Kinect-based sign language recognition of static and dynamic hand movements

Science.gov (United States)

Dalawis, Rando C.; Olayao, Kenneth Deniel R.; Ramos, Evan Geoffrey I.; Samonte, Mary Jane C.

2017-02-01

A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.

Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

Science.gov (United States)

Park, GiTae; Kim, Soowon

2013-01-01

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119

An Efficient Solution for Hand Gesture Recognition from Video Sequence

Directory of Open Access Journals (Sweden)

PRODAN, R.-C.

2012-08-01

Full Text Available The paper describes a system of hand gesture recognition by image processing for human robot interaction. The recognition and interpretation of the hand postures acquired through a video camera allow the control of the robotic arm activity: motion - translation and rotation in 3D - and tightening/releasing the clamp. A gesture dictionary was defined and heuristic algorithms for recognition were developed and tested. The system can be used for academic and industrial purposes, especially for those activities where the movements of the robotic arm were not previously scheduled, for training the robot easier than using a remote control. Besides the gesture dictionary, the novelty of the paper consists in a new technique for detecting the relative positions of the fingers in order to recognize the various hand postures, and in the achievement of a robust system for controlling robots by postures of the hands.

Digital speech processing using Matlab

CERN Document Server

Gopi, E S

2014-01-01

Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

An adaptive deep Q-learning strategy for handwritten digit recognition.

Science.gov (United States)

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

Learning through hand- or typewriting influences visual recognition of new graphic shapes: behavioral and functional imaging evidence.

Science.gov (United States)

Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Anton, Jean-Luc; Roth, Muriel; Nazarian, Bruno; Velay, Jean-Luc

2008-05-01

Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.

Enhancing spoken connected-digit recognition accuracy by error ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

nition systems have gained acceptable accuracy levels, the accuracy of recognition of current connected ... bar code and ISBN1 library code to name a few. ..... Kopec G, Bush M 1985 Network-based connected-digit recognition. IEEE Trans.

Device of Definition of Hand-Written Documents Belonging to One Executor

Directory of Open Access Journals (Sweden)

S. D. Kulik

2012-03-01

Full Text Available Results of working out of the device of definition of hand-written documents belonging to the executor of the text in Russian are presented. The device is intended for automation of work of experts and allows to solve problems of information security and search of criminals.

NUI framework based on real-time head pose estimation and hand gesture recognition

Directory of Open Access Journals (Sweden)

Kim Hyunduk

2016-01-01

Full Text Available The natural user interface (NUI is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. In this paper, we develop natural user interface framework based on two recognition module. First module is real-time head pose estimation module using random forests and second module is hand gesture recognition module, named Hand gesture Key Emulation Toolkit (HandGKET. Using the head pose estimation module, we can know where the user is looking and what the user’s focus of attention is. Moreover, using the hand gesture recognition module, we can also control the computer using the user’s hand gesture without mouse and keyboard. In proposed framework, the user’s head direction and hand gesture are mapped into mouse and keyboard event, respectively.

Connected digit speech recognition system for Malayalam language

Indian Academy of Sciences (India)

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual ...

Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

CERN Document Server

Pisharady, Pramod Kumar; Poh, Loh Ai

2014-01-01

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

An Approach for Pattern Recognition of EEG Applied in Prosthetic Hand Drive

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Xiao-Dong Zhang

2011-12-01

Full Text Available For controlling the prosthetic hand by only electroencephalogram (EEG, it has become the hot spot in robotics research to set up a direct communication and control channel between human brain and prosthetic hand. In this paper, the EEG signal is analyzed based on multi-complicated hand activities. And then, two methods of EEG pattern recognition are investigated, a neural prosthesis hand system driven by BCI is set up, which can complete four kinds of actions (arm’s free state, arm movement, hand crawl, hand open. Through several times of off-line and on-line experiments, the result shows that the neural prosthesis hand system driven by BCI is reasonable and feasible, the C-support vector classifiers-based method is better than BP neural network on the EEG pattern recognition for multi-complicated hand activities.

Using virtual data for training deep model for hand gesture recognition

Science.gov (United States)

Nikolaev, E. I.; Dvoryaninov, P. V.; Lensky, Y. Y.; Drozdovsky, N. S.

2018-05-01

Deep learning has shown real promise for the classification efficiency for hand gesture recognition problems. In this paper, the authors present experimental results for a deeply-trained model for hand gesture recognition through the use of hand images. The authors have trained two deep convolutional neural networks. The first architecture produces the hand position as a 2D-vector by input hand image. The second one predicts the hand gesture class for the input image. The first proposed architecture produces state of the art results with an accuracy rate of 89% and the second architecture with split input produces accuracy rate of 85.2%. In this paper, the authors also propose using virtual data for training a supervised deep model. Such technique is aimed to avoid using original labelled images in the training process. The interest of this method in data preparation is motivated by the need to overcome one of the main challenges of deep supervised learning: using a copious amount of labelled data during training.

Localization and Recognition of Dynamic Hand Gestures Based on Hierarchy of Manifold Classifiers

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Favorskaya, M.; Nosov, A.; Popov, A.

2015-05-01

Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case). Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset "Multi-modal Gesture Recognition Challenge 2013: Dataset and Results" including 393 dynamic hand-gestures was chosen. The proposed method yielded 84-91% recognition accuracy, in average, for restricted set of dynamic gestures.

LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

Directory of Open Access Journals (Sweden)

M. Favorskaya

2015-05-01

Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.

Hand gesture recognition in confined spaces with partial observability and occultation constraints

Science.gov (United States)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Electromyographic Grasp Recognition for a Five Fingered Robotic Hand

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Nayan M. Kakoty

2012-09-01

Full Text Available This paper presents classification of grasp types based on surface electromyographic signals. Classification is through radial basis function kernel support vector machine using sum of wavelet decomposition coefficients of the EMG signals. In a study involving six subjects, we achieved an average recognition rate of 86%. The electromyographic grasp recognition together with a 8-bit microcontroller has been employed to control a fivefingered robotic hand to emulate six grasp types used during 70% daily living activities.

Speech recognition training for enhancing written language generation by a traumatic brain injury survivor.

Science.gov (United States)

Manasse, N J; Hux, K; Rankin-Erickson, J L

2000-11-01

Impairments in motor functioning, language processing, and cognitive status may impact the written language performance of traumatic brain injury (TBI) survivors. One strategy to minimize the impact of these impairments is to use a speech recognition system. The purpose of this study was to explore the effect of mild dysarthria and mild cognitive-communication deficits secondary to TBI on a 19-year-old survivor's mastery and use of such a system-specifically, Dragon Naturally Speaking. Data included the % of the participant's words accurately perceived by the system over time, the participant's accuracy over time in using commands for navigation and error correction, and quantitative and qualitative changes in the participant's written texts generated with and without the use of the speech recognition system. Results showed that Dragon NaturallySpeaking was approximately 80% accurate in perceiving words spoken by the participant, and the participant quickly and easily mastered all navigation and error correction commands presented. Quantitatively, the participant produced a greater amount of text using traditional word processing and a standard keyboard than using the speech recognition system. Minimal qualitative differences appeared between writing samples. Discussion of factors that may have contributed to the obtained results and that may affect the generalization of the findings to other TBI survivors is provided.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

Science.gov (United States)

Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

2016-04-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

Mexican sign language recognition using normalized moments and artificial neural networks

Science.gov (United States)

Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

2014-09-01

This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

"Like the palm of my hands": Motor imagery enhances implicit and explicit visual recognition of one's own hands.

Science.gov (United States)

Conson, Massimiliano; Volpicella, Francesco; De Bellis, Francesco; Orefice, Agnese; Trojano, Luigi

2017-10-01

A key point in motor imagery literature is that judging hands in palm view recruits sensory-motor information to a higher extent than judging hands in back view, due to the greater biomechanical complexity implied in rotating hands depicted from palm than from back. We took advantage from this solid evidence to test the nature of a phenomenon known as self-advantage, i.e. the advantage in implicitly recognizing self vs. others' hand images. The self-advantage has been actually found when implicitly but not explicitly judging self-hands, likely due to dissociation between implicit and explicit body representations. However, such a finding might be related to the extent to which motor imagery is recruited during implicit and explicit processing of hand images. We tested this hypothesis in two behavioural experiments. In Experiment 1, right-handed participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. Crucially, in both experiments participants were randomly presented with hand images viewed from back or from palm. The main result of both experiments was the self-advantage when participants judged hands from palm view. This novel finding demonstrate that increasing the "motor imagery load" during processing of self vs. others' hands can elicit a self-advantage in explicit recognition tasks as well. Future studies testing the possible dissociation between implicit and explicit visual body representations should take into account the modulatory effect of motor imagery load on self-hand processing. Copyright © 2017. Published by Elsevier B.V.

Handwritten Digits Recognition Using Neural Computing

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Călin Enăchescu

2009-12-01

Full Text Available In this paper we present a method for the recognition of handwritten digits and a practical implementation of this method for real-time recognition. A theoretical framework for the neural networks used to classify the handwritten digits is also presented.The classification task is performed using a Convolutional Neural Network (CNN. CNN is a special type of multy-layer neural network, being trained with an optimized version of the back-propagation learning algorithm.CNN is designed to recognize visual patterns directly from pixel images with minimal preprocessing, being capable to recognize patterns with extreme variability (such as handwritten characters, and with robustness to distortions and simple geometric transformations.The main contributions of this paper are related to theoriginal methods for increasing the efficiency of the learning algorithm by preprocessing the images before the learning process and a method for increasing the precision and performance for real-time applications, by removing the non useful information from the background.By combining these strategies we have obtained an accuracy of 96.76%, using as training set the NIST (National Institute of Standards and Technology database.

Implementation of age and gender recognition system for intelligent digital signage

Science.gov (United States)

Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

2015-12-01

Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis.

Science.gov (United States)

Nygaard, Gro O; de Rodez Benavent, Sigrid A; Harbo, Hanne F; Laeng, Bruno; Sowa, Piotr; Damangir, Soheil; Bernhard Nilsen, Kristian; Etholm, Lars; Tønnesen, Siren; Kerty, Emilia; Drolsum, Liv; Inge Landrø, Nils; Celius, Elisabeth G

2015-11-01

Eye and hand motor dysfunction may be present early in the disease course of relapsing-remitting multiple sclerosis (RRMS), and can affect the results on visual and written cognitive tests. We aimed to test for differences in saccadic initiation time (SI time) between RRMS patients and healthy controls, and whether SI time and hand motor speed interacted with the written version of the Symbol Digit Modalities Test (wSDMT). Patients with RRMS (N = 44, age 35.1 ± 7.3 years), time since diagnosis < 3 years and matched controls (N = 41, age 33.2 ± 6.8 years) were examined with ophthalmological, neurological and neuropsychological tests, as well as structural MRI (white matter lesion load (WMLL) and brainstem lesions), visual evoked potentials (VEP) and eye-tracker examinations of saccades. SI time was longer in RRMS than controls (p < 0.05). SI time was not related to the Paced Auditory Serial Addition Test (PASAT), WMLL or to the presence of brainstem lesions. 9 hole peg test (9HP) correlated significantly with WMLL (r = 0.58, p < 0.01). Both SI time and 9HP correlated negatively with the results of wSDMT (r = -0.32, p < 0.05, r = -0.47, p < 0.01), but none correlated with the results of PASAT. RRMS patients have an increased SI time compared to controls. Cognitive tests results, exemplified by the wSDMT, may be confounded by eye and hand motor function. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Past Examination Questions in Senior Secondary Chemistry: From Written Practice to Hands-On Experiments

Science.gov (United States)

Chow, Cheuk-Fai; So, Wing-Mui Winnie; Cheung, Tsz-Yan

2016-01-01

This study applied an unconventional use of past examination papers by converting questions into hands-on experiments for students. Students in an experimental group were engaged in use of those experiments while the remainder attended conventional lectures with written practice. The results reflect that the experimental group positively improved…

Force-independent distribution of correlated neural inputs to hand muscles during three-digit grasping.

Science.gov (United States)

Poston, Brach; Danna-Dos Santos, Alessander; Jesunathadas, Mark; Hamm, Thomas M; Santello, Marco

2010-08-01

The ability to modulate digit forces during grasping relies on the coordination of multiple hand muscles. Because many muscles innervate each digit, the CNS can potentially choose from a large number of muscle coordination patterns to generate a given digit force. Studies of single-digit force production tasks have revealed that the electromyographic (EMG) activity scales uniformly across all muscles as a function of digit force. However, the extent to which this finding applies to the coordination of forces across multiple digits is unknown. We addressed this question by asking subjects (n = 8) to exert isometric forces using a three-digit grip (thumb, index, and middle fingers) that allowed for the quantification of hand muscle coordination within and across digits as a function of grasp force (5, 20, 40, 60, and 80% maximal voluntary force). We recorded EMG from 12 muscles (6 extrinsic and 6 intrinsic) of the three digits. Hand muscle coordination patterns were quantified in the amplitude and frequency domains (EMG-EMG coherence). EMG amplitude scaled uniformly across all hand muscles as a function of grasp force (muscle x force interaction: P = 0.997; cosines of angle between muscle activation pattern vector pairs: 0.897-0.997). Similarly, EMG-EMG coherence was not significantly affected by force (P = 0.324). However, coherence was stronger across extrinsic than that across intrinsic muscle pairs (P = 0.0039). These findings indicate that the distribution of neural drive to multiple hand muscles is force independent and may reflect the anatomical properties or functional roles of hand muscle groups.

Real-Time Control of an Exoskeleton Hand Robot with Myoelectric Pattern Recognition.

Science.gov (United States)

Lu, Zhiyuan; Chen, Xiang; Zhang, Xu; Tong, Kay-Yu; Zhou, Ping

2017-08-01

Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

Optimizing pattern recognition-based control for partial-hand prosthesis application.

Science.gov (United States)

Earley, Eric J; Adewuyi, Adenike A; Hargrove, Levi J

2014-01-01

Partial-hand amputees often retain good residual wrist motion, which is essential for functional activities involving use of the hand. Thus, a crucial design criterion for a myoelectric, partial-hand prosthesis control scheme is that it allows the user to retain residual wrist motion. Pattern recognition (PR) of electromyographic (EMG) signals is a well-studied method of controlling myoelectric prostheses. However, wrist motion degrades a PR system's ability to correctly predict hand-grasp patterns. We studied the effects of (1) window length and number of hand-grasps, (2) static and dynamic wrist motion, and (3) EMG muscle source on the ability of a PR-based control scheme to classify functional hand-grasp patterns. Our results show that training PR classifiers with both extrinsic and intrinsic muscle EMG yields a lower error rate than training with either group by itself (pgrasps available to the classifier significantly decrease classification error (pgrasp.

Sensitivity and specificity of a digit symbol recognition trial in the identification of response bias.

Science.gov (United States)

Kim, Nancy; Boone, Kyle B; Victor, Tara; Lu, Po; Keatinge, Carolyn; Mitchell, Cary

2010-08-01

Recently published practice standards recommend that multiple effort indicators be interspersed throughout neuropsychological evaluations to assess for response bias, which is most efficiently accomplished through use of effort indicators from standard cognitive tests already included in test batteries. The present study examined the utility of a timed recognition trial added to standard administration of the WAIS-III Digit Symbol subtest in a large sample of "real world" noncredible patients (n=82) as compared with credible neuropsychology clinic patients (n=89). Scores from the recognition trial were more sensitive in identifying poor effort than were standard Digit Symbol scores, and use of an equation incorporating Digit Symbol Age-Corrected Scaled Scores plus accuracy and time scores from the recognition trial was associated with nearly 80% sensitivity at 88.7% specificity. Thus, inclusion of a brief recognition trial to Digit Symbol administration has the potential to provide accurate assessment of response bias.

