystrophies are a heterogeneous group of genetic muscle diseases characterized by muscle weakness and atrophy. Mutations in sarcoglycans and other subunits of the dystrophin-glycoprotein complex cause muscular dystrophy and dilated cardiomyopathy in animals and humans. Aberrant autonomic signalling is recognized in a variety of neuromuscular disorders. We hypothesized that activation of the renin-angiotensin system contributes to skeletal muscle and autonomic dysfunction in mice deficient in the sarcoglycan-δ (Sgcd) gene at a young age and that this early autonomic dysfunction contributes to the later development of left ventricular (LV) dysfunction and increased mortality. We demonstrated that young Sgcd-/- mice exhibit histopathological features of skeletal muscle dystrophy, decreased locomotor activity and severe autonomic dysregulation, but normal LV function. Autonomic regulation continued to deteriorate in Sgcd-/- mice with age and was accompanied by LV dysfunction and dilated cardiomyopathy at older ages. Autonomic dysregulation at a young age predicted later development of LV dysfunction and higher mortality in Sgcd-/- mice. Treatment of Sgcd-/- mice with the angiotensin type 1 receptor blocker losartan for 8-9 weeks, beginning at 3 weeks of age, decreased fibrosis and oxidative stress in skeletal muscle, increased locomotor activity and prevented autonomic dysfunction. Chronic infusion of the counter-regulatory peptide angiotensin-(1-7) resulted in similar protection. We conclude that activation of the renin-angiotensin system, at a young age, contributes to skeletal muscle and autonomic dysfunction in muscular dystrophy. We speculate that the latter is mediated via abnormal sensory nerve and/or cytokine signalling from dystrophic skeletal muscle to the brain and contributes to age-related LV dysfunction, dilated cardiomyopathy, arrhythmias and premature death. Therefore, correcting the early autonomic dysregulation and renin-angiotensin system activation may provide a novel therapeutic approach in muscular dystrophy.

Control of working memory: effects of attention training on target recognition and distractor salience in an auditory selection task.

PubMed

Melara, Robert D; Tong, Yunxia; Rao, Aparna

2012-01-09

Behavioral and electrophysiological measures of target and distractor processing were examined in an auditory selective attention task before and after three weeks of distractor suppression training. Behaviorally, training improved target recognition and led to less conservative and more rapid responding. Training also effectively shortened the temporal distance between distractors and targets needed to achieve a fixed level of target sensitivity. The effects of training on event-related potentials were restricted to the distracting stimulus: earlier N1 latency, enhanced P2 amplitude, and weakened P3 amplitude. Nevertheless, as distractor P2 amplitude increased, so too did target P3 amplitude, connecting experience-dependent changes in distractor processing with greater distinctiveness of targets in working memory. We consider the effects of attention training on the processing priorities, representational noise, and inhibitory processes operating in working memory. Copyright © 2011 Elsevier B.V. All rights reserved.

VNIR hyperspectral background characterization methods in adverse weather conditions

NASA Astrophysics Data System (ADS)

Romano, João M.; Rosario, Dalton; Roth, Luz

2009-05-01

Hyperspectral technology is currently being used by the military to detect regions of interest where potential targets may be located. Weather variability, however, may affect the ability for an algorithm to discriminate possible targets from background clutter. Nonetheless, different background characterization approaches may facilitate the ability for an algorithm to discriminate potential targets over a variety of weather conditions. In a previous paper, we introduced a new autonomous target size invariant background characterization process, the Autonomous Background Characterization (ABC) or also known as the Parallel Random Sampling (PRS) method, features a random sampling stage, a parallel process to mitigate the inclusion by chance of target samples into clutter background classes during random sampling; and a fusion of results at the end. In this paper, we will demonstrate how different background characterization approaches are able to improve performance of algorithms over a variety of challenging weather conditions. By using the Mahalanobis distance as the standard algorithm for this study, we compare the performance of different characterization methods such as: the global information, 2 stage global information, and our proposed method, ABC, using data that was collected under a variety of adverse weather conditions. For this study, we used ARDEC's Hyperspectral VNIR Adverse Weather data collection comprised of heavy, light, and transitional fog, light and heavy rain, and low light conditions.