SU-F-T-20: Novel Catheter Lumen Recognition Algorithm for Rapid Digitization

Energy Technology Data Exchange (ETDEWEB)

Dise, J; McDonald, D; Ashenafi, M; Peng, J; Mart, C; Koch, N; Vanek, K [Medical University of South Carolina, Charleston, SC (United States)

2016-06-15

Purpose: Manual catheter recognition remains a time-consuming aspect of high-dose-rate brachytherapy (HDR) treatment planning. In this work, a novel catheter lumen recognition algorithm was created for accurate and rapid digitization. Methods: MatLab v8.5 was used to create the catheter recognition algorithm. Initially, the algorithm searches the patient CT dataset using an intensity based k-means filter designed to locate catheters. Once the catheters have been located, seed points are manually selected to initialize digitization of each catheter. From each seed point, the algorithm searches locally in order to automatically digitize the remaining catheter. This digitization is accomplished by finding pixels with similar image curvature and divergence parameters compared to the seed pixel. Newly digitized pixels are treated as new seed positions, and hessian image analysis is used to direct the algorithm toward neighboring catheter pixels, and to make the algorithm insensitive to adjacent catheters that are unresolvable on CT, air pockets, and high Z artifacts. The algorithm was tested using 11 HDR treatment plans, including the Syed template, tandem and ovoid applicator, and multi-catheter lung brachytherapy. Digitization error was calculated by comparing manually determined catheter positions to those determined by the algorithm. Results: he digitization error was 0.23 mm ± 0.14 mm axially and 0.62 mm ± 0.13 mm longitudinally at the tip. The time of digitization, following initial seed placement was less than 1 second per catheter. The maximum total time required to digitize all tested applicators was 4 minutes (Syed template with 15 needles). Conclusion: This algorithm successfully digitizes HDR catheters for a variety of applicators with or without CT markers. The minimal axial error demonstrates the accuracy of the algorithm, and its insensitivity to image artifacts and challenging catheter positioning. Future work to automatically place initial seed

SU-F-T-20: Novel Catheter Lumen Recognition Algorithm for Rapid Digitization

International Nuclear Information System (INIS)

Dise, J; McDonald, D; Ashenafi, M; Peng, J; Mart, C; Koch, N; Vanek, K

2016-01-01

Purpose: Manual catheter recognition remains a time-consuming aspect of high-dose-rate brachytherapy (HDR) treatment planning. In this work, a novel catheter lumen recognition algorithm was created for accurate and rapid digitization. Methods: MatLab v8.5 was used to create the catheter recognition algorithm. Initially, the algorithm searches the patient CT dataset using an intensity based k-means filter designed to locate catheters. Once the catheters have been located, seed points are manually selected to initialize digitization of each catheter. From each seed point, the algorithm searches locally in order to automatically digitize the remaining catheter. This digitization is accomplished by finding pixels with similar image curvature and divergence parameters compared to the seed pixel. Newly digitized pixels are treated as new seed positions, and hessian image analysis is used to direct the algorithm toward neighboring catheter pixels, and to make the algorithm insensitive to adjacent catheters that are unresolvable on CT, air pockets, and high Z artifacts. The algorithm was tested using 11 HDR treatment plans, including the Syed template, tandem and ovoid applicator, and multi-catheter lung brachytherapy. Digitization error was calculated by comparing manually determined catheter positions to those determined by the algorithm. Results: he digitization error was 0.23 mm ± 0.14 mm axially and 0.62 mm ± 0.13 mm longitudinally at the tip. The time of digitization, following initial seed placement was less than 1 second per catheter. The maximum total time required to digitize all tested applicators was 4 minutes (Syed template with 15 needles). Conclusion: This algorithm successfully digitizes HDR catheters for a variety of applicators with or without CT markers. The minimal axial error demonstrates the accuracy of the algorithm, and its insensitivity to image artifacts and challenging catheter positioning. Future work to automatically place initial seed

One-Dimensional Signal Extraction Of Paper-Written ECG Image And Its Archiving

Science.gov (United States)

Zhang, Zhi-ni; Zhang, Hong; Zhuang, Tian-ge

1987-10-01

A method for converting paper-written electrocardiograms to one dimensional (1-D) signals for archival storage on floppy disk is presented here. Appropriate image processing techniques were employed to remove the back-ground noise inherent to ECG recorder charts and to reconstruct the ECG waveform. The entire process consists of (1) digitization of paper-written ECGs with an image processing system via a TV camera; (2) image preprocessing, including histogram filtering and binary image generation; (3) ECG feature extraction and ECG wave tracing, and (4) transmission of the processed ECG data to IBM-PC compatible floppy disks for storage and retrieval. The algorithms employed here may also be used in the recognition of paper-written EEG or EMG and may be useful in robotic vision.

Degraded character recognition based on gradient pattern

Science.gov (United States)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

Teachers' Perceptions of Digital Badges as Recognition of Professional Development

Science.gov (United States)

Jones, W. Monty; Hope, Samantha; Adams, Brianne

2018-01-01

This mixed methods study examined teachers' perceptions and uses of digital badges received as recognition of participation in a professional development program. Quantitative and qualitative survey data was collected from 99 K-12 teachers who were awarded digital badges in Spring 2016. In addition, qualitative data was collected through…

Latin Letters Recognition Using Optical Character Recognition to Convert Printed Media Into Digital Format

Directory of Open Access Journals (Sweden)

Rio Anugrah

2017-12-01

Full Text Available Printed media is still popular now days society. Unfortunately, such media encountered several drawbacks. For example, this type of media consumes large storage that impact in high maintenance cost. To keep printed information more efficient and long-lasting, people usually convert it into digital format. In this paper, we built Optical Character Recognition (OCR system to enable automatic conversion the image containing the sentence in Latin characters into digital text-shaped information. This system consists of several interrelated stages including preprocessing, segmentation, feature extraction, classifier, model and recognition. In preprocessing, the median filter is used to clarify the image from noise and the Otsu’s function is used to binarize the image. It followed by character segmentation using connected component labeling. Artificial neural network (ANN is used for feature extraction to recognize the character. The result shows that this system enable to recognize the characters in the image whose success rate is influenced by the training of the system.

Human computer interaction using hand gestures

CERN Document Server

Premaratne, Prashan

2014-01-01

Human computer interaction (HCI) plays a vital role in bridging the 'Digital Divide', bringing people closer to consumer electronics control in the 'lounge'. Keyboards and mouse or remotes do alienate old and new generations alike from control interfaces. Hand Gesture Recognition systems bring hope of connecting people with machines in a natural way. This will lead to consumers being able to use their hands naturally to communicate with any electronic equipment in their 'lounge.' This monograph will include the state of the art hand gesture recognition approaches and how they evolved from their inception. The author would also detail his research in this area for the past 8 years and how the future might turn out to be using HCI. This monograph will serve as a valuable guide for researchers (who would endeavour into) in the world of HCI.

Shape-based hand recognition approach using the morphological pattern spectrum

Science.gov (United States)

Ramirez-Cortes, Juan Manuel; Gomez-Gil, Pilar; Sanchez-Perez, Gabriel; Prieto-Castro, Cesar

2009-01-01

We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good feature-extraction alternative for low- and medium-level hand-shape-based biometric applications.

A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies.

Science.gov (United States)

Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

2017-04-15

Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller.

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

Science.gov (United States)

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

Impact of body posture on laterality judgement and explicit recognition tasks performed on self and others' hands.

Science.gov (United States)

Conson, Massimiliano; Errico, Domenico; Mazzarella, Elisabetta; De Bellis, Francesco; Grossi, Dario; Trojano, Luigi

2015-04-01

Judgments on laterality of hand stimuli are faster and more accurate when dealing with one's own than others' hand, i.e. the self-advantage. This advantage seems to be related to activation of a sensorimotor mechanism while implicitly processing one's own hands, but not during explicit one's own hand recognition. Here, we specifically tested the influence of proprioceptive information on the self-hand advantage by manipulating participants' body posture during self and others' hand processing. In Experiment 1, right-handed healthy participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. In both experiments, the participants performed the task while holding their left or right arm flexed with their hand in direct contact with their chest ("flexed self-touch posture") or with their hand placed on a wooden smooth surface in correspondence with their chest ("flexed proprioceptive-only posture"). In an "extended control posture", both arms were extended and in contact with thighs. In Experiment 1 (hand laterality judgment), we confirmed the self-advantage and demonstrated that it was enhanced when the subjects judged left-hand stimuli at 270° orientation while keeping their left arm in the flexed proprioceptive-only posture. In Experiment 2 (explicit self-hand recognition), instead, we found an advantage for others' hand ("self-disadvantage") independently from posture manipulation. Thus, position-related proprioceptive information from left non-dominant arm can enhance sensorimotor one's own body representation selectively favouring implicit self-hands processing.

A Real-time Face/Hand Tracking Method for Chinese Sign Language Recognition

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

This paper introduces a new Chinese Sign Language recognition (CSLR) system and a method of real-time tracking face and hand applied in the system. In the method, an improved agent algorithm is used to extract the region of face and hand and track them. Kalman filter is introduced to forecast the position and rectangle of search, and self-adapting of target color is designed to counteract the effect of illumination.

Physical Principles of the Method for Determination of Geometrical Characteristics and Particle Recognition in Digital Holography

Science.gov (United States)

Dyomin, V. V.; Polovtsev, I. G.; Davydova, A. Yu.

2018-03-01

The physical principles of a method for determination of geometrical characteristics of particles and particle recognition based on the concepts of digital holography, followed by processing of the particle images reconstructed from the digital hologram, using the morphological parameter are reported. An example of application of this method for fast plankton particle recognition is given.

Digital tomosynthesis of hand joints for arthritis assessment

International Nuclear Information System (INIS)

Duryea, J.; Dobbins, J.T. III; Lynch, J.A.

2003-01-01

The two principal forms of hand arthritis, rheumatoid arthritis (RA) and osteoarthritis (OA) have large clinical and economic costs. Radiography has been shown to be a useful tool to assess the condition of the disease. A hand radiograph, however, is a two-dimensional projection of a three-dimensional object. In this report we present the results of a study that applied digital tomosynthesis to hand radiography in order to extract three-dimensional outcome measures that should be more sensitive to arthritis progression. The study was performed using simulated projection radiographs created using micro computed tomography (μCT) and a set of five dry-bone hand skeletons. These simulated projection images were then reconstructed into tomographic slices using the matrix inversion tomosynthesis (MITS) algorithm. The accuracy of the tomosynthesis reconstruction was evaluated by comparing the reconstructed images to a gold standard created using the μCT data. A parameter from image registration science, normalized mutual information, provided a quantifiable figure of merit. This study examined the effects of source displacement, number of reconstructed planes, number of acquisitions, noise added to the gray scale images, and errors in the location of a fiducial marker. We also optimized the reconstruction as a function of two variables k and α, that controlled the mixing of MITS with conventional shift-and-add tomosynthesis. A study using hand delineated joint margins demonstrated that MITS images provided a better measurement of average joint space width. We found good agreement between the MITS slices and the true planes. Both joint margins and trabecular structure were visible and the reconstructed slices showed additional structures not visible with the standard projection image. Using hand-delineated joint margins we compared the average joint space width of the gold standard slices to the MITS and projection images. A root-mean square deviation (RMSD), calculated

Film-screen vs. digital radiography in rheumatoid arthritis of the hand. An ROC analysis

International Nuclear Information System (INIS)

Jonsson, A.; Borg, A.; Hannesson, P.; Herrlin, K.; Jonsson, K.; Sloth, M.; Pettersson, H.

1994-01-01

In a prospective investigation the diagnostic accuracy of filmscreen and digital radiography in rheumatoid arthritis of hands was compared. Seventy hands of 36 patients with established rheumatoid arthritis were included in the study. Each of 11 joints in every hand was evaluated regarding the following radiologic parameters: soft tissue swelling, joint space narrowing, erosions and periarticular osteopenia. The digital images were obtained with storage phosphor image plates and evaluated in 2 forms; as digital hard-copy on film and on a monitor of an interactive workstation. The digital images had a resolution of either 3.33 or 5.0 lp/mm. ROC curves were constructed and comparing the area under the curves no significant difference was found between the 3 different imaging forms in either resolution group for soft tissue swelling, joint space narrowing and erosions. The film-screen image evaluation of periarticular osteopenia was significantly better than the digital hard-copy one in the 3.33 lp/mm resolution group, but no significant difference was found in the 5.0 lp/mm group. These results support the view that currently available digital systems are capable of adequate diagnostic performance. (orig.)

Hand Gesture Recognition Using Modified 1$ and Background Subtraction Algorithms

Directory of Open Access Journals (Sweden)

Hazem Khaled

2015-01-01

Full Text Available Computers and computerized machines have tremendously penetrated all aspects of our lives. This raises the importance of Human-Computer Interface (HCI. The common HCI techniques still rely on simple devices such as keyboard, mice, and joysticks, which are not enough to convoy the latest technology. Hand gesture has become one of the most important attractive alternatives to existing traditional HCI techniques. This paper proposes a new hand gesture detection system for Human-Computer Interaction using real-time video streaming. This is achieved by removing the background using average background algorithm and the 1$ algorithm for hand’s template matching. Then every hand gesture is translated to commands that can be used to control robot movements. The simulation results show that the proposed algorithm can achieve high detection rate and small recognition time under different light changes, scales, rotation, and background.

Fractionally Spaced Constant Modulus Equalizer with Recognition Capability for Digital Array Radar

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Feng Wang

2017-01-01

Full Text Available Fractionally spaced blind equalizer (BE based on constant modulus criteria is exploited to compensate for the channel-to-channel mismatch in a digital array radar. We apply the technique of recognition to improve the stability and reliability of the BE. The surveillance of the calibration signal and the convergence property of BE are both implemented with recognition description words. BE with cognitive capability is appropriate for the equalization of a digital array radar with thousands of channels and hundreds of working frequencies, where reliability becomes the most concerned indicator. The improvement of performance in the accidental scenarios is tested via numerical simulations with the cost of increased computational complexity.

Incremental Tensor Principal Component Analysis for Handwritten Digit Recognition

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Chang Liu

2014-01-01

Full Text Available To overcome the shortcomings of traditional dimensionality reduction algorithms, incremental tensor principal component analysis (ITPCA based on updated-SVD technique algorithm is proposed in this paper. This paper proves the relationship between PCA, 2DPCA, MPCA, and the graph embedding framework theoretically and derives the incremental learning procedure to add single sample and multiple samples in detail. The experiments on handwritten digit recognition have demonstrated that ITPCA has achieved better recognition performance than that of vector-based principal component analysis (PCA, incremental principal component analysis (IPCA, and multilinear principal component analysis (MPCA algorithms. At the same time, ITPCA also has lower time and space complexity.

Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

Science.gov (United States)

Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

2017-03-01

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

OpenAIRE

M. Favorskaya; A. Nosov; A. Popov

2015-01-01

Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin dete...

Temporary Nerve Block at Selected Digits Revealed Hand Motor Deficits in Grasping Tasks

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Aude Carteron

2016-11-01

Full Text Available Peripheral sensory feedback plays a crucial role in ensuring correct motor execution throughout hand grasp control. Previous studies utilized local anesthesia to deprive somatosensory feedback in the digits or hand, observations included sensorimotor deficits at both corticospinal and peripheral levels. However, the questions of how the disturbed and intact sensory input integrate and interact with each other to assist the motor program execution, and whether the motor coordination based on motor output variability between affected and non-affected elements (e.g., digits becomes interfered by the local sensory deficiency, have not been answered. The current study aims to investigate the effect of peripheral deafferentation through digital nerve blocks at selective digits on motor performance and motor coordination in grasp control. Our results suggested that the absence of somatosensory information induced motor deficits in hand grasp control, as evidenced by reduced maximal force production ability in both local and non-local digits, impairment of force and moment control during object lift and hold, and attenuated motor synergies in stabilizing task performance variables, namely the tangential force and moment of force. These findings implied that individual sensory input is shared across all the digits and the disturbed signal from local sensory channel(s has a more comprehensive impact on the process of the motor output execution in the sensorimotor integration process. Additionally, a feedback control mechanism with a sensation-based component resides in the formation process for the motor covariation structure.

Bridging storytelling traditions with digital technology.

Science.gov (United States)

Cueva, Melany; Kuhnley, Regina; Revels, Laura J; Cueva, Katie; Dignan, Mark; Lanier, Anne P

2013-01-01

The purpose of this project was to learn how Community Health Workers (CHWs) in Alaska perceived digital storytelling as a component of the "Path to Understanding Cancer" curriculum and as a culturally respectful tool for sharing cancer-related health messages. A pre-course written application, end-of-course written evaluation, and internet survey informed this project. Digital storytelling was included in seven 5-day cancer education courses (May 2009-2012) in which 67 CHWs each created a personal 2-3 minute cancer-related digital story. Participant-chosen digital story topics included tobacco cessation, the importance of recommended cancer screening exams, cancer survivorship, loss, grief and end-of-life comfort care, and self-care as patient care providers. All participants completed an end-of-course written evaluation. In July 2012, contact information was available for 48 participants, of whom 24 completed an internet survey. All 67 participants successfully completed a digital story which they shared and discussed with course members. On the written post-course evaluation, all participants reported that combining digital storytelling with cancer education supported their learning and was a culturally respectful way to provide health messages. Additionally, 62 of 67 CHWs reported that the course increased their confidence to share cancer information with their communities. Up to 3 years post-course, all 24 CHW survey respondents reported they had shown their digital story. Of note, 23 of 24 CHWs also reported change in their own behavior as a result of the experience. All CHWs, regardless of computer skills, successfully created a digital story as part of the cancer education course. CHWs reported that digital stories enhanced their learning and were a culturally respectful way to share cancer-related information. Digital storytelling gave the power of the media into the hands of CHWs to increase their cancer knowledge, facilitate patient and community cancer

Functional and cosmetic outcome of single-digit ray amputation in hand.

Science.gov (United States)

Bhat, A K; Acharya, A M; Narayanakurup, J K; Kumar, B; Nagpal, P S; Kamath, A

2017-12-01

To assess patient satisfaction, functional and cosmetic outcomes of single-digit ray amputation in hand and identify factors that might affect the outcome. Forty-five patients who underwent ray amputation were evaluated, 37 males and eight females whose mean age was 36.6 years ranging between 15 and 67 years. Twenty-eight patients had dominant hand involvement. Twenty-one patients underwent primary ray amputation, and 24 patients had secondary ray amputation. Eight out of the 23 patients with central digit injuries underwent transposition. Grip strength, pinch strength, tactile sensibility and functional evaluation using Result Assessment Scale (RAS) and DASH score were analysed. Cosmetic assessment was performed using visual analogue scale (VAS) for cosmesis. Median time of assessment after surgery was 20 months. Average loss of grip strength and pinch strength was found to be 43.3 and 33.6%, respectively. Average RAS score was 3.75. Median DASH score was 23.4. Eighty-three percentage of patients had excellent or good cosmesis on the VAS. Transposition causes significant increase in DASH scores for central digit ray amputations but was cosmetically superior. Middle finger ray amputation had the maximum loss of grip strength, and index finger ray amputation had greater loss of pinch strength. Affection of neighbouring digits caused greater grip and pinch loss, and a higher DASH score. Primary ray resection decreased the total disability and eliminated the costs of a second procedure. Following ray amputation, one can predict an approximate 43.3% loss of grip strength and 33.6% loss of pinch strength. The patients can be counselled regarding the expected time off from work, amount of disability and complications after a single-digit ray amputation. Majority of the patients can return to the same occupation after a period of dedicated hand therapy. Therapeutic, Level III.

A New Database of Digits Extracted from Coins with Hard-to-Segment Foreground for Optical Character Recognition Evaluation

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Xingyu Pan

2017-05-01

Full Text Available Since the release date struck on a coin is important information of its monetary type, recognition of extracted digits may assist in identification of monetary types. However, digit images extracted from coins are challenging for conventional optical character recognition methods because the foreground of such digits has very often the same color as their background. In addition, other noises, including the wear of coin metal, make it more difficult to obtain a correct segmentation of the character shape. To address those challenges, this article presents the CoinNUMS database for automatic digit recognition. The database CoinNUMS, containing 3,006 digit images, is divided into three subsets. The first subset CoinNUMS_geni consists of 606 digit images manually cropped from high-resolution photographs of well-conserved coins from GENI coin photographs; the second subset CoinNUMS_pcgs_a consists of 1,200 digit images automatically extracted from a subset of the USA_Grading numismatic database containing coins in different quality; the last subset CoinNUMS_pcgs_m consists of 1,200 digit images manually extracted from the same coin photographs as CoinNUMS_pcgs_a. In CoinNUMS_pcgs_a and CoinNUMS_pcgs_m, the digit images are extracted from the release date. In CoinNUMS_geni, the digit images can come from the cropped date, the face value, or any other legends containing digits in the coin. To show the difficulty of these databases, we have tested recognition algorithms of the literature. The database and the results of the tested algorithms will be freely available on a dedicated website.1

Surgical amputation of the digit: an investigation into the technical variations among hand surgeons.

Science.gov (United States)

Li, Andrew; Meunier, Matthew; Rennekampff, Hans-Oliver; Tenenhaus, Mayer

2013-01-01

Digital injuries are common and frequently complicate occupational hazards and trauma. The management of these injuries often necessitates digital amputation, and a variety of different amputation techniques are advocated and employed by hand surgeons. In this survey study, we investigate the variation in technical detail among a group of hand surgeons when performing digital amputations, specifically the preferred management of the residual articular cartilage, transected nerves, and phalangeal contouring. We reviewed the literature on techniques in digital amputation and created a 7-question survey that targeted controversial issues within this specific topic. We then sent this survey electronically to the members of the American Society for Surgery of the Hand and reviewed the responses of the respondents (n = 592, 20%). There was a mixed response regarding whether or not to remove the articular cartilage when disarticulating, nearly a 50% split between the respondents. Most would perform a "pull and resect" technique for transected nerves. Phalangeal contouring was generally agreed upon, though the technique in doing so varied from performing condylectomies, to bony contouring only, to some combination of both. We detected a substantial variation in technique among our group of hand surgeons regarding the treatment of articular cartilage and the method of phalangeal contouring. There was more consensus regarding the treatment of transected nerve. It is interesting that to date, the aforementioned issues in digital amputation have not been critically evaluated by definitive and well-controlled studies.

Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks

KAUST Repository

Younis, Sohaib; Weiland, Claus; Hoehndorf, Robert; Dressler, Stefan; Hickler, Thomas; Seeger, Bernhard; Schmidt, Marco

2018-01-01

Herbaria worldwide are housing a treasure of hundreds of millions of herbarium specimens, which are increasingly being digitized and thereby more accessible to the scientific community. At the same time, deep-learning algorithms are rapidly improving pattern recognition from images and these techniques are more and more being applied to biological objects. In this study, we are using digital images of herbarium specimens in order to identify taxa and traits of these collection objects by applying convolutional neural networks (CNN). Images of the 1000 species most frequently documented by herbarium specimens on GBIF have been downloaded and combined with morphological trait data, preprocessed and divided into training and test datasets for species and trait recognition. Good performance in both domains suggests substantial potential of this approach for supporting taxonomy and natural history collection management. Trait recognition is also promising for applications in functional ecology.

Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks

KAUST Repository

Younis, Sohaib

2018-03-13

Herbaria worldwide are housing a treasure of hundreds of millions of herbarium specimens, which are increasingly being digitized and thereby more accessible to the scientific community. At the same time, deep-learning algorithms are rapidly improving pattern recognition from images and these techniques are more and more being applied to biological objects. In this study, we are using digital images of herbarium specimens in order to identify taxa and traits of these collection objects by applying convolutional neural networks (CNN). Images of the 1000 species most frequently documented by herbarium specimens on GBIF have been downloaded and combined with morphological trait data, preprocessed and divided into training and test datasets for species and trait recognition. Good performance in both domains suggests substantial potential of this approach for supporting taxonomy and natural history collection management. Trait recognition is also promising for applications in functional ecology.

Effect of data compression on diagnostic accuracy in digital hand and chest radiography

Science.gov (United States)

Sayre, James W.; Aberle, Denise R.; Boechat, Maria I.; Hall, Theodore R.; Huang, H. K.; Ho, Bruce K. T.; Kashfian, Payam; Rahbar, Guita

1992-05-01

Image compression is essential to handle a large volume of digital images including CT, MR, CR, and digitized films in a digital radiology operation. The full-frame bit allocation using the cosine transform technique developed during the last few years has been proven to be an excellent irreversible image compression method. This paper describes the effect of using the hardware compression module on diagnostic accuracy in hand radiographs with subperiosteal resorption and chest radiographs with interstitial disease. Receiver operating characteristic analysis using 71 hand radiographs and 52 chest radiographs with five observers each demonstrates that there is no statistical significant difference in diagnostic accuracy between the original films and the compressed images with a compression ratio as high as 20:1.

Hand posture effects on handedness recognition as revealed by the Simon effect

Directory of Open Access Journals (Sweden)

Allan P Lameira

2009-11-01

Full Text Available We investigated the influence of hand posture in handedness recognition, while varying the spatial correspondence between stimulus and response in a modified Simon task. Drawings of the left and right hands were displayed either in a back or palm view while participants discriminated stimulus handedness by pressing left/right keys with their hands resting either in a prone or supine posture. As a control, subjects performed a regular Simon task using simple geometric shapes as stimuli. Results showed that when hands were in a prone posture, the spatially corresponding trials (i.e., stimulus and response located on the same side were faster than the non-corresponding trials (i.e., stimulus and response on opposite sides. In contrast, for the supine posture, there was no difference between corresponding and non-corresponding trials. The control experiment with the regular Simon task showed that the posture of the responding hand had no influence on performance. When the stimulus is the drawing of a hand, however, the posture of the responding hand affects the spatial correspondence effect because response location is coded based on multiple reference points, including the body of the hand.

Vascular changes of the hand in professional baseball players with emphasis on digital ischemia in catchers.

Science.gov (United States)

Ginn, T Adam; Smith, Adam M; Snyder, Jon R; Koman, L Andrew; Smith, Beth P; Rushing, Julia

2005-07-01

Repetitive trauma to the hand is a concern for baseball players. The present study investigated the effects of repetitive trauma and the prevalence of microvascular pathological changes in the hands of minor league professional baseball players. In contrast to previous investigators, we documented the presence of abnormalities in younger, asymptomatic individuals. Thirty-six baseball players on active minor league rosters underwent a history and physical examination of both hands as well as additional specialized tests, including Doppler ultrasound, a timed Allen test, determination of digital brachial pressure indices, and ring sizing of fingers. Data were compared between gloved hands and throwing hands, hitters and nonhitters, and players at four different positions (catcher [nine subjects], outfielder [seven subjects], infielder [five subjects], and pitcher [fifteen subjects]). Digital brachial indices in the ring fingers of the gloved (p healthy professional baseball players in all positions, with a significantly higher prevalence in catchers, prior to the development of clinically important ischemia. Repetitive trauma resulting from the impact of the baseball also leads to digital hypertrophy in the index finger of the gloved hand of catchers. Gloves currently used by professional catchers do not adequately protect the hand from repetitive trauma.

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

Science.gov (United States)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

Static sign language recognition using 1D descriptors and neural networks

Science.gov (United States)

Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César

2012-10-01

A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.

Dupuytren’s disease digital radius IV right hand and carpal tunnel syndrome on ipsilateral hand

Directory of Open Access Journals (Sweden)

Teona Sebe Ioana

2015-11-01

Full Text Available Dupuytren’s contracture is a fibroproliferative disease whose etiology and pathophysiology are unclear and controversial. It is a connective tissue disorder, which takes part in the palmar’s fibromatosis category and has common characteristics with the healing process. Dupuytren’s disease is characterized by the flexion contracture of the hand due to palmar and digital aponevrosis. It generally affects the 4th digital radius, followed by the 5th one. Without surgery, it leads to functional impotence of those digital rays and/or hand. It is associated with other diseases and situational conditions like Peyronie’s disease, the Lederhose disease (plantar fibromatosis, Garrod’s digital knuckle-pads, diabetes, epilepsy, alcoholism, micro traumatisms, stenosing tenosynovitis and not the least with carpal tunnel syndrome. The carpal tunnel syndrome is a peripheral neuropathy with the incarceration of the median nerve at the ARC level, expressed clinically by sensory and motor disturbances in the distribution territory of the median nerve, which cause functional limitations of daily activities of the patient. After the failure of the nonsurgical treatment or the appearance of the motor deficit, is established the open or endoscopic surgical treatment with the release of the median nerve. Postoperative recovery in both diseases is crucial to the functionality of the affected upper limb and to the quality of the patient’s life. The patient, a 61 years old man, admitted to the clinic for the functional impotence of the right hand, for the permanent flexion contracture of the metacarpophalangeal joint (MCP and proximal interphalangeal joint (PIP of the 4th finger with extension deficit, for the damage of the thumb pulp clamp of the 4th finger, for nocturnal paresthesia of fingers I-III and pain that radiates into the fingertips. After clinical, paraclinical, imagistic and electrical investigations, surgery is practiced partial aponevrectomy

Bridging storytelling traditions with digital technology

Directory of Open Access Journals (Sweden)

Melany Cueva

2013-08-01

Full Text Available Objective. The purpose of this project was to learn how Community Health Workers (CHWs in Alaska perceived digital storytelling as a component of the “Path to Understanding Cancer” curriculum and as a culturally respectful tool for sharing cancer-related health messages. Design. A pre-course written application, end-of-course written evaluation, and internet survey informed this project. Methods. Digital storytelling was included in seven 5-day cancer education courses (May 2009–2012 in which 67 CHWs each created a personal 2–3 minute cancer-related digital story. Participant-chosen digital story topics included tobacco cessation, the importance of recommended cancer screening exams, cancer survivorship, loss, grief and end-of-life comfort care, and self-care as patient care providers. All participants completed an end-of-course written evaluation. In July 2012, contact information was available for 48 participants, of whom 24 completed an internet survey. Results. All 67 participants successfully completed a digital story which they shared and discussed with course members. On the written post-course evaluation, all participants reported that combining digital storytelling with cancer education supported their learning and was a culturally respectful way to provide health messages. Additionally, 62 of 67 CHWs reported that the course increased their confidence to share cancer information with their communities. Up to 3 years post-course, all 24 CHW survey respondents reported they had shown their digital story. Of note, 23 of 24 CHWs also reported change in their own behaviour as a result of the experience. Conclusions. All CHWs, regardless of computer skills, successfully created a digital story as part of the cancer education course. CHWs reported that digital stories enhanced their learning and were a culturally respectful way to share cancer-related information. Digital storytelling gave the power of the media into the hands of CHWs

Digital knowledge in the coat pocket - hand-held personal digital assistants in radiology

International Nuclear Information System (INIS)

Niehues, S.M.; Froehlich, M.; Felix, R.; Lemke, A.J.

2004-01-01

The personal digital assistant (PDA) enables the independent access to large data in a pocket-sized format. The applications for hand-held computers are growing steadily and can support almost any kind of problem. An overview of the available hardware and software is provided and evaluated. Furthermore, the use of the PDA in the clinical daily routine is described. In view of the numerous software programs available in radiology, the range of software solutions for radiologists is presented. Despite the high acquisition cost, the PDA has already become the digital assistant for the radiologist. After a short time of getting used to the PDA, nobody wants to miss it at work or at home. New technical features and available software programs will continuously increase the integration of the PDA into the medical workflow in the near future. (orig.)

Viewpoint Integration for Hand-Based Recognition of Social Interactions from a First-Person View.

Science.gov (United States)

Bambach, Sven; Crandall, David J; Yu, Chen

2015-11-01

Wearable devices are becoming part of everyday life, from first-person cameras (GoPro, Google Glass), to smart watches (Apple Watch), to activity trackers (FitBit). These devices are often equipped with advanced sensors that gather data about the wearer and the environment. These sensors enable new ways of recognizing and analyzing the wearer's everyday personal activities, which could be used for intelligent human-computer interfaces and other applications. We explore one possible application by investigating how egocentric video data collected from head-mounted cameras can be used to recognize social activities between two interacting partners (e.g. playing chess or cards). In particular, we demonstrate that just the positions and poses of hands within the first-person view are highly informative for activity recognition, and present a computer vision approach that detects hands to automatically estimate activities. While hand pose detection is imperfect, we show that combining evidence across first-person views from the two social partners significantly improves activity recognition accuracy. This result highlights how integrating weak but complimentary sources of evidence from social partners engaged in the same task can help to recognize the nature of their interaction.

Robotic Hand-Assisted Training for Spinal Cord Injury Driven by Myoelectric Pattern Recognition: A Case Report.

Science.gov (United States)

Lu, Zhiyuan; Tong, Kai-Yu; Shin, Henry; Stampas, Argyrios; Zhou, Ping

2017-10-01

A 51-year-old man with an incomplete C6 spinal cord injury sustained 26 yrs ago attended twenty 2-hr visits over 10 wks for robot-assisted hand training driven by myoelectric pattern recognition. In each visit, his right hand was assisted to perform motions by an exoskeleton robot, while the robot was triggered by his own motion intentions. The hand robot was designed for this study, which can perform six kinds of motions, including hand closing/opening; thumb, index finger, and middle finger closing/opening; and middle, ring, and little fingers closing/opening. After the training, his grip force increased from 13.5 to 19.6 kg, his pinch force remained the same (5.0 kg), his score of Box and Block test increased from 32 to 39, and his score from the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B increased from 22 to 24. He accomplished the tasks in the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B 28.8% faster on average. The results demonstrate the feasibility and effectiveness of robot-assisted training driven by myoelectric pattern recognition after spinal cord injury.

Hand Grasping Synergies As Biometrics.

Science.gov (United States)

Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana

2017-01-01

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

Hand Grasping Synergies As Biometrics

Directory of Open Access Journals (Sweden)

Ramana Vinjamuri

2017-05-01

Full Text Available Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements. Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic. Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies—postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

Ensemble methods for handwritten digit recognition

DEFF Research Database (Denmark)

Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

1992-01-01

Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

Hand and digital ischemia due to arteriosclerosis and thromboembolization in young adults: pathologic features with clinical correlations.

Science.gov (United States)

Guarda, L A; Borrero, J L

1990-11-01

Twenty young adult patients with hand and digital ischemia were found to have obstructive arterial disease. All patients were surgically explored, and the occluded vessels were resected and by-passed. Eighteen patients had obstruction at the level of the distal ulnar artery and palmar arch, and 12 had obstruction of the common digital and digital proper arteries. Occlusive arteriosclerotic lesions were found in all patients; these lesions were characterized by prominent fibromuscular intimal plaques with superimposed thrombosis. Six patients had also thromboembolism to distal digital vessels. Vasculitis, calcifications, cholesterol deposits, and atheromatous emboli were not observed. Five patients had transmural neovascularization of the lesions in a similar manner to that described in coronary artery lesions. Obstructive lesions due to fibromuscular intimal proliferation with associated thrombosis and/or distal thromboembolization affecting arteries of hands and digits appear to be an important lesion that can affect young patients.

Hand gesture recognition by analysis of codons

Science.gov (United States)

Ramachandra, Poornima; Shrikhande, Neelima

2007-09-01

The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

Sketch Style Recognition, Transfer and Synthesis of Hand-Drawn Sketches

KAUST Repository

Shaheen, Sara

2017-07-19

Humans have always used sketches to explain the visual world. It is a simple and straight- forward mean to communicate new ideas and designs. Consequently, as in almost every aspect of our modern life, the relatively recent major developments in computer science have highly contributed to enhancing individual sketching experience. The literature of sketch related research has witnessed seminal advancements and a large body of interest- ing work. Following up with this rich literature, this dissertation provides a holistic study on sketches through three proposed novel models including sketch analysis, transfer, and geometric representation. The first part of the dissertation targets sketch authorship recognition and analysis of sketches. It provides answers to the following questions: Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? The proposed stroke authorship recognition approach is a novel method that distinguishes the authorship of 2D digitized drawings. This method converts a drawing into a histogram of stroke attributes that is discriminative of authorship. Extensive classification experiments on a large variety of datasets are conducted to validate the ability of the proposed techniques to distinguish unique authorship of artists and designers. The second part of the dissertation is concerned with sketch style transfer from one free- hand drawing to another. The proposed method exploits techniques from multi-disciplinary areas including geometrical modeling and image processing. It consists of two methods of transfer: stroke-style and brush-style transfer. (1) Stroke-style transfer aims to transfer the style of the input sketch at the stroke level to the style encountered in other sketches by other artists. This is done by modifying all the parametric stroke segments in the input, so as to minimize a global stroke-level distance between the input and

A Record Book of Open Heart Surgical Cases between 1959 and 1982, Hand-Written by a Cardiac Surgeon.