Direct comparison of the acute subjective, emotional, autonomic, and endocrine effects of MDMA, methylphenidate, and modafinil in healthy subjects.

PubMed

Dolder, Patrick C; Müller, Felix; Schmid, Yasmin; Borgwardt, Stefan J; Liechti, Matthias E

2018-02-01

3,4-Methylenedioxymethamphetamine (MDMA) is used recreationally and investigated as an adjunct to psychotherapy. Methylphenidate and modafinil are psychostimulants that are used to treat attention-deficit/hyperactivity disorder and narcolepsy, respectively, but they are also misused as cognitive enhancers. Little is known about differences in the acute effects of equally cardiostimulant doses of these stimulant-type substances compared directly within the same subjects. We investigated the acute autonomic, subjective, endocrine, and emotional effects of single doses of MDMA (125 mg), methylphenidate (60 mg), modafinil (600 mg), and placebo in a double-blind, cross-over study in 24 healthy participants. Acute drug effects were tested using psychometric scales, the Facial Emotion Recognition Task (FERT), and the Sexual Arousal and Desire Inventory (SADI). All active drugs produced comparable hemodynamic and adverse effects. MDMA produced greater increases in pupil dilation, subjective good drug effects, drug liking, happiness, trust, well-being, and alterations in consciousness than methylphenidate or modafinil. Only MDMA reduced subjective anxiety and impaired fear recognition and led to misclassifications of emotions as happy on the FERT. On the SADI, only MDMA produced sexual arousal-like effects. Only MDMA produced marked increases in cortisol, prolactin, and oxytocin. In contrast to MDMA, methylphenidate increased subjective anxiety, and methylphenidate and modafinil increased misclassifications of emotions as angry on the FERT. Modafinil had no significant subjective drug effects but significant sympathomimetic and adverse effects. MDMA induced subjective, emotional, sexual, and endocrine effects that were clearly distinct from those of methylphenidate and modafinil at the doses used.

ERP Correlates of Target-Distracter Differentiation in Repeated Runs of a Continuous Recognition Task with Emotional and Neutral Faces

ERIC Educational Resources Information Center

Treese, Anne-Cecile; Johansson, Mikael; Lindgren, Magnus

2010-01-01

The emotional salience of faces has previously been shown to induce memory distortions in recognition memory tasks. This event-related potential (ERP) study used repeated runs of a continuous recognition task with emotional and neutral faces to investigate emotion-induced memory distortions. In the second and third runs, participants made more…

A Pilot Study of a Test for Visual Recognition Memory in Adults with Moderate to Severe Intellectual Disability

ERIC Educational Resources Information Center

Pyo, Geunyeong; Ala, Tom; Kyrouac, Gregory A.; Verhulst, Steven J.

2010-01-01

Objective assessment of memory functioning is an important part of evaluation for Dementia of Alzheimer Type (DAT). The revised Picture Recognition Memory Test (r-PRMT) is a test for visual recognition memory to assess memory functioning of persons with intellectual disabilities (ID), specifically targeting moderate to severe ID. A pilot study was…

Linguistic contributions to speech-on-speech masking for native and non-native listeners: language familiarity and semantic content.

PubMed

Brouwer, Susanne; Van Engen, Kristin J; Calandruccio, Lauren; Bradlow, Ann R

2012-02-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener's knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. © 2012 Acoustical Society of America

A new FOD recognition algorithm based on multi-source information fusion and experiment analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Xiao, Gang

2011-08-01

Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.

Linguistic contributions to speech-on-speech masking for native and non-native listeners: Language familiarity and semantic content

PubMed Central

Brouwer, Susanne; Van Engen, Kristin J.; Calandruccio, Lauren; Bradlow, Ann R.

2012-01-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener’s knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. PMID:22352516

Simultaneous Versus Sequential Presentation in Testing Recognition Memory for Faces.