Science.gov (United States)

Kim, Won-Gon

2016-08-01

A book of brief records of open heart surgery underwent between 1959 and 1982 at Seoul National University Hospital was recently found. The book was hand-written by the late professor and cardiac surgeon Yung Kyoon Lee (1921-1994). This book contains valuable information about cardiac patients and surgery at the early stages of the establishment of open heart surgery in Korea, and at Seoul National University Hospital. This report is intended to analyze the content of the book.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Science.gov (United States)

Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

2015-01-01

A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

Effects of Isometric Hand-Grip Muscle Contraction on Young Adults' Free Recall and Recognition Memory

Science.gov (United States)

Tomporowski, Phillip D.; Albrecht, Chelesa; Pendleton, Daniel M.

2017-01-01

Purpose: The purpose of this study was to determine if physical arousal produced by isometric hand-dynamometer contraction performed during word-list learning affects young adults' free recall or recognition memory. Method: Twenty-four young adults (12 female; M[subscript age] = 22 years) were presented with 4 20-item word lists. Moderate arousal…

ZONING DESIGN FOR HAND­WRITTEN NUMERAL RECOGNITION

NARCIS (Netherlands)

Lecce Di, V.; Dimauro, G.; Guerriero, A.; Impedovo, S.; Pirlo, G.; Salzo, A.

2004-01-01

In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper zoning is considered as the result of an optimisation problem and a new technique is presented for automatic zoning. More precisely, local analysis of feature

Robust Digital Speech Watermarking For Online Speaker Recognition

Directory of Open Access Journals (Sweden)

Mohammad Ali Nematollahi

2015-01-01

Full Text Available A robust and blind digital speech watermarking technique has been proposed for online speaker recognition systems based on Discrete Wavelet Packet Transform (DWPT and multiplication to embed the watermark in the amplitudes of the wavelet’s subbands. In order to minimize the degradation effect of the watermark, these subbands are selected where less speaker-specific information was available (500 Hz–3500 Hz and 6000 Hz–7000 Hz. Experimental results on Texas Instruments Massachusetts Institute of Technology (TIMIT, Massachusetts Institute of Technology (MIT, and Mobile Biometry (MOBIO show that the degradation for speaker verification and identification is 1.16% and 2.52%, respectively. Furthermore, the proposed watermark technique can provide enough robustness against different signal processing attacks.

Diagnosis and evaluation of diseases of the hand by intravenous digital subtraction angiography done by an improved method

International Nuclear Information System (INIS)

Minakuchi, Kazuo; Nakamura, Kenji; Kudoh, Hiroaki; Takashima, Sumio; Manabe, Takao; Kaminoh, Toshio; Onoyama, Yasuto

1988-01-01

Twenty patients with various diseases of the hand were studied by intravenous digital subtraction angiography (IV-DSA). We used clay preparation as a compensatory filter to improve the radiological conditions and increased local circulation by use of a hot compress. By IV-DSA done in this way, excellent or good images of the carpal arteries were obtained in 21 of 23 hands examined (91%). For the metacarpal region, images were excellent or good for 13 hands (57%), and for the digital region, for 4 (17%). The arteries of the hand could be seen in all studies, although sometimes the image was poor. Further improvements of images by IV-DSA should make it possible to use IV-DSA for screening and follow-up studies of many parts of the body. (author)

An observational study of implicit motor imagery using laterality recognition of the hand after stroke.

Science.gov (United States)

Amesz, Sarah; Tessari, Alessia; Ottoboni, Giovanni; Marsden, Jon

2016-01-01

To explore the relationship between laterality recognition after stroke and impairments in attention, 3D object rotation and functional ability. Observational cross-sectional study. Acute care teaching hospital. Thirty-two acute and sub-acute people with stroke and 36 healthy, age-matched controls. Laterality recognition, attention and mental rotation of objects. Within the stroke group, the relationship between laterality recognition and functional ability, neglect, hemianopia and dyspraxia were further explored. People with stroke were significantly less accurate (69% vs 80%) and showed delayed reaction times (3.0 vs 1.9 seconds) when determining the laterality of a pictured hand. Deficits either in accuracy or reaction times were seen in 53% of people with stroke. The accuracy of laterality recognition was associated with reduced functional ability (R(2) = 0.21), less accurate mental rotation of objects (R(2) = 0.20) and dyspraxia (p = 0.03). Implicit motor imagery is affected in a significant number of patients after stroke with these deficits related to lesions to the motor networks as well as other deficits seen after stroke. This research provides new insights into how laterality recognition is related to a number of other deficits after stroke, including the mental rotation of 3D objects, attention and dyspraxia. Further research is required to determine if treatment programmes can improve deficits in laterality recognition and impact functional outcomes after stroke.

Qualitative Evaluation of Digital Hand X-rays is Not a Reliable Method to Assess Bone Mineral Density

Directory of Open Access Journals (Sweden)

AndrewJ. Miller

2017-01-01

Full Text Available Object: The gold standard for evaluating bone mineral density is dual energy x-ray absorptiometry (DEXA.  Prior studies have shown poor reliability using analog wrist X-rays in diagnosing osteoporosis. Our goal was to investigate if there was improved diagnostic value to visual assessment of digital hand X-rays in osteoporosis screening. We hypothesized that similar to analog counterparts, digital hand X-rays have poor correlation and reliability in determining bone mineral density (BMD relative to DEXA.Methods: We prospectively evaluated female patients older than 65 years who presented to our hand clinic with digital hand and wrist X-rays as part of their evaluation over six months. Patients who had a fracture and were without DEXA scans within the past two years were excluded. Five fellowship-trained hand surgeons, blinded to DEXA T-scores, evaluated the x-rays over two assessments separated by four weeks and classified them as osteoporotic, osteopenic, or normal BMD.  Accuracy relative to DEXA T-score, interobserver and intraobserver rates were calculated.Results: Thirty four patients met the inclusion criteria and a total of 340 x-rays reviews were performed.  The assessments were correct in 169 cases (49% as compared to the DEXA T-scores. A mean weighted kappa coefficient of agreement between observers was 0.29 (range 0.02-0.41 reflecting a fair agreement. The first and second assessment for all five physicians was 0.46 (range 0.19-0.78 reflecting a moderate agreement.  Grouping osteoporosis and osteopenia together compared to normal, the accuracy, interobserver and intraobserver rates increased to 63%, 0.42 and 0.54 respectively.Conclusion: Abnormally low BMD is a common occurrence in patients treated for upper extremity disorders. There is poor accuracy relative to DEXA scan and only fair agreement in diagnosing osteoporosis using visual assessments of digital x-rays.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Directory of Open Access Journals (Sweden)

Jiangyi Qin

Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

New Digital Approach to CNN On-chip Implementation for Pattern Recognition

OpenAIRE

Durackova, Daniela

2008-01-01

We developed a novel simulator for the CNN using the program tool Visual Basic for Application. Its algorithm is based on the same principle as the planned designed circuit. The network can process the patterns with 400 point recognition. The created universal simulator can change various simulation parameters. We found that the rounding at multiplication is not as important as we previously expected. On the basis of the simulations we designed a novel digital CNN cell implemented on a chip. ...

The role of hand drawing in basic design education in the digital age

NARCIS (Netherlands)

Have, R.; Van den Toorn, M.W.M.

2012-01-01

In the last decennia, hand drawing has been slowly moved out of the curricula in architecture schools and the teaching of computer skills has taken over. It has also created an 'intellectual dichotomy of viewpoints'; the digital and analogues. The question now is how to find a new balance for

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

Science.gov (United States)

Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

2015-11-01

This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

Science.gov (United States)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

29 CFR 100.610 - Written demand for payment.

Science.gov (United States)

2010-07-01

... Procedures § 100.610 Written demand for payment. (a) The NLRB will promptly make written demand upon the debtor for payment of money or the return of specific property. The written demand for payment will be... late charges will be 60 days from the date that the demand letter is mailed or hand-delivered. (b) The...

Your fate is in your hands? Handedness, digit ratio (2D:4D), and selection to a national talent development system.

Science.gov (United States)

Baker, Joseph; Kungl, Ann-Marie; Pabst, Jan; Strauß, Bernd; Büsch, Dirk; Schorer, Jörg

2013-01-01

Over the past decade a small evidence base has highlighted the potential importance of seemingly innocuous variables related to one's hands, such as hand dominance and the relative length of the second and fourth digits (2D:4D ratio), to success in sport. This study compared 2D:4D digit ratio and handedness among handball players selected to advance in a national talent development system with those not selected. Participants included 480 youth handball players (240 females and 240 males) being considered as part of the talent selection programme for the German Youth National team. Hand dominance and digit ratio were compared to age-matched control data using standard t-tests. There was a greater proportion of left-handers compared to the normal population in males but not in females. There was also a lower digit ratio in both females and males. However, there were no differences between those selected for the next stage of talent development and those not selected on either handedness or digit ratio. These results add support for general effects for both digit ratio and handedness in elite handball; however, these factors seem inadequate to explain talent selection decisions at this level.

Performance Comparison of Several Pre-Processing Methods in a Hand Gesture Recognition System based on Nearest Neighbor for Different Background Conditions

Directory of Open Access Journals (Sweden)

Iwan Setyawan

2012-12-01

Full Text Available This paper presents a performance analysis and comparison of several pre-processing methods used in a hand gesture recognition system. The pre-processing methods are based on the combinations of several image processing operations, namely edge detection, low pass filtering, histogram equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possible classes. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.

Universal Robot Hand Equipped with Tactile and Joint Torque Sensors: Development and Experiments on Stiffness Control and Object Recognition

Directory of Open Access Journals (Sweden)

Hiroyuki NAKAMOTO

2007-04-01

Full Text Available Various humanoid robots have been developed and multifunction robot hands which are able to attach those robots like human hand is needed. But a useful robot hand has not been depeveloped, because there are a lot of problems such as control method of many degrees of freedom and processing method of enormous sensor outputs. Realizing such robot hand, we have developed five-finger robot hand. In this paper, the detailed structure of developed robot hand is described. The robot hand we developed has five fingers of multi-joint that is equipped with joint torque sensors and tactile sensors. We report experimental results of a stiffness control with the developed robot hand. Those results show that it is possible to change the stiffness of joints. Moreover we propose an object recognition method with the tactile sensor. The validity of that method is assured by experimental results.

Digital fringe projection for hand surface coordinate variation analysis caused by osteoarthritis

Science.gov (United States)

Nor Haimi, Wan Mokhdzani Wan; Hau Tan, Cheek; Retnasamy, Vithyacharan; Vairavan, Rajendaran; Sauli, Zaliman; Roshidah Yusof, Nor; Hambali, Nor Azura Malini Ahmad; Aziz, Muhammad Hafiz Ab; Bakhit, Ahmad Syahir Ahmad

2017-11-01

Hand osteoarthritis is one of the most common forms of arthritis which impact millions of people worldwide. The disabling problem occurs when the protective cartilage on the boundaries of bones wear off over time. Currently, in order to identify hand osteoarthritis, special instruments namely X-ray scanning and MRI are used for the detection but it also has its limitations such as radiation exposure and can be quite costly. In this work, an optical metrology system based on digital fringe projection which comprises of an LCD projector, CCD camera and a personal computer has been developed to anticipate abnormal growth or deformation on the joints of the hand which are common symptoms of osteoarthritis. The main concept of this optical metrology system is to apply structured light as imaging source for surface change detection. The imaging source utilizes fringe patterns generated by C++ programming and is shifted by 3 phase shifts based on the 3 steps 2 shifts method. Phase wrapping technique and analysis were applied in order to detect the deformation of live subjects. The result has demonstrated a successful method of hand deformation detection based on the pixel tracking differences of a normal and deformed state.

Performance Comparison of Several Pre-Processing Methods in a Hand Gesture Recognition System based on Nearest Neighbor for Different Background Conditions

Directory of Open Access Journals (Sweden)

Regina Lionnie

2013-09-01

Full Text Available This paper presents a performance analysis and comparison of several pre-processing  methods  used  in  a  hand  gesture  recognition  system.  The  preprocessing methods are based on the combinations ofseveral image processing operations,  namely  edge  detection,  low  pass  filtering,  histogram  equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possibleclasses. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.

A mechatronics platform to study prosthetic hand control using EMG signals.

Science.gov (United States)

Geethanjali, P

2016-09-01

In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time

Hand Gesture Modeling and Recognition for Human and Robot Interactive Assembly Using Hidden Markov Models

Directory of Open Access Journals (Sweden)

Fei Chen

2015-04-01

Full Text Available Gesture recognition is essential for human and robot collaboration. Within an industrial hybrid assembly cell, the performance of such a system significantly affects the safety of human workers. This work presents an approach to recognizing hand gestures accurately during an assembly task while in collaboration with a robot co-worker. We have designed and developed a sensor system for measuring natural human-robot interactions. The position and rotation information of a human worker's hands and fingertips are tracked in 3D space while completing a task. A modified chain-code method is proposed to describe the motion trajectory of the measured hands and fingertips. The Hidden Markov Model (HMM method is adopted to recognize patterns via data streams and identify workers' gesture patterns and assembly intentions. The effectiveness of the proposed system is verified by experimental results. The outcome demonstrates that the proposed system is able to automatically segment the data streams and recognize the gesture patterns thus represented with a reasonable accuracy ratio.

Evidence for a Limited-Cascading Account of Written Word Naming

Science.gov (United States)

Bonin, Patrick; Roux, Sebastien; Barry, Christopher; Canell, Laura

2012-01-01

We address the issue of how information flows within the written word production system by examining written object-naming latencies. We report 4 experiments in which we manipulate variables assumed to have their primary impact at the level of object recognition (e.g., quality of visual presentation of pictured objects), at the level of semantic…

Adding Value to the University of Oklahoma Libraries History of Science Collections through Digital Enhancement

Directory of Open Access Journals (Sweden)

Maura Valentino

2014-03-01

Full Text Available Much of the focus of digital collections has been and continues to be on rare and unique materials, including monographs.   A monograph may be made even rarer and more valuable by virtue of hand written marginalia.   Using technology to enhance scans of unique books and make previously unreadable marginalia readable increases the value of a digital object to researchers.  This article describes a case study of enhancing the marginalia in a rare book by Copernicus.

Hand Gesture Recognition Using Ultrasonic Waves

KAUST Repository

AlSharif, Mohammed Hussain

2016-01-01

estimation of the moving hand and received signal strength (RSS). These two factors are estimated using two simple methods; channel impulse response (CIR) and cross correlation (CC) of the reflected ultrasonic signal from the gesturing hand. A customized

Digital field mapping for stimulating Secondary School students in the recognition of geological features and landforms

Science.gov (United States)

Giardino, Marco; Magagna, Alessandra; Ferrero, Elena; Perrone, Gianluigi

2015-04-01

Digital field mapping has certainly provided geoscientists with the opportunity to map and gather data in the field directly using digital tools and software rather than using paper maps, notebooks and analogue devices and then subsequently transferring the data to a digital format for subsequent analysis. But, the same opportunity has to be recognized for Geoscience education, as well as for stimulating and helping students in the recognition of landforms and interpretation of the geological and geomorphological components of a landscape. More, an early exposure to mapping during school and prior to university can optimise the ability to "read" and identify uncertainty in 3d models. During 2014, about 200 Secondary School students (aged 12-15) of the Piedmont region (NW Italy) participated in a research program involving the use of mobile devices (smartphone and tablet) in the field. Students, divided in groups, used the application Trimble Outdoors Navigators for tracking a geological trail in the Sangone Valley and for taking georeferenced pictures and notes. Back to school, students downloaded the digital data in a .kml file for the visualization on Google Earth. This allowed them: to compare the hand tracked trail on a paper map with the digital trail, and to discuss about the functioning and the precision of the tools; to overlap a digital/semitransparent version of the 2D paper map (a Regional Technical Map) used during the field trip on the 2.5D landscape of Google Earth, as to help them in the interpretation of conventional symbols such as contour lines; to perceive the landforms seen during the field trip as a part of a more complex Pleistocene glacial landscape; to understand the classical and innovative contributions from different geoscientific disciplines to the generation of a 3D structural geological model of the Rivoli-Avigliana Morainic Amphitheatre. In 2013 and 2014, some other pilot projects have been carried out in different areas of the

A comparative study between MFCC and LSF coefficients in automatic recognition of isolated digits pronounced in Portuguese and English - doi: 10.4025/actascitechnol.v35i4.19825

Directory of Open Access Journals (Sweden)

Diego Furtado Silva

2013-10-01

Full Text Available Recognition of isolated spoken digits is the core procedure for a large number of applications which rely solely on speech for data exchange, as in telephone-based services, such as dialing, airline reservation, bank transaction and price quotation. Spoken digit recognition is generally a challenging task since the signals last for a short period of time and often some digits are acoustically very similar to other digits. The objective of this paper is to investigate the use of machine learning algorithms for spoken digit recognition and disclose the free availability of a database with digits pronounced in English and Portuguese to the scientific community. Since machine learning algorithms are fully dependent on predictive attributes to build precise classifiers, we believe that the most important task for successfully recognizing spoken digits is feature extraction. In this work, we show that Line Spectral Frequencies (LSF provide a set of highly predictive coefficients. We evaluated our classifiers in different settings by altering the sampling rate to simulate low quality channels and varying the number of coefficients.  

Robotic Hand

Science.gov (United States)

1993-01-01

The Omni-Hand was developed by Ross-Hime Designs, Inc. for Marshall Space Flight Center (MSFC) under a Small Business Innovation Research (SBIR) contract. The multiple digit hand has an opposable thumb and a flexible wrist. Electric muscles called Minnacs power wrist joints and the interchangeable digits. Two hands have been delivered to NASA for evaluation for potential use on space missions and the unit is commercially available for applications like hazardous materials handling and manufacturing automation. Previous SBIR contracts resulted in the Omni-Wrist and Omni-Wrist II robotic systems, which are commercially available for spray painting, sealing, ultrasonic testing, as well as other uses.

Hand and foot pressures in the aye-aye (Daubentonia madagascariensis) reveal novel biomechanical trade-offs required for walking on gracile digits.

Science.gov (United States)

Kivell, Tracy L; Schmitt, Daniel; Wunderlich, Roshna E

2010-05-01

Arboreal animals with prehensile hands must balance the complex demands of bone strength, grasping and manipulation. An informative example of this problem is that of the aye-aye (Daubentonia madagascariensis), a rare lemuriform primate that is unusual in having exceptionally long, gracile fingers specialized for foraging. In addition, they are among the largest primates to engage in head-first descent on arboreal supports, a posture that should increase loads on their gracile digits. We test the hypothesis that aye-ayes will reduce pressure on their digits during locomotion by curling their fingers off the substrate. This hypothesis was tested using simultaneous videographic and pressure analysis of the hand, foot and digits for five adult aye-ayes during horizontal locomotion and during ascent and descent on a 30 degrees instrumented runway. Aye-ayes consistently curled their fingers during locomotion on all slopes. When the digits were in contact with the substrate, pressures were negligible and significantly less than those experienced by the palm or pedal digits. In addition, aye-ayes lifted their hands vertically off the substrate instead of 'toeing-off' and descended head-first at significantly slower speeds than on other slopes. Pressure on the hand increased during head-first descent relative to horizontal locomotion but not as much as the pressure increased on the foot during ascent. This distribution of pressure suggests that aye-ayes shift their weight posteriorly during head-first descent to reduce loads on their gracile fingers. This research demonstrates several novel biomechanical trade-offs to deal with complex functional demands on the mammalian skeleton.

Investigating the Learning Challenges Presented by Digital Technologies to the College of Education in Kuwait University

Science.gov (United States)

Aldhafeeri, Fayiz; Male, Trevor

2016-01-01

There is now widespread recognition that digital technologies, particularly portable hand held devices capable of Internet connection, present opportunities and challenges to the way in which student learning is organized in schools, colleges and institutions of higher education in the 21st Century. Traxler, "Journal of the Research Centre…

Coordination of intrinsic and extrinsic hand muscle activity as a function of wrist joint angle during two-digit grasping.

Science.gov (United States)

Johnston, Jamie A; Bobich, Lisa R; Santello, Marco

2010-04-26

Fingertip forces result from the activation of muscles that cross the wrist and muscles whose origins and insertions reside within the hand (extrinsic and intrinsic hand muscles, respectively). Thus, tasks that involve changes in wrist angle affect the moment arm and length, hence the force-producing capabilities, of extrinsic muscles only. If a grasping task requires the exertion of constant fingertip forces, the Central Nervous System (CNS) may respond to changes in wrist angle by modulating the neural drive to extrinsic or intrinsic muscles only or by co-activating both sets of muscles. To distinguish between these scenarios, we recorded electromyographic (EMG) activity of intrinsic and extrinsic muscles of the thumb and index finger as a function of wrist angle during a two-digit object hold task. We hypothesized that changes in wrist angle would elicit EMG amplitude modulation of the extrinsic and intrinsic hand muscles. In one experimental condition we asked subjects to exert the same digit forces at each wrist angle, whereas in a second condition subjects could choose digit forces for holding the object. EMG activity was significantly modulated in both extrinsic and intrinsic muscles as a function of wrist angle (both pextrinsic and intrinsic muscles as a muscle synergy. These findings are discussed within the theoretical frameworks of synergies and common neural input across motor nuclei of hand muscles. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

The Avocado Hand

LENUS (Irish Health Repository)

Rahmani, G

2017-11-01

Accidental self-inflicted knife injuries to digits are a common cause of tendon and nerve injury requiring hand surgery. There has been an apparent increase in avocado related hand injuries. Classically, the patients hold the avocado in their non-dominant hand while using a knife to cut\\/peel the fruit with their dominant hand. The mechanism of injury is usually a stabbing injury to the non-dominant hand as the knife slips past the stone, through the soft avocado fruit. Despite their apparent increased incidence, we could not find any cases in the literature which describe the “avocado hand”. We present a case of a 32-year-old woman who sustained a significant hand injury while preparing an avocado. She required exploration and repair of a digital nerve under regional anaesthesia and has since made a full recovery.

Handling movement epenthesis and hand segmentation ambiguities in continuous sign language recognition using nested dynamic programming.

Science.gov (United States)

Yang, Ruiduo; Sarkar, Sudeep; Loeding, Barbara

2010-03-01

We consider two crucial problems in continuous sign language recognition from unaided video sequences. At the sentence level, we consider the movement epenthesis (me) problem and at the feature level, we consider the problem of hand segmentation and grouping. We construct a framework that can handle both of these problems based on an enhanced, nested version of the dynamic programming approach. To address movement epenthesis, a dynamic programming (DP) process employs a virtual me option that does not need explicit models. We call this the enhanced level building (eLB) algorithm. This formulation also allows the incorporation of grammar models. Nested within this eLB is another DP that handles the problem of selecting among multiple hand candidates. We demonstrate our ideas on four American Sign Language data sets with simple background, with the signer wearing short sleeves, with complex background, and across signers. We compared the performance with Conditional Random Fields (CRF) and Latent Dynamic-CRF-based approaches. The experiments show more than 40 percent improvement over CRF or LDCRF approaches in terms of the frame labeling rate. We show the flexibility of our approach when handling a changing context. We also find a 70 percent improvement in sign recognition rate over the unenhanced DP matching algorithm that does not accommodate the me effect.

Bone age assessment in Hispanic children: digital hand atlas compared with the Greulich and Pyle (G&P) atlas

Science.gov (United States)

Fernandez, James Reza; Zhang, Aifeng; Vachon, Linda; Tsao, Sinchai

2008-03-01

Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P) book atlas, which was developed in the 1950s. The population of theUnited States is not as homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18 years was collected from Children's Hospital Los Angeles. Statistical analysis discovered significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand and wrist computed radiography images using either the G&P pediatric radiographic atlas or the Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual reading begins. Statistical analysis of the results was then performed to determine if a discrepancy exists between the two readings.

Design, data, and theory regarding a digital hand inclinometer: a portable device for studying slant perception.

Science.gov (United States)

Li, Zhi; Durgin, Frank H

2011-06-01

Palm boards are often used as a nonverbal measure in human slant perception studies. It was recently found that palm boards are biased and relatively insensitive measures, and that an unrestricted hand gesture provides a more sensitive response (Durgin, Hajnal, Li, Tonge, & Stigliani, Acta Psychologica, 134, 182-197, 2010a). In this article, we describe an original design for a portable lightweight digital device for measuring hand orientation. This device is microcontroller-based and uses a micro inclinometer chip as its inclination sensor. The parts are fairly inexpensive. This device, used to measure hand orientation, provides a sensitive nonverbal method for studying slant perception, which can be used in both indoor and outdoor environments. We present data comparing the use of a free hand to palm-board and verbal measures for surfaces within reach and explain how to interpret free-hand measures for outdoor hills.

Deep Visual Attributes vs. Hand-Crafted Audio Features on Multidomain Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Michalis Papakostas

2017-06-01

Full Text Available Emotion recognition from speech may play a crucial role in many applications related to human–computer interaction or understanding the affective state of users in certain tasks, where other modalities such as video or physiological parameters are unavailable. In general, a human’s emotions may be recognized using several modalities such as analyzing facial expressions, speech, physiological parameters (e.g., electroencephalograms, electrocardiograms etc. However, measuring of these modalities may be difficult, obtrusive or require expensive hardware. In that context, speech may be the best alternative modality in many practical applications. In this work we present an approach that uses a Convolutional Neural Network (CNN functioning as a visual feature extractor and trained using raw speech information. In contrast to traditional machine learning approaches, CNNs are responsible for identifying the important features of the input thus, making the need of hand-crafted feature engineering optional in many tasks. In this paper no extra features are required other than the spectrogram representations and hand-crafted features were only extracted for validation purposes of our method. Moreover, it does not require any linguistic model and is not specific to any particular language. We compare the proposed approach using cross-language datasets and demonstrate that it is able to provide superior results vs. traditional ones that use hand-crafted features.

Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

Science.gov (United States)

Bai, Hao; Zhang, Xi-wen

2017-06-01

While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

Effects of Carpal Tunnel Syndrome on adaptation of multi-digit forces to object mass distribution for whole-hand manipulation

Directory of Open Access Journals (Sweden)

Zhang Wei

2012-11-01

Full Text Available Abstract Background Carpal tunnel syndrome (CTS is a compression neuropathy of the median nerve that results in sensorimotor deficits in the hand. Until recently, the effects of CTS on hand function have been studied using mostly two-digit grip tasks. The purpose of this study was to investigate the coordination of multi-digit forces as a function of object center of mass (CM during whole-hand grasping. Methods Fourteen CTS patients and age- and gender-matched controls were instructed to grasp, lift, hold, and release a grip device with five digits for seven consecutive lifts while maintaining its vertical orientation. The object CM was changed by adding a mass at different locations at the base of the object. We measured forces and torques exerted by each digit and object kinematics and analyzed modulation of these variables to object CM at object lift onset and during object hold. Our task requires a modulation of digit forces at and after object lift onset to generate a compensatory moment to counteract the external moment caused by the added mass and to minimize object tilt. Results We found that CTS patients learned to generate a compensatory moment and minimized object roll to the same extent as controls. However, controls fully exploited the available degrees of freedom (DoF in coordinating their multi-digit forces to generate a compensatory moment, i.e., digit normal forces, tangential forces, and the net center of pressure on the finger side of the device at object lift onset and during object hold. In contrast, patients modulated only one of these DoFs (the net center of pressure to object CM by modulating individual normal forces at object lift onset. During object hold, however, CTS patients were able to modulate digit tangential force distribution to object CM. Conclusions Our findings suggest that, although CTS did not affect patients’ ability to perform our manipulation task, it interfered with the modulation of specific grasp

Parametric Primitives for Hand Gesture Recognition

DEFF Research Database (Denmark)

Baby, Sanmohan; Krüger, Volker

2009-01-01

Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper  an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding...

Non Audio-Video gesture recognition system

DEFF Research Database (Denmark)

Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis

2016-01-01

Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...

The hand of birds revealed by early ostrich embryos

Science.gov (United States)

Feduccia, Alan; Nowicki, Julie

2002-08-01

The problem of resolving the homology of the digits of the avian hand has been framed as a conflict between paleontological and embryological evidence, the former thought to support a hand composed of digits I, II, III, because of similarity of the phalangeal formulae of the earliest known bird Archaeopteryx to that of Mesozoic pentadactyl archosaurs, while embryological evidence has traditionally favored a II, III, IV avian hand. We have identified the critical developmental period for the major features of the avian skeleton in a primitive bird, the ostrich. Analysis of digit anlagen in the avian hand has revealed those for digits/metacarpals I and V, thus confirming previous embryological studies that indirectly suggested that the avian hand comprises digits II, III, IV, and was primitively pentadactyl.

X-ray film digitization using a personal computer and hand-held scanner: a simple technique for storing images

International Nuclear Information System (INIS)

Munoz-Nunez, C. F.; Lloret-Alcaniz, A.

1998-01-01

To develop a simple, low-cost technique for the digitization of X-ray films for personal use. A 66-MHz 486 PC with 8 MB of RAM, a Logitech ScanMan 256 hand-held scanner and a standard negatoscope with the power source converted to direct current. Although the system was originally designed for the digitization of mammographies, it has also been used with computed tomography, magnetic resonance, digital angiography and ultrasonographic images, as well as plain X-rays. After a minimal training period, the system digitized X-ray films easily and rapidly. Although the scanning values vary depending on the type of image to be digitized, an input spatial resolution of 200 dpi and a contrast resolution of 256 levels of gray are generally adequate. Of the storage formats tested, JPEG presented the best quality/image size ratio. A simple, low-cost technique has been developed for the digitization of X-ray films. This technique enables the storage of images in a digital format, thus facilitating their presentation and transmission. (Author) 9 refs

When Passive Feels Active--Delusion-Proneness Alters Self-Recognition in the Moving Rubber Hand Illusion.

Science.gov (United States)

Louzolo, Anaïs; Kalckert, Andreas; Petrovic, Predrag

2015-01-01

Psychotic patients have problems with bodily self-recognition such as the experience of self-produced actions (sense of agency) and the perception of the body as their own (sense of ownership). While it has been shown that such impairments in psychotic patients can be explained by hypersalient processing of external sensory input it has also been suggested that they lack normal efference copy in voluntary action. However, it is not known how problems with motor predictions like efference copy contribute to impaired sense of agency and ownership in psychosis or psychosis-related states. We used a rubber hand illusion based on finger movements and measured sense of agency and ownership to compute a bodily self-recognition score in delusion-proneness (indexed by Peters' Delusion Inventory - PDI). A group of healthy subjects (n=71) experienced active movements (involving motor predictions) or passive movements (lacking motor predictions). We observed a highly significant correlation between delusion-proneness and self-recognition in the passive conditions, while no such effect was observed in the active conditions. This was seen for both ownership and agency scores. The result suggests that delusion-proneness is associated with hypersalient external input in passive conditions, resulting in an abnormal experience of the illusion. We hypothesize that this effect is not present in the active condition because deficient motor predictions counteract hypersalience in psychosis proneness.

Recognition of tennis serve performed by a digital player: comparison among polygon, shadow, and stick-figure models.

Directory of Open Access Journals (Sweden)

Hirofumi Ida

Full Text Available The objective of this study was to assess the cognitive effect of human character models on the observer's ability to extract relevant information from computer graphics animation of tennis serve motions. Three digital human models (polygon, shadow, and stick-figure were used to display the computationally simulated serve motions, which were perturbed at the racket-arm by modulating the speed (slower or faster of one of the joint rotations (wrist, elbow, or shoulder. Twenty-one experienced tennis players and 21 novices made discrimination responses about the modulated joint and also specified the perceived swing speeds on a visual analogue scale. The result showed that the discrimination accuracies of the experienced players were both above and below chance level depending on the modulated joint whereas those of the novices mostly remained at chance or guessing levels. As far as the experienced players were concerned, the polygon model decreased the discrimination accuracy as compared with the stick-figure model. This suggests that the complicated pictorial information may have a distracting effect on the recognition of the observed action. On the other hand, the perceived swing speed of the perturbed motion relative to the control was lower for the stick-figure model than for the polygon model regardless of the skill level. This result suggests that the simplified visual information can bias the perception of the motion speed toward slower. It was also shown that the increasing the joint rotation speed increased the perceived swing speed, although the resulting racket velocity had little correlation with this speed sensation. Collectively, observer's recognition of the motion pattern and perception of the motion speed can be affected by the pictorial information of the human model as well as by the perturbation processing applied to the observed motion.

Recognition of tennis serve performed by a digital player: comparison among polygon, shadow, and stick-figure models.

Science.gov (United States)

Ida, Hirofumi; Fukuhara, Kazunobu; Ishii, Motonobu

2012-01-01

The objective of this study was to assess the cognitive effect of human character models on the observer's ability to extract relevant information from computer graphics animation of tennis serve motions. Three digital human models (polygon, shadow, and stick-figure) were used to display the computationally simulated serve motions, which were perturbed at the racket-arm by modulating the speed (slower or faster) of one of the joint rotations (wrist, elbow, or shoulder). Twenty-one experienced tennis players and 21 novices made discrimination responses about the modulated joint and also specified the perceived swing speeds on a visual analogue scale. The result showed that the discrimination accuracies of the experienced players were both above and below chance level depending on the modulated joint whereas those of the novices mostly remained at chance or guessing levels. As far as the experienced players were concerned, the polygon model decreased the discrimination accuracy as compared with the stick-figure model. This suggests that the complicated pictorial information may have a distracting effect on the recognition of the observed action. On the other hand, the perceived swing speed of the perturbed motion relative to the control was lower for the stick-figure model than for the polygon model regardless of the skill level. This result suggests that the simplified visual information can bias the perception of the motion speed toward slower. It was also shown that the increasing the joint rotation speed increased the perceived swing speed, although the resulting racket velocity had little correlation with this speed sensation. Collectively, observer's recognition of the motion pattern and perception of the motion speed can be affected by the pictorial information of the human model as well as by the perturbation processing applied to the observed motion.

Auditory Modeling for Noisy Speech Recognition

National Research Council Canada - National Science Library

2000-01-01

... digital filtering for noise cancellation which interfaces to speech recognition software. It uses auditory features in speech recognition training, and provides applications to multilingual spoken language translation...

Establishing CAD/CAM in Preclinical Dental Education: Evaluation of a Hands-On Module.