PubMed

Finley, Jason R; Roediger, Henry L; Hughes, Andrea D; Wahlheim, Christopher N; Jacoby, Larry L

2015-01-01

Three experiments examined the issue of whether faces could be better recognized in a simul- taneous test format (2-alternative forced choice [2AFC]) or a sequential test format (yes-no). All experiments showed that when target faces were present in the test, the simultaneous procedure led to superior performance (area under the ROC curve), whether lures were high or low in similarity to the targets. However, when a target-absent condition was used in which no lures resembled the targets but the lures were similar to each other, the simultaneous procedure yielded higher false alarm rates (Experiments 2 and 3) and worse overall performance (Experi- ment 3). This pattern persisted even when we excluded responses that participants opted to withhold rather than volunteer. We conclude that for the basic recognition procedures used in these experiments, simultaneous presentation of alternatives (2AFC) generally leads to better discriminability than does sequential presentation (yes-no) when a target is among the alterna- tives. However, our results also show that the opposite can occur when there is no target among the alternatives. An important future step is to see whether these patterns extend to more realistic eyewitness lineup procedures. The pictures used in the experiment are available online at http://www.press.uillinois.edu/journals/ajp/media/testing_recognition/.

Sleep and eyewitness memory: Fewer false identifications after sleep when the target is absent from the lineup.

PubMed

Stepan, Michelle E; Dehnke, Taylor M; Fenn, Kimberly M

2017-01-01

Inaccurate eyewitness identifications are the leading cause of known false convictions in the United States. Moreover, improving eyewitness memory is difficult and often unsuccessful. Sleep consistently strengthens and protects memory from interference, particularly when a recall test is used. However, the effect of sleep on recognition memory is more equivocal. Eyewitness identification tests are often recognition based, thus leaving open the question of how sleep affects recognition performance in an eyewitness context. In the current study, we investigated the effect of sleep on eyewitness memory. Participants watched a video of a mock-crime and attempted to identify the perpetrator from a simultaneous lineup after a 12-hour retention interval that either spanned a waking day or night of sleep. In Experiment 1, we used a target-present lineup and, in Experiment 2, we used a target-absent lineup in order to investigate correct and false identifications, respectively. Sleep reduced false identifications in the target-absent lineup (Experiment 2) but had no effect on correct identifications in the target-present lineup (Experiment 1). These results are discussed with respect to memory strength and decision making strategies.

Sleep and eyewitness memory: Fewer false identifications after sleep when the target is absent from the lineup

PubMed Central

Dehnke, Taylor M.; Fenn, Kimberly M.

2017-01-01

Inaccurate eyewitness identifications are the leading cause of known false convictions in the United States. Moreover, improving eyewitness memory is difficult and often unsuccessful. Sleep consistently strengthens and protects memory from interference, particularly when a recall test is used. However, the effect of sleep on recognition memory is more equivocal. Eyewitness identification tests are often recognition based, thus leaving open the question of how sleep affects recognition performance in an eyewitness context. In the current study, we investigated the effect of sleep on eyewitness memory. Participants watched a video of a mock-crime and attempted to identify the perpetrator from a simultaneous lineup after a 12-hour retention interval that either spanned a waking day or night of sleep. In Experiment 1, we used a target-present lineup and, in Experiment 2, we used a target-absent lineup in order to investigate correct and false identifications, respectively. Sleep reduced false identifications in the target-absent lineup (Experiment 2) but had no effect on correct identifications in the target-present lineup (Experiment 1). These results are discussed with respect to memory strength and decision making strategies. PMID:28877169

Laser rangefinders for autonomous intelligent cruise control systems

NASA Astrophysics Data System (ADS)

Journet, Bernard A.; Bazin, Gaelle

1998-01-01

THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.

ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs

NASA Astrophysics Data System (ADS)

Adil Mahdi, Omar; Wahab, Ainuddin Wahid Abdul; Idris, Mohd Yamani Idna; Znaid, Ammar Abu; Khan, Suleman; Al-Mayouf, Yusor Rafid Bahar

2016-10-01

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

DTIC Science & Technology

2014-03-27

and machine learning for a range of research including such topics as medical imaging [10] and handwriting recognition [11]. The type of feature...1989. [11] C. Bahlmann, B. Haasdonk, and H. Burkhardt, “Online handwriting recognition with support vector machines-a kernel approach,” in Eighth...International Workshop on Frontiers in Handwriting Recognition, pp. 49–54, IEEE, 2002. [12] C. Cortes and V. Vapnik, “Support-vector networks,” Machine

Effects of the augmenter of liver regeneration on the biological behavior of hepatocellular carcinoma.