Science.gov (United States)

Schwindling, Franz Sebastian; Deisenhofer, Ulrich Karl; Porsche, Monika; Rammelsberg, Peter; Kappel, Stefanie; Stober, Thomas

2015-10-01

The aim of this study was to evaluate a hands-on computer-assisted design/computer-assisted manufacture (CAD/CAM) module in a preclinical dental course in restorative dentistry. A controlled trial was conducted by dividing a class of 56 third-year dental students in Germany into study and control groups; allocation to the two groups depended on student schedules. Prior information about CAD/CAM-based restorations was provided for all students by means of lectures, preparation exercises, and production of gypsum casts of prepared resin teeth. The study group (32 students) then participated in a hands-on CAD/CAM module in small groups, digitizing their casts and designing zirconia frameworks for single crowns. The digitization process was introduced to the control group (24 students) solely by means of a video-supported lecture. To assess the knowledge gained, a 20-question written examination was administered; 48 students took the exam. The results were analyzed with Student's t-tests at a significance level of 0.05. The results on the examination showed a significant difference between the two groups: the mean scores were 16.8 (SD 1.7, range 13-19) for the study group and 12.5 (SD 3, range 4-18) for the control group. After the control group had also experienced the hands-on module, a total of 48 students from both groups completed a questionnaire with 13 rating-scale and three open-ended questions evaluating the module. Those results showed that the module was highly regarded by the students. This study supports the idea that small-group hands-on courses are helpful for instruction in digital restoration design. These students' knowledge gained and satisfaction seemed to justify the time, effort, and equipment needed.

Digital-flight-control-system software written in automated-engineering-design language: A user's guide of verification and validation tools

Science.gov (United States)

Saito, Jim

1987-01-01

The user guide of verification and validation (V&V) tools for the Automated Engineering Design (AED) language is specifically written to update the information found in several documents pertaining to the automated verification of flight software tools. The intent is to provide, in one document, all the information necessary to adequately prepare a run to use the AED V&V tools. No attempt is made to discuss the FORTRAN V&V tools since they were not updated and are not currently active. Additionally, the current descriptions of the AED V&V tools are contained and provides information to augment the NASA TM 84276. The AED V&V tools are accessed from the digital flight control systems verification laboratory (DFCSVL) via a PDP-11/60 digital computer. The AED V&V tool interface handlers on the PDP-11/60 generate a Univac run stream which is transmitted to the Univac via a Remote Job Entry (RJE) link. Job execution takes place on the Univac 1100 and the job output is transmitted back to the DFCSVL and stored as a PDP-11/60 printfile.

Digitization of Full-Text Documents Before Publishing on the Internet: A Case Study Reviewing the Latest Optical Character Recognition Technologies.

Science.gov (United States)

McClean, Clare M.

1998-01-01

Reviews strengths and weaknesses of five optical character recognition (OCR) software packages used to digitize paper documents before publishing on the Internet. Outlines options available and stages of the conversion process. Describes the learning experience of Eurotext, a United Kingdom-based electronic libraries project (eLib). (PEN)

Comparative implementation of Handwritten and Machine written Gurmukhi text utilizing appropriate parameters

Science.gov (United States)

Kaur, Jaswinder; Jagdev, Gagandeep, Dr.

2018-01-01

Optical character recognition is concerned with the recognition of optically processed characters. The recognition is done offline after the writing or printing has been completed, unlike online recognition where the computer has to recognize the characters instantly as they are drawn. The performance of character recognition depends upon the quality of scanned documents. The preprocessing steps are used for removing low-frequency background noise and normalizing the intensity of individual scanned documents. Several filters are used for reducing certain image details and enabling an easier or faster evaluation. The primary aim of the research work is to recognize handwritten and machine written characters and differentiate them. The language opted for the research work is Punjabi Gurmukhi and tool utilized is Matlab.

Unsupervised Learning of Digit Recognition Using Spike-Timing-Dependent Plasticity

Directory of Open Access Journals (Sweden)

Peter U. Diehl

2015-08-01

Full Text Available In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns, since most of such SNN architectures rely on training in a rate-based network and subsequent conversion to a SNN. We present a SNN for digit recognition which is based on mechanisms with increased biological plausibility, i.e. conductance-based instead of current-based synapses, spike-timing-dependent plasticity with time-dependent weight change, lateral inhibition, and an adaptive spiking threshold. Unlike most other systems, we do not use a teaching signal and do not present any class labels to the network. Using this unsupervised learning scheme, our architecture achieves 95% accuracy on the MNIST benchmark, which is better than previous SNN implementations without supervision. The fact that we used no domain-specific knowledge points toward the general applicability of our network design. Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks.

The Contribution of Verbal Working Memory to Deaf Children’s Oral and Written Production

Science.gov (United States)

Arfé, Barbara; Rossi, Cristina; Sicoli, Silvia

2015-01-01

This study investigated the contribution of verbal working memory to the oral and written story production of deaf children. Participants were 29 severely to profoundly deaf children aged 8–13 years and 29 hearing controls, matched for grade level. The children narrated a picture story orally and in writing and performed a reading comprehension test, the Wechsler Intelligence Scale for Children-Fourth Edition forward digit span task, and a reading span task. Oral and written stories were analyzed at the microstructural (i.e., clause) and macrostructural (discourse) levels. Hearing children’s stories scored higher than deaf children’s at both levels. Verbal working memory skills contributed to deaf children’s oral and written production over and above age and reading comprehension skills. Verbal rehearsal skills (forward digit span) contributed significantly to deaf children’s ability to organize oral and written stories at the microstructural level; they also accounted for unique variance at the macrostructural level in writing. Written story production appeared to involve greater verbal working memory resources than oral story production. PMID:25802319

Personal authentication through dorsal hand vein patterns

Science.gov (United States)

Hsu, Chih-Bin; Hao, Shu-Sheng; Lee, Jen-Chun

2011-08-01

Biometric identification is an emerging technology that can solve security problems in our networked society. A reliable and robust personal verification approach using dorsal hand vein patterns is proposed in this paper. The characteristic of the approach needs less computational and memory requirements and has a higher recognition accuracy. In our work, the near-infrared charge-coupled device (CCD) camera is adopted as an input device for capturing dorsal hand vein images, it has the advantages of the low-cost and noncontact imaging. In the proposed approach, two finger-peaks are automatically selected as the datum points to define the region of interest (ROI) in the dorsal hand vein images. The modified two-directional two-dimensional principal component analysis, which performs an alternate two-dimensional PCA (2DPCA) in the column direction of images in the 2DPCA subspace, is proposed to exploit the correlation of vein features inside the ROI between images. The major advantage of the proposed method is that it requires fewer coefficients for efficient dorsal hand vein image representation and recognition. The experimental results on our large dorsal hand vein database show that the presented schema achieves promising performance (false reject rate: 0.97% and false acceptance rate: 0.05%) and is feasible for dorsal hand vein recognition.

Neural-Network Object-Recognition Program

Science.gov (United States)

Spirkovska, L.; Reid, M. B.

1993-01-01

HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

What Is the Role of Manual Preference in Hand-Digit Mapping During Finger Counting? A Study in a Large Sample of Right- and Left-Handers.

Science.gov (United States)

Zago, Laure; Badets, Arnaud

2016-01-01

The goal of the present study was to test whether there is a relationship between manual preference and hand-digit mapping in 369 French adults with similar numbers of right- and left-handers. Manual laterality was evaluated with the finger tapping test to evaluate hand motor asymmetry, and the Edinburgh handedness inventory was used to assess manual preference strength (MPS) and direction. Participants were asked to spontaneously "count on their fingers from 1 to 10" without indications concerning the hand(s) to be used. The results indicated that both MPS and hand motor asymmetry affect the hand-starting preference for counting. Left-handers with a strong left-hand preference (sLH) or left-hand motor asymmetry largely started to count with their left hand (left-starter), while right-handers with a strong right-hand preference (sRH) or right-hand motor asymmetry largely started to count with their right hand (right-starter). Notably, individuals with weak MPS did not show a hand-starting preference. These findings demonstrated that manual laterality contributes to finger counting directionality. Lastly, the results showed a higher proportion of sLH left-starter individuals compared with sRH right-starters, indicating an asymmetric bias of MPS on hand-starting preference. We hypothesize that the higher proportion of sLH left-starters could be explained by the congruence between left-to-right hand-digit mapping and left-to-right mental number line representation that has been largely reported in the literature. Taken together, these results indicate that finger-counting habits integrate biological and cultural information. © The Author(s) 2015.

Digital Technologies for Social Innovation: An Empirical Recognition on the New Enablers

Directory of Open Access Journals (Sweden)

Riccardo Maiolini

2016-12-01

Full Text Available Even though scholars’ attention has been placed on Social Innovation (SI, little evidence has been provided with regards to which tools are actually used to address social needs and foster Social Innovation initiatives. The purpose of the article is twofold. Firstly, the article offers empirical recognition to SI by investigating, on a large-scale, social and innovative activities conducted by start-ups and small and medium-sized enterprises (SMEs across the world between 2001 and 2014. Secondly, the article intends to capture SI core businesses and underlying complementarities between products, markets, and technologies and show in which way digital media and IT are essentially tracing innovation trajectories over a multitude of industries, leading the current industrial patterns of SI, and continually fostering its cross-industry nature.

Evaluation of Speech Recognition of Cochlear Implant Recipients Using Adaptive, Digital Remote Microphone Technology and a Speech Enhancement Sound Processing Algorithm.

Science.gov (United States)

Wolfe, Jace; Morais, Mila; Schafer, Erin; Agrawal, Smita; Koch, Dawn

2015-05-01

Cochlear implant recipients often experience difficulty with understanding speech in the presence of noise. Cochlear implant manufacturers have developed sound processing algorithms designed to improve speech recognition in noise, and research has shown these technologies to be effective. Remote microphone technology utilizing adaptive, digital wireless radio transmission has also been shown to provide significant improvement in speech recognition in noise. There are no studies examining the potential improvement in speech recognition in noise when these two technologies are used simultaneously. The goal of this study was to evaluate the potential benefits and limitations associated with the simultaneous use of a sound processing algorithm designed to improve performance in noise (Advanced Bionics ClearVoice) and a remote microphone system that incorporates adaptive, digital wireless radio transmission (Phonak Roger). A two-by-two way repeated measures design was used to examine performance differences obtained without these technologies compared to the use of each technology separately as well as the simultaneous use of both technologies. Eleven Advanced Bionics (AB) cochlear implant recipients, ages 11 to 68 yr. AzBio sentence recognition was measured in quiet and in the presence of classroom noise ranging in level from 50 to 80 dBA in 5-dB steps. Performance was evaluated in four conditions: (1) No ClearVoice and no Roger, (2) ClearVoice enabled without the use of Roger, (3) ClearVoice disabled with Roger enabled, and (4) simultaneous use of ClearVoice and Roger. Speech recognition in quiet was better than speech recognition in noise for all conditions. Use of ClearVoice and Roger each provided significant improvement in speech recognition in noise. The best performance in noise was obtained with the simultaneous use of ClearVoice and Roger. ClearVoice and Roger technology each improves speech recognition in noise, particularly when used at the same time

Human Digital Modeling & Hand Scanning Lab

Data.gov (United States)

Federal Laboratory Consortium — This laboratory incorporates specialized scanning equipment, computer workstations and software applications for the acquisition and analysis of digitized models of...

Speech Recognition on Mobile Devices

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Lindberg, Børge

2010-01-01

in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within......The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...

Side-View Face Recognition

NARCIS (Netherlands)

Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; van den Biggelaar, Olivier

As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Sadhana. KANNAN BALAKRISHNAN. Articles written in Sadhana. Volume 38 Issue 6 December 2013 pp 1339-1346. Connected digit speech recognition system for Malayalam language · Cini Kurian Kannan Balakrishnan · More Details Abstract Fulltext PDF. A connected digit speech recognition is ...

Multiscale Convolutional Neural Networks for Hand Detection

Directory of Open Access Journals (Sweden)

Shiyang Yan

2017-01-01

Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.

Written Cultural Heritage in the Context of Adopted Legal Regulations

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Eva Kodrič-Dačić

2013-09-01

Full Text Available ABSTRACTPurpose: Libraries collect written cultural heritage which is not only the most valuable part of their collections but also a part of library materials which is, due to digitalization projects in the last decade, becoming more and more interesting to librarians and library users. The main goal of the study is a theoretical research of library materials acknowledged as Slovenian heritage. By defining the basic terms it highlights the attributes which are immanent to library materials, derived from the context of their origin or later destiny. Slovenian library legislation concerning protection of written cultural heritage is also critically analysed.Methodology/approach: Comparative analyses of European and Slovenian legislation concerning librarianship and written cultural heritage. Research limitation: Research was mainly limited to professional literature and resources dealing with written cultural heritage. Originality/practical implications: Results of the research serve as formal criteria for definition of library materials as written heritage and suggest how to improve legislation in the field of protection of written heritage in libraries. 

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Sadhana. Kannan Balakrishnan. Articles written in Sadhana. Volume 38 Issue 6 December 2013 pp 1339-1346. Connected digit speech recognition system for Malayalam language · Cini Kurian Kannan Balakrishnan · More Details Abstract Fulltext PDF. A connected digit speech recognition is important in ...

Digital atlas of fetal brain MRI

Energy Technology Data Exchange (ETDEWEB)

Chapman, Teresa; Weinberger, E. [Department of Radiology, Seattle Children' s Hospital, Seattle, WA (United States); Matesan, Manuela [University of Washington, Department of Radiology, Seattle, WA (United States); Bulas, Dorothy I. [Division of Diagnostic Imaging and Radiology, Children' s National Medical Center, Washington, DC (United States)

2010-02-15

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download. Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development. (orig.)

Digital atlas of fetal brain MRI

International Nuclear Information System (INIS)

Chapman, Teresa; Weinberger, E.; Matesan, Manuela; Bulas, Dorothy I.

2010-01-01

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download. Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development. (orig.)

Finger Angle-Based Hand Gesture Recognition for Smart Infrastructure Using Wearable Wrist-Worn Camera

Directory of Open Access Journals (Sweden)

Feiyu Chen

2018-03-01

Full Text Available The arising of domestic robots in smart infrastructure has raised demands for intuitive and natural interaction between humans and robots. To address this problem, a wearable wrist-worn camera (WwwCam is proposed in this paper. With the capability of recognizing human hand gestures in real-time, it enables services such as controlling mopping robots, mobile manipulators, or appliances in smart-home scenarios. The recognition is based on finger segmentation and template matching. Distance transformation algorithm is adopted and adapted to robustly segment fingers from the hand. Based on fingers’ angles relative to the wrist, a finger angle prediction algorithm and a template matching metric are proposed. All possible gesture types of the captured image are first predicted, and then evaluated and compared to the template image to achieve the classification. Unlike other template matching methods relying highly on large training set, this scheme possesses high flexibility since it requires only one image as the template, and can classify gestures formed by different combinations of fingers. In the experiment, it successfully recognized ten finger gestures from number zero to nine defined by American Sign Language with an accuracy up to 99.38%. Its performance was further demonstrated by manipulating a robot arm using the implemented algorithms and WwwCam to transport and pile up wooden building blocks.

Static human face recognition using artificial neural networks

International Nuclear Information System (INIS)

Qamar, R.; Shah, S.H.; Javed-ur-Rehman

2003-01-01

This paper presents a novel method of human face recognition using digital computers. A digital PC camera is used to take the BMP images of the human faces. An artificial neural network using Back Propagation Algorithm is developed as a recognition engine. The BMP images of the faces serve as the input patterns for this engine. A software 'Face Recognition' has been developed to recognize the human faces for which it is trained. Once the neural network is trained for patterns of the faces, the software is able to detect and recognize them with success rate of about 97%. (author)

Dexterous hand gestures recognition based on low-density sEMG signals for upper-limb forearm amputees

Directory of Open Access Journals (Sweden)

John Jairo Villarejo Mayor

2017-08-01

Full Text Available Abstract Introduction Intuitive prosthesis control is one of the most important challenges in order to reduce the user effort in learning how to use an artificial hand. This work presents the development of a novel method for pattern recognition of sEMG signals able to discriminate, in a very accurate way, dexterous hand and fingers movements using a reduced number of electrodes, which implies more confidence and usability for amputees. Methods The system was evaluated for ten forearm amputees and the results were compared with the performance of able-bodied subjects. Multiple sEMG features based on fractal analysis (detrended fluctuation analysis and Higuchi’s fractal dimension combined with traditional magnitude-based features were analyzed. Genetic algorithms and sequential forward selection were used to select the best set of features. Support vector machine (SVM, K-nearest neighbors (KNN and linear discriminant analysis (LDA were analyzed to classify individual finger flexion, hand gestures and different grasps using four electrodes, performing contractions in a natural way to accomplish these tasks. Statistical significance was computed for all the methods using different set of features, for both groups of subjects (able-bodied and amputees. Results The results showed average accuracy up to 99.2% for able-bodied subjects and 98.94% for amputees using SVM, followed very closely by KNN. However, KNN also produces a good performance, as it has a lower computational complexity, which implies an advantage for real-time applications. Conclusion The results show that the method proposed is promising for accurately controlling dexterous prosthetic hands, providing more functionality and better acceptance for amputees.

Applications of chaotic neurodynamics in pattern recognition

Science.gov (United States)

Baird, Bill; Freeman, Walter J.; Eeckman, Frank H.; Yao, Yong

1991-08-01

Network algorithms and architectures for pattern recognition derived from neural models of the olfactory system are reviewed. These span a range from highly abstract to physiologically detailed, and employ the kind of dynamical complexity observed in olfactory cortex, ranging from oscillation to chaos. A simple architecture and algorithm for analytically guaranteed associative memory storage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored. There are N units of capacity in an N node network with 3N2 weights. It costs one unit per static attractor, two per Fourier component of each sequence, and three to four per chaotic attractor. There are no spurious attractors, and for sequences there is a Liapunov function in a special coordinate system which governs the approach of transient states to stored trajectories. Unsupervised or supervised incremental learning algorithms for pattern classification, such as competitive learning or bootstrap Widrow-Hoff can easily be implemented. The architecture can be ''folded'' into a recurrent network with higher order weights that can be used as a model of cortex that stores oscillatory and chaotic attractors by a Hebb rule. Network performance is demonstrated by application to the problem of real-time handwritten digit recognition. An effective system with on-line learning has been written by Eeckman and Baird for the Macintosh. It utilizes static, oscillatory, and/or chaotic attractors of two kinds--Lorenze attractors, or attractors resulting from chaotically interacting oscillatory modes. The successful application to an industrial pattern recognition problem of a network architecture of considerable physiological and dynamical complexity, developed by Freeman and Yao, is described. The data sets of the problem come in three classes of difficulty, and performance of the biological network is

3D palmprint and hand imaging system based on full-field composite color sinusoidal fringe projection technique.

Science.gov (United States)

Zhang, Zonghua; Huang, Shujun; Xu, Yongjia; Chen, Chao; Zhao, Yan; Gao, Nan; Xiao, Yanjun

2013-09-01

Palmprint and hand shape, as two kinds of important biometric characteristics, have been widely studied and applied to human identity recognition. The existing research is based mainly on 2D images, which lose the third-dimensional information. The biological features extracted from 2D images are distorted by pressure and rolling, so the subsequent feature matching and recognition are inaccurate. This paper presents a method to acquire accurate 3D shapes of palmprint and hand by projecting full-field composite color sinusoidal fringe patterns and the corresponding color texture information. A 3D imaging system is designed to capture and process the full-field composite color fringe patterns on hand surface. Composite color fringe patterns having the optimum three fringe numbers are generated by software and projected onto the surface of human hand by a digital light processing projector. From another viewpoint, a color CCD camera captures the deformed fringe patterns and saves them for postprocessing. After compensating for the cross talk and chromatic aberration between color channels, three fringe patterns are extracted from three color channels of a captured composite color image. Wrapped phase information can be calculated from the sinusoidal fringe patterns with high precision. At the same time, the absolute phase of each pixel is determined by the optimum three-fringe selection method. After building up the relationship between absolute phase map and 3D shape data, the 3D palmprint and hand are obtained. Color texture information can be directly captured or demodulated from the captured composite fringe pattern images. Experimental results show that the proposed method and system can yield accurate 3D shape and color texture information of the palmprint and hand shape.

A proposal of decontamination robot using 3D hand-eye-dual-cameras solid recognition and accuracy validation

International Nuclear Information System (INIS)

Minami, Mamoru; Nishimura, Kenta; Sunami, Yusuke; Yanou, Akira; Yu, Cui; Yamashita, Manabu; Ishiyama, Shintaro

2015-01-01

New robotic system that uses three dimensional measurement with solid object recognition —3D-MOS (Three Dimensional Move on Sensing)— based on visual servoing technology was designed and the on-board hand-eye-dual-cameras robot system has been developed to reduce risks of radiation exposure during decontamination processes by filter press machine that solidifies and reduces the volume of irradiation contaminated soil. The feature of 3D-MoS includes; (1) the both hand-eye-dual-cameras take the images of target object near the intersection of both lenses' centerlines, (2) the observation at intersection enables both cameras can see target object almost at the center of both images, (3) then it brings benefits as reducing the effect of lens aberration and improving the detection accuracy of three dimensional position. In this study, accuracy validation test of interdigitation of the robot's hand into filter cloth rod of the filter press —the task is crucial for the robot to remove the contaminated cloth from the filter press machine automatically and for preventing workers from exposing to radiation—, was performed. Then the following results were derived; (1) the 3D-MoS controlled robot could recognize the rod at arbitrary position within designated space, and all of insertion test were carried out successfully and, (2) test results also demonstrated that the proposed control guarantees that interdigitation clearance between the rod and robot hand can be kept within 1.875[mm] with standard deviation being 0.6[mm] or less. (author)

A CAD system and quality assurance protocol for bone age assessment utilizing digital hand atlas

Science.gov (United States)

Gertych, Arakadiusz; Zhang, Aifeng; Ferrara, Benjamin; Liu, Brent J.

2007-03-01

Determination of bone age assessment (BAA) in pediatric radiology is a task based on detailed analysis of patient's left hand X-ray. The current standard utilized in clinical practice relies on a subjective comparison of the hand with patterns in the book atlas. The computerized approach to BAA (CBAA) utilizes automatic analysis of the regions of interest in the hand image. This procedure is followed by extraction of quantitative features sensitive to skeletal development that are further converted to a bone age value utilizing knowledge from the digital hand atlas (DHA). This also allows providing BAA results resembling current clinical approach. All developed methodologies have been combined into one CAD module with a graphical user interface (GUI). CBAA can also improve the statistical and analytical accuracy based on a clinical work-flow analysis. For this purpose a quality assurance protocol (QAP) has been developed. Implementation of the QAP helped to make the CAD more robust and find images that cannot meet conditions required by DHA standards. Moreover, the entire CAD-DHA system may gain further benefits if clinical acquisition protocol is modified. The goal of this study is to present the performance improvement of the overall CAD-DHA system with QAP and the comparison of the CAD results with chronological age of 1390 normal subjects from the DHA. The CAD workstation can process images from local image database or from a PACS server.

Study on municipal road cracking and surface deformation based on image recognition

Science.gov (United States)

Yuan, Haitao; Wang, Shuai; Tan, Jizong

2017-05-01

In recent years, the digital image recognition technology of concrete structure cracks and deformation of binocular vision technology detection of civil engineering structure have made substantial development. As a result, people's understanding of the road engineering structure cracking and surface deformation recognition gives rise to a new situation. For the research on digital image concrete structure cracking and masonry structure surface deformation recognition technology, the key is to break through in the method, and to improve the traditional recognition technology and mode. Only in this way can we continuously improve the security level of the highway, to adapt to the new requirements of the development of new urbanization and modernization. This thesis focuses on and systematically analyzes the digital image road engineering structure cracking and key technologies of surface deformation recognition and its engineering applications. In addition, we change the concrete structure cracking and masonry structure surface deformation recognition pattern, and realize the breakthrough and innovation of the road structure safety testing means and methods.

3D Visual Sensing of the Human Hand for the Remote Operation of a Robotic Hand

Directory of Open Access Journals (Sweden)

Pablo Gil

2014-02-01

Full Text Available New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

Reading handprinted addresses on IRS tax forms

Science.gov (United States)

Ramanaprasad, Vemulapati; Shin, Yong-Chul; Srihari, Sargur N.

1996-03-01

The hand-printed address recognition system described in this paper is a part of the Name and Address Block Reader (NABR) system developed by the Center of Excellence for Document Analysis and Recognition (CEDAR). NABR is currently being used by the IRS to read address blocks (hand-print as well as machine-print) on fifteen different tax forms. Although machine- print address reading was relatively straightforward, hand-print address recognition has posed some special challenges due to demands on processing speed (with an expected throughput of 8450 forms/hour) and recognition accuracy. We discuss various subsystems involved in hand- printed address recognition, including word segmentation, word recognition, digit segmentation, and digit recognition. We also describe control strategies used to make effective use of these subsystems to maximize recognition accuracy. We present system performance on 931 address blocks in recognizing various fields, such as city, state, ZIP Code, street number and name, and personal names.

Digital image processing

National Research Council Canada - National Science Library

Gonzalez, Rafael C; Woods, Richard E

2008-01-01

Completely self-contained-and heavily illustrated-this introduction to basic concepts and methodologies for digital image processing is written at a level that truly is suitable for seniors and first...

Digital atlas of fetal brain MRI.

Science.gov (United States)

Chapman, Teresa; Matesan, Manuela; Weinberger, Ed; Bulas, Dorothy I

2010-02-01

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C#, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download from http://radiology.seattlechildrens.org/teaching/fetal_brain . Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development.

A biometric authentication model using hand gesture images.

Science.gov (United States)

Fong, Simon; Zhuang, Yan; Fister, Iztok; Fister, Iztok

2013-10-30

A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i' , 'l' , 'o' , 'v' , 'e' , and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.

Common input to motor units of intrinsic and extrinsic hand muscles during two-digit object hold.

Science.gov (United States)

Winges, Sara A; Kornatz, Kurt W; Santello, Marco

2008-03-01

Anatomical and physiological evidence suggests that common input to motor neurons of hand muscles is an important neural mechanism for hand control. To gain insight into the synaptic input underlying the coordination of hand muscles, significant effort has been devoted to describing the distribution of common input across motor units of extrinsic muscles. Much less is known, however, about the distribution of common input to motor units belonging to different intrinsic muscles and to intrinsic-extrinsic muscle pairs. To address this void in the literature, we quantified the incidence and strength of near-simultaneous discharges of motor units residing in either the same or different intrinsic hand muscles (m. first dorsal, FDI, and m. first palmar interosseus, FPI) during two-digit object hold. To extend the characterization of common input to pairs of extrinsic muscles (previous work) and pairs of intrinsic muscles (present work), we also recorded electromyographic (EMG) activity from an extrinsic thumb muscle (m. flexor pollicis longus, FPL). Motor-unit synchrony across FDI and FPI was weak (common input strength, CIS, mean +/- SE: 0.17 +/- 0.02). Similarly, motor units from extrinsic-intrinsic muscle pairs were characterized by weak synchrony (FPL-FDI: 0.25 +/- 0.02; FPL-FPI: 0.29 +/- 0.03) although stronger than FDI-FPI. Last, CIS from within FDI and FPI was more than three times stronger (0.70 +/- 0.06 and 0.66 +/- 0.06, respectively) than across these muscles. We discuss present and previous findings within the framework of muscle-pair specific distribution of common input to hand muscles based on their functional role in grasping.

Digitalization of the second finger in type 2 central longitudinal deficiencies (clefting) of the hand.

Science.gov (United States)

Oberlin, Christophe; Korchi, Amar; Belkheyar, Zoubir; Touam, Chabane; Macquillan, Anthony

2009-06-01

In central longitudinal deficiency of the hand type 2 (Manske and Halikis), the second finger presents itself anatomically and functionally as a second thumb. It is therefore necessary to undertake digitalization of the index, performed exactly as a reverse pollicization technique, with the same principles: minimum volar scarring and reconstruction of a large first web space without scars at the fold of the commissure. The incision surrounds the second digit at the level of the midproximal phalanx, extends over the dorsal edge of the cleft, and finishes on the radial side of the third finger where the second web space is to be created. Through this approach, the index metacarpal is freed (extraperiosteally), preserving the dorsal venous network, and translocated into the space of the missing third ray. After internal bone fixation, the flap, with its wide and safe volar cutaneous pedicle, is easily transposed to reconstruct the first web space, avoiding the need for skin grafting. This technique is easier and safer and does not impair the normal thumb musculature compared with the classic Snow-Littler procedure.

Faith in the net: towards the creation of digital networks of religious acknowledgement and recognition

Directory of Open Access Journals (Sweden)

Luis Ignacio SIERRA GUTIÉRREZ

2017-12-01

Full Text Available Undoubtedly, the technological revolution in information and communications causing major changes in citizens’ social interactions. The new reticular rationality offers the possibility of shaping, developing, and strengthening social networks and virtual communities. All of them facilitate the creation of new interactive spaces, new social collectives promoting citizenship and that, from different social fields and levels of experience, articulate and streamline processes of production, circulation and appropriation of new symbolic products. Such products contribute not only to generating new sources of knowledge but, above all, to strengthening processes of citizen interaction. In such processes, the field of media, religiosities and socio-cultural processes are strategically intertwined. In this context, experiences of civic religiosity find in the potential generated by the global network, new possibilities of interaction and religious recognition. Also new forms and spaces to share plural options of faith and socio-religious practices that make sense of the existence of cybernauts. This text is divided into three parts: First, critically contextualizes the global phenomenon of social networks. Second, it makes an approximation to some experiences of digital networks of religious recognition from Latin America. Finally, raises some questions that arise from such virtual practices.

Comparison of a digital and an optical analogue hand-held refractometer for the measurement of canine urine specific gravity.

Science.gov (United States)

Paris, J K; Bennett, A D; Dodkin, S J; Gunn-Moore, D A

2012-05-05

Urine specific gravity (USG) is used clinically as a measure of urine concentration, and is routinely assessed by refractometry. A comparison between optical analogue and digital refractometers for evaluation of canine urine has not been reported. The aim of this study was to compare a digital and an optical analogue hand-held refractometer for the measurement of canine USG, and to assess correlation with urine osmolality. Prospective study. Free-catch urine samples were collected from 285 hospitalised adult dogs, and paired USG readings were obtained with a digital and an optical analogue refractometer. In 50 dogs, urine osmolality was also measured using a freezing point depression osmometer. There was a small but statistically significant difference between the two refractometers (P<0.001), with the optical analogue refractometer reading higher than the digital refractometer (mean difference 0.0006, sd 0.0012). Paired refractometer measurements varied by <0.002 in 91.5 per cent of cases. The optical analogue and digital refractometer readings showed excellent correlation with osmolality (r=0.980 and r=0.977, respectively, P<0.001 in both cases). Despite statistical significance, the difference between the two refractometers is unlikely to be clinically significant. Both instruments provide an accurate assessment of USG in dogs.

Arabic sign language recognition based on HOG descriptor

Science.gov (United States)

Ben Jmaa, Ahmed; Mahdi, Walid; Ben Jemaa, Yousra; Ben Hamadou, Abdelmajid

2017-02-01

We present in this paper a new approach for Arabic sign language (ArSL) alphabet recognition using hand gesture analysis. This analysis consists in extracting a histogram of oriented gradient (HOG) features from a hand image and then using them to generate an SVM Models. Which will be used to recognize the ArSL alphabet in real-time from hand gesture using a Microsoft Kinect camera. Our approach involves three steps: (i) Hand detection and localization using a Microsoft Kinect camera, (ii) hand segmentation and (iii) feature extraction using Arabic alphabet recognition. One each input image first obtained by using a depth sensor, we apply our method based on hand anatomy to segment hand and eliminate all the errors pixels. This approach is invariant to scale, to rotation and to translation of the hand. Some experimental results show the effectiveness of our new approach. Experiment revealed that the proposed ArSL system is able to recognize the ArSL with an accuracy of 90.12%.

Digital information culture the individual and society in the digital age

CERN Document Server

Tredinnick, Luke

2008-01-01

Digital Information Culture is an introduction to the cultural, social and political impact of digital information and digital resources. The book is organised around themes, rather than theories and is arranged into three sections: culture, society and the individual. Each explores key elements of the social, cultural and political impact of digital information. The culture section outlines the origins of cyber culture in fifties pulp-fiction through to the modern day. It explores the issues of information overload, the threat of a digital dark age, and the criminal underbelly of digital culture. Section two, society, explores the economic and social impact of digital information, outlining key theories of the Information Age. Section three explores the impact of digital information and digital resources on the individual, exploring the changing nature of identity in a digital world. Written by a leading author in the field Focuses on digital information and its social, cultural and political impact is uniqu...

Hand burns surface area: A rule of thumb.

Science.gov (United States)

Dargan, Dallan; Mandal, Anirban; Shokrollahi, Kayvan

2018-03-11

Rapid estimation of acute hand burns is important for communication, standardisation of assessment, rehabilitation and research. Use of an individual's own thumbprint area as a fraction of their total hand surface area was evaluated to assess potential utility in hand burn evaluation. Ten health professionals used an ink-covered dominant thumb pulp to cover the surfaces of their own non-dominant hand using the contralateral thumb. Thumbprints were assessed on the web spaces, sides of digits and dorsum and palm beyond the distal wrist crease. Hand surface area was estimated using the Banerjee and Sen method, and thumbprint ellipse area calculated to assess correlation. Mean estimated total hand surface area was 390.0cm 2 ±SD 51.5 (328.3-469.0), mean thumbprint ellipse area was 5.5cm 2 ±SD 1.3 (3.7-8.4), and mean estimated print number was 73.5±SD 11.0 (range 53.1-87.8, 95% CI 6.8). The mean observed number of thumbprints on one hand was 80.1±SD 5.9 (range 70.0-88.0, 95% CI 3.7), χ 2 =0.009. The combined mean of digital prints was 42, comprising a mean of two prints each on volar, dorsal, radial and ulnar digit surfaces, except volar middle and ring (3 prints each). Palmar prints were 15 (11-19), dorsal 15 (11-19), ulnar palm border 3, first web space 2, and second, third and fourth web spaces one each. Using the surface of the palm alone, excluding digits, as 0.5% of total body surface area, the area of one thumbprint was approximated as 1/30th of 1%. We have demonstrated how thumbprint area serves as a simple method for evaluating hand burn surface area. Copyright © 2018 Elsevier Ltd and ISBI. All rights reserved.