PubMed

Tang, Lin; Sun, Hang; Zhang, Lin; Deng, Jian C; Guo, Hui; Zhang, Ling; Liu, Qi

2009-08-01

To take advantage of the small interfering ribonucleic acid (siRNA) targeting the human augmenter of liver regeneration (hALR) and anti-hALR monoclonal antibody (McAb) to inhibit the function of hALR, and to demonstrate whether the growth of hepatoma is influenced by siRNA targeting hALR and anti-hALR McAb through inhibiting expression of hALR. This study was conducted in the Key Laboratory of Molecular Biology for Infectious Diseases, Ministry of Education, Institute for Viral Hepatitis, Chongqing Medical University, China, between January 2005 and May 2007. We transfected siRNA plasmid pSIALR-A, which targeted the complementary deoxyribonucleic acid (cDNA) of hALR and the unrelated control plasmid pSIALR-B into human hepatocellular liver carcinoma cell line (HepG2) cells. Then, the proliferation of HepG2 cells, after being treated with pSIALR-A and anti-hALR McAb was detected. The growth of the xenograft tumor was observed after being treated with pSIALR-A and anti-hALR McAb in nude mice. We successfully constructed expressing plasmid pSIALR-A and pSIALR-B. The pSIALR-A inhibited the expression of hALR in HepG2 cells significantly. The siRNA targeting hALR and anti-hALR McAb inhibited obviously the growth of HepG2 cells in vitro. siRNA targeting hALR and anti-hALR McAb significantly inhibited the growth of xenograft tumor in 5 nude mice. Anti-hALR McAb inhibited apparently the autonomous growth of HepG2 cells. Our results demonstrated that anti-hALR McAb inhibited the autonomous growth of hepatoma cells obviously, moreover, hALR maintained the autonomous growth of hepatoma cells in vitro through an autocrine mechanism.

Cascade DNA nanomachine and exponential amplification biosensing.

PubMed

Xu, Jianguo; Wu, Zai-Sheng; Shen, Weiyu; Xu, Huo; Li, Hongling; Jia, Lee

2015-11-15

DNA is a versatile scaffold for the assembly of multifunctional nanostructures, and potential applications of various DNA nanodevices have been recently demonstrated for disease diagnosis and treatment. In the current study, a powerful cascade DNA nanomachine was developed that can execute the exponential amplification of p53 tumor suppressor gene. During the operation of the newly-proposed DNA nanomachine, dual-cyclical nucleic acid strand-displacement polymerization (dual-CNDP) was ingeniously introduced, where the target trigger is repeatedly used as the fuel molecule and the nicked fragments are dramatically accumulated. Moreover, each displaced nicked fragment is able to activate the another type of cyclical strand-displacement amplification, increasing exponentially the value of fluorescence intensity. Essentially, one target binding event can induce considerable number of subsequent reactions, and the nanodevice was called cascade DNA nanomachine. It can implement several functions, including recognition element, signaling probe, polymerization primer and template. Using the developed autonomous operation of DNA nanomachine, the p53 gene can be quantified in the wide concentration range from 0.05 to 150 nM with the detection limit of 50 pM. If taking into account the final volume of mixture, the detection limit is calculated as lower as 6.2 pM, achieving an desirable assay ability. More strikingly, the mutant gene can be easily distinguished from the wild-type one. The proof-of-concept demonstrations reported herein is expected to promote the development and application of DNA nanomachine, showing great potential value in basic biology and medical diagnosis. Copyright © 2015 Elsevier B.V. All rights reserved.

A Unitary Anesthetic Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedula, L. Sangeetha; Brannigan, Grace; Economou, Nicoleta J.

2009-10-21

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

L Vedula; G Brannigan; N Economou

2011-12-31

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic-Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedula, L.; Brannigan, G; Economou, N

2009-01-01

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABAA receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show that apoferritinmore » also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Hybrid Neural Network and Feature Extraction Technique for Target Recognition.

DTIC Science & Technology

target features are extracted, the extracted data being evaluated in an artificial neural network to identify a target at a location within the image scene from which the different viewing angles extend.

Impaired neural structure and function contributing to autonomic symptoms in congenital central hypoventilation syndrome.

PubMed

Harper, Ronald M; Kumar, Rajesh; Macey, Paul M; Harper, Rebecca K; Ogren, Jennifer A

2015-01-01

Congenital central hypoventilation syndrome (CCHS) patients show major autonomic alterations in addition to their better-known breathing deficiencies. The processes underlying CCHS, mutations in the PHOX2B gene, target autonomic neuronal development, with frame shift extent contributing to symptom severity. Many autonomic characteristics, such as impaired pupillary constriction and poor temperature regulation, reflect parasympathetic alterations, and can include disturbed alimentary processes, with malabsorption and intestinal motility dyscontrol. The sympathetic nervous system changes can exert life-threatening outcomes, with dysregulation of sympathetic outflow leading to high blood pressure, time-altered and dampened heart rate and breathing responses to challenges, cardiac arrhythmia, profuse sweating, and poor fluid regulation. The central mechanisms contributing to failed autonomic processes are readily apparent from structural and functional magnetic resonance imaging studies, which reveal substantial cortical thinning, tissue injury, and disrupted functional responses in hypothalamic, hippocampal, posterior thalamic, and basal ganglia sites and their descending projections, as well as insular, cingulate, and medial frontal cortices, which influence subcortical autonomic structures. Midbrain structures are also compromised, including the raphe system and its projections to cerebellar and medullary sites, the locus coeruleus, and medullary reflex integrating sites, including the dorsal and ventrolateral medullary nuclei. The damage to rostral autonomic sites overlaps metabolic, affective and cognitive regulatory regions, leading to hormonal disruption, anxiety, depression, behavioral control, and sudden death concerns. The injuries suggest that interventions for mitigating hypoxic exposure and nutrient loss may provide cellular protection, in the same fashion as interventions in other conditions with similar malabsorption, fluid turnover, or hypoxic exposure.

Bi-Spectral Method for Radar Target Recognition

DTIC Science & Technology

2006-12-01

θazimuth=60° and ϕelevation=30° with HV Polarization....................................53 Figure 50 Comparison of Radar Range Profile with Actual...radar systems. A comparison of the NCTR techniques and their relative advantages and disadvantages in target recognition performance is presented. 8...32 f fR i R R c c f fi R R i R R c c A e A e A e ψ ψ π ψ ψ π ψ ψ π ψ ψ

TALE-PvuII Fusion Proteins – Novel Tools for Gene Targeting

PubMed Central

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity. PMID:24349308

The study of infrared target recognition at sea background based on visual attention computational model

NASA Astrophysics Data System (ADS)

Wang, Deng-wei; Zhang, Tian-xu; Shi, Wen-jun; Wei, Long-sheng; Wang, Xiao-ping; Ao, Guo-qing

2009-07-01

Infrared images at sea background are notorious for the low signal-to-noise ratio, therefore, the target recognition of infrared image through traditional methods is very difficult. In this paper, we present a novel target recognition method based on the integration of visual attention computational model and conventional approach (selective filtering and segmentation). The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The visual attention algorithm searches the salient regions automatically, and represented them by a set of winner points, at the same time, demonstrated the salient regions in terms of circles centered at these winner points. This provides a priori knowledge for the filtering and segmentation process. Based on the winner point, we construct a rectangular region to facilitate the filtering and segmentation, then the labeling operation will be added selectively by requirement. Making use of the labeled information, from the final segmentation result we obtain the positional information of the interested region, label the centroid on the corresponding original image, and finish the localization for the target. The cost time does not depend on the size of the image but the salient regions, therefore the consumed time is greatly reduced. The method is used in the recognition of several kinds of real infrared images, and the experimental results reveal the effectiveness of the algorithm presented in this paper.

Diagnosis of multiple system atrophy

PubMed Central

Palma, Jose-Alberto; Norcliffe-Kaufmann, Lucy; Kaufmann, Horacio

2017-01-01

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs. PMID:29111419

Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness

DOE PAGES

Vollmer, Todd; Manic, Milos; Linda, Ondrej

2013-06-01

The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfiguremore » in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.« less