Digital Mayhem 3D machine techniques where inspiration, techniques and digital art meet

CERN Document Server

Evans, Duncan

2014-01-01

From Icy Tundras to Desert savannahs, master the art of landscape and environment design for 2D and 3D digital content. Make it rain, shower your digital scene with a snow storm or develop a believable urban scene with a critical eye for modeling, lighting and composition. Move beyond the limitations of gallery style coffee table books with Digital Mayhem: 3D Landscapes-offering leading professional techniques, groundbreaking inspiration, and artistic mastery from some of the greatest digital artists. More than just a gallery book - each artist has written a breakdown overview, with supporting

Digital mammography

International Nuclear Information System (INIS)

Bick, Ulrich; Diekmann, Felix

2010-01-01

This state-of-the-art reference book provides in-depth coverage of all aspects of digital mammography, including detector technology, image processing, computer-aided diagnosis, soft-copy reading, digital workflow, and PACS. Specific advantages and disadvantages of digital mammography in comparison to screen-film mammography are thoroughly discussed. By including authors from both North America and Europe, the book is able to outline variations in the use, acceptance, and quality assurance of digital mammography between the different countries and screening programs. Advanced imaging techniques and future developments such as contrast mammography and digital breast tomosynthesis are also covered in detail. All of the chapters are written by internationally recognized experts and contain numerous high-quality illustrations. This book will be of great interest both to clinicians who already use or are transitioning to digital mammography and to basic scientists working in the field. (orig.)

Modulation of pathogen recognition by autophagy

Directory of Open Access Journals (Sweden)

Ji Eun eOh

2012-03-01

Full Text Available Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand, autophagy modulates pathogen recognition and downstream signaling for innate immune responses. Pathogen recognition via pattern recognition receptors induces autophagy. The function of phagocytic cells is enhanced by recruitment of autophagy-related proteins. Moreover, autophagy acts as a delivery system for viral replication complexes to migrate to the endosomal compartments where virus sensing occurs. In another case, key molecules of the autophagic pathway have been found to negatively regulate immune signaling, thus preventing aberrant activation of cytokine production and consequent immune responses. In this review, we focus on the recent advances in the role of autophagy in pathogen recognition and modulation of innate immune responses.

Digitized mammograms

International Nuclear Information System (INIS)

Bruneton, J.N.; Balu-Maestro, C.; Rogopoulos, A.; Chauvel, C.; Geoffray, A.

1988-01-01

Two observers conducted a blind evaluation of 100 mammography files, including 47 malignant cases. Films were read both before and after image digitization at 50 μm and 100 μm with the FilmDRSII. Digitization permitted better analysis of the normal anatomic structures and moderately improved diagnostic sensitivity. Searches for microcalcifications before and after digitization at 100 μm and 50 μm showed better analysis of anatomic structures after digitization (especially for solitary microcalcifications). The diagnostic benefit, with discovery of clustered microcalcifications, was more limited (one case at 100 μm, nine cases at 50 μm). Recognition of microcalcifications was clearly improved in dense breasts, which can benefit from reinterpretation after digitization at 50 μm rather 100μm

Incorporating Speech Recognition into a Natural User Interface

Science.gov (United States)

Chapa, Nicholas

2017-01-01

The Augmented/ Virtual Reality (AVR) Lab has been working to study the applicability of recent virtual and augmented reality hardware and software to KSC operations. This includes the Oculus Rift, HTC Vive, Microsoft HoloLens, and Unity game engine. My project in this lab is to integrate voice recognition and voice commands into an easy to modify system that can be added to an existing portion of a Natural User Interface (NUI). A NUI is an intuitive and simple to use interface incorporating visual, touch, and speech recognition. The inclusion of speech recognition capability will allow users to perform actions or make inquiries using only their voice. The simplicity of needing only to speak to control an on-screen object or enact some digital action means that any user can quickly become accustomed to using this system. Multiple programs were tested for use in a speech command and recognition system. Sphinx4 translates speech to text using a Hidden Markov Model (HMM) based Language Model, an Acoustic Model, and a word Dictionary running on Java. PocketSphinx had similar functionality to Sphinx4 but instead ran on C. However, neither of these programs were ideal as building a Java or C wrapper slowed performance. The most ideal speech recognition system tested was the Unity Engine Grammar Recognizer. A Context Free Grammar (CFG) structure is written in an XML file to specify the structure of phrases and words that will be recognized by Unity Grammar Recognizer. Using Speech Recognition Grammar Specification (SRGS) 1.0 makes modifying the recognized combinations of words and phrases very simple and quick to do. With SRGS 1.0, semantic information can also be added to the XML file, which allows for even more control over how spoken words and phrases are interpreted by Unity. Additionally, using a CFG with SRGS 1.0 produces a Finite State Machine (FSM) functionality limiting the potential for incorrectly heard words or phrases. The purpose of my project was to

Education, Sociability and Written Culture : the case of the Society of Jesus in France

Directory of Open Access Journals (Sweden)

Stéphane Van Damme

2007-06-01

Full Text Available In a special Issue of the journal Annales, the historian Roger Chartier could draw up a review of the written culture history and underlined the role played by certain social groups in the diffusion of written culture in the cities. He distinguished two major elements in this evolution  : one hand “ The use of writing as an instrument of self-government and administration ” and on the other hand “ the link between religious experience and use of writting ”. In this tension, it has been intere...

IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP

OpenAIRE

LIU Ying; HAN Yan-bin; ZHANG Yu-lin

2015-01-01

In the paper, we combined DSP processor with image processing algorithm and studied the method of water meter character recognition. We collected water meter image through camera at a fixed angle, and the projection method is used to recognize those digital images. The experiment results show that the method can recognize the meter characters accurately and artificial meter reading is replaced by automatic digital recognition, which improves working efficiency.

A New Profile Shape Matching Stereovision Algorithm for Real-time Human Pose and Hand Gesture Recognition

Directory of Open Access Journals (Sweden)

Dong Zhang

2014-02-01

Full Text Available This paper presents a new profile shape matching stereovision algorithm that is designed to extract 3D information in real time. This algorithm obtains 3D information by matching profile intensity shapes of each corresponding row of the stereo image pair. It detects the corresponding matching patterns of the intensity profile rather than the intensity values of individual pixels or pixels in a small neighbourhood. This approach reduces the effect of the intensity and colour variations caused by lighting differences. As with all real-time vision algorithms, there is always a trade-off between accuracy and processing speed. This algorithm achieves a balance between the two to produce accurate results for real-time applications. To demonstrate its performance, the proposed algorithm is tested for human pose and hand gesture recognition to control a smart phone and an entertainment system.

Strategies in digital marketing

OpenAIRE

Robert DRAGOMIR; Mihai ANDRONIE

2017-01-01

The present paper deals with digital marketing. The approach into discussion is the strategies met with the concept mentioned above. Within the actual socio-economic context, the electronic equipments offer on one hand new and innovative methods for products promoting and, on the other hand new challenges for the consumers. Thus, we analysed different and major types of strategies, which have a great impact on the digital marketing.

The left hand second to fourth digit ratio (2D:4D) is not related to any physical fitness component in adolescent girls.

Science.gov (United States)

Peeters, Maarten W; Van Aken, Katrijn; Claessens, Albrecht L

2013-01-01

The second to fourth-digit-ratio (2D:4D), a putative marker of prenatal androgen action and a sexually dimorphic trait, has been suggested to be related with fitness and sports performance, although results are not univocal. Most studies however focus on a single aspect of physical fitness or one sports discipline. In this study the 2D:4D ratio of 178 adolescent girls (age 13.5-18 y) was measured on X-rays of the left hand. The relation between 2D:4D digit ratio and multiple aspects of physical fitness (balance, speed of limb movement, flexibility, explosive strength, static strength, trunk strength, functional strength, running speed/agility, and endurance) was studied by correlation analyses and stepwise multiple regression. For comparison the relation between these physical fitness components and a selected number of objectively measured anthropometric traits (stature, mass, BMI, somatotype components and the Bayer & Bailey androgyny index) are presented alongside the results of 2D:4D digit ratio. Left hand 2D:4D digit ratio (0.925±0.019) was not significantly correlated with any of the physical fitness components nor any of the anthropometric variables included in the present study. 2D:4D did not enter the multiple stepwise regression for any of the physical fitness components in which other anthropometric traits explained between 9.2% (flexibility) and 33.9% (static strength) of variance. Unlike other anthropometric traits the 2D:4D digit ratio does not seem to be related to any physical fitness component in adolescent girls and therefore most likely should not be considered in talent detection programs for sporting ability in girls.

Improved pattern recognition systems by hybrid methods

International Nuclear Information System (INIS)

Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

1978-12-01

This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

Dynamic Features for Iris Recognition.

Science.gov (United States)

da Costa, R M; Gonzaga, A

2012-08-01

The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

Investigation of efficient features for image recognition by neural networks.

Science.gov (United States)

Goltsev, Alexander; Gritsenko, Vladimir

2012-04-01

In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

Pattern recognition and string matching

CERN Document Server

Cheng, Xiuzhen

2002-01-01

The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

iHand: an interactive bare-hand-based augmented reality interface on commercial mobile phones

Science.gov (United States)

Choi, Junyeong; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2013-02-01

The performance of mobile phones has rapidly improved, and they are emerging as a powerful platform. In many vision-based applications, human hands play a key role in natural interaction. However, relatively little attention has been paid to the interaction between human hands and the mobile phone. Thus, we propose a vision- and hand gesture-based interface in which the user holds a mobile phone in one hand but sees the other hand's palm through a built-in camera. The virtual contents are faithfully rendered on the user's palm through palm pose estimation, and reaction with hand and finger movements is achieved that is recognized by hand shape recognition. Since the proposed interface is based on hand gestures familiar to humans and does not require any additional sensors or markers, the user can freely interact with virtual contents anytime and anywhere without any training. We demonstrate that the proposed interface works at over 15 fps on a commercial mobile phone with a 1.2-GHz dual core processor and 1 GB RAM.

Electromyography data for non-invasive naturally-controlled robotic hand prostheses.

Science.gov (United States)

Atzori, Manfredo; Gijsberts, Arjan; Castellini, Claudio; Caputo, Barbara; Hager, Anne-Gabrielle Mittaz; Elsig, Simone; Giatsidis, Giorgio; Bassetto, Franco; Müller, Henning

2014-01-01

Recent advances in rehabilitation robotics suggest that it may be possible for hand-amputated subjects to recover at least a significant part of the lost hand functionality. The control of robotic prosthetic hands using non-invasive techniques is still a challenge in real life: myoelectric prostheses give limited control capabilities, the control is often unnatural and must be learned through long training times. Meanwhile, scientific literature results are promising but they are still far from fulfilling real-life needs. This work aims to close this gap by allowing worldwide research groups to develop and test movement recognition and force control algorithms on a benchmark scientific database. The database is targeted at studying the relationship between surface electromyography, hand kinematics and hand forces, with the final goal of developing non-invasive, naturally controlled, robotic hand prostheses. The validation section verifies that the data are similar to data acquired in real-life conditions, and that recognition of different hand tasks by applying state-of-the-art signal features and machine-learning algorithms is possible.

Stimulation over primary motor cortex during action observation impairs effector recognition.

Science.gov (United States)

Naish, Katherine R; Barnes, Brittany; Obhi, Sukhvinder S

2016-04-01

Recent work suggests that motor cortical processing during action observation plays a role in later recognition of the object involved in the action. Here, we investigated whether recognition of the effector making an action is also impaired when transcranial magnetic stimulation (TMS) - thought to interfere with normal cortical activity - is applied over the primary motor cortex (M1) during action observation. In two experiments, single-pulse TMS was delivered over the hand area of M1 while participants watched short clips of hand actions. Participants were then asked whether an image (experiment 1) or a video (experiment 2) of a hand presented later in the trial was the same or different to the hand in the preceding video. In Experiment 1, we found that participants' ability to recognise static images of hands was significantly impaired when TMS was delivered over M1 during action observation, compared to when no TMS was delivered, or when stimulation was applied over the vertex. Conversely, stimulation over M1 did not affect recognition of dot configurations, or recognition of hands that were previously presented as static images (rather than action movie clips) with no object. In Experiment 2, we found that effector recognition was impaired when stimulation was applied part way through (300ms) and at the end (500ms) of the action observation period, indicating that 200ms of action-viewing following stimulation was not long enough to form a new representation that could be used for later recognition. The findings of both experiments suggest that interfering with cortical motor activity during action observation impairs subsequent recognition of the effector involved in the action, which complements previous findings of motor system involvement in object memory. This work provides some of the first evidence that motor processing during action observation is involved in forming representations of the effector that are useful beyond the action observation period

Multi-font printed Mongolian document recognition system

Science.gov (United States)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Report generation using digital speech recognition in radiology

International Nuclear Information System (INIS)

Vorbeck, F.; Ba-Ssalamah, A.; Kettenbach, J.; Huebsch, P.

2000-01-01

The aim of this study was to evaluate whether the use of a digital continuous speech recognition (CSR) in the field of radiology could lead to relevant time savings in generating a report. A CSR system (SP6000, Philips, Eindhoven, The Netherlands) for German was used to transform fluently spoken sentences into text. Two radiologists dictated a total of 450 reports on five radiological topics. Two typists edited those reports by means of conventional typing using a text editor (WinWord 6.0, Microsoft, Redmond, Wash.) installed on an IBM-compatible personal computer (PC). The same reports were generated using the CSR system and the performance of both systems was then evaluated by comparing the time needed to generate the reports and the error rates of both systems. In addition, the error rate of the CSR system and the time needed to create the reports was evaluated. The mean error rate for the CSR system was 5.5 %, and the mean error rate for conventional typing was 0.4 %. Reports edited with the CSR, on average, were generated 19 % faster compared with the conventional text-editing method. However, the amount of error rates and time savings were different and depended on topics, speakers, and typists. Using CSR the maximum time saving achieved was 28 % for the topic sonography. The CSR system was never slower, under any circumstances, than conventional typing on a PC. When compared with a conventional manual typing method, the CSR system proved to be useful in a clinical setting and saved time in generating radiological reports. The amount of time saved, however, greatly depended on the performance of the typist, the speaker, and on stored vocabulary provided by the CSR system. (orig.)

Skeletal development of the hand and wrist: digital bone age companion - a suitable alternative to the Greulich and Pyle atlas for bone age assessment?

International Nuclear Information System (INIS)

Bunch, Paul M.; Altes, Talissa A.; McIlhenny, Joan; Gaskin, Cree M.; Patrie, James

2017-01-01

To assess reader performance and subjective workflow experience when reporting bone age studies with a digital bone age reference as compared to the Greulich and Pyle atlas (G and P). We hypothesized that pediatric radiologists would achieve equivalent results with each method while digital workflow would improve speed, experience, and reporting quality. IRB approval was obtained for this HIPAA-compliant study. Two pediatric radiologists performed research interpretations of bone age studies randomized to either the digital (Digital Bone Age Companion, Oxford University Press) or G and P method, generating reports to mimic clinical workflow. Bone age standard selection, interpretation-reporting time, and user preferences were recorded. Reports were reviewed for typographical or speech recognition errors. Comparisons of agreement were conducted by way of Fisher's exact tests. Interpretation-reporting times were analyzed on the natural logarithmic scale via a linear mixed model and transformed to the geometric mean. Subjective workflow experience was compared with an exact binomial test. Report errors were compared via a paired random permutation test. There was no difference in bone age determination between atlases (p = 0.495). The interpretation-reporting time (p < 0.001) was significantly faster with the digital method. The faculty indicated preference for the digital atlas (p < 0.001). Signed reports had fewer errors with the digital atlas (p < 0.001). Bone age study interpretations performed with the digital method were similar to those performed with the Greulich and Pyle atlas. The digital atlas saved time, improved workflow experience, and reduced reporting errors relative to the Greulich and Pyle atlas when integrated into electronic workflow. (orig.)

Automatic digitization of SMA data

Science.gov (United States)

Väänänen, Mika; Tanskanen, Eija

2017-04-01

In the 1970's and 1980's the Scandinavian Magnetometer Array produced large amounts of excellent data from over 30 stations In Norway, Sweden and Finland. 620 film reels and 20 kilometers of film have been preserved and the longest time series produced in the campaign span almost uninterrupted for five years, but the data has never seen widespread use due to the choice of medium. Film is a difficult medium to digitize efficiently. Previously events of interest were searched for by hand and digitization was done by projecting the film on paper and plotting it by hand. We propose a method of automatically digitizing geomagnetic data stored on film and extracting the numerical values from the digitized data. The automatic digitization process helps in preserving old, valuable data that might otherwise go unused.

The left hand second to fourth digit ratio (2D:4D is not related to any physical fitness component in adolescent girls.

Directory of Open Access Journals (Sweden)

Maarten W Peeters

Full Text Available INTRODUCTION: The second to fourth-digit-ratio (2D:4D, a putative marker of prenatal androgen action and a sexually dimorphic trait, has been suggested to be related with fitness and sports performance, although results are not univocal. Most studies however focus on a single aspect of physical fitness or one sports discipline. METHODS: In this study the 2D:4D ratio of 178 adolescent girls (age 13.5-18 y was measured on X-rays of the left hand. The relation between 2D:4D digit ratio and multiple aspects of physical fitness (balance, speed of limb movement, flexibility, explosive strength, static strength, trunk strength, functional strength, running speed/agility, and endurance was studied by correlation analyses and stepwise multiple regression. For comparison the relation between these physical fitness components and a selected number of objectively measured anthropometric traits (stature, mass, BMI, somatotype components and the Bayer & Bailey androgyny index are presented alongside the results of 2D:4D digit ratio. RESULTS: Left hand 2D:4D digit ratio (0.925±0.019 was not significantly correlated with any of the physical fitness components nor any of the anthropometric variables included in the present study. 2D:4D did not enter the multiple stepwise regression for any of the physical fitness components in which other anthropometric traits explained between 9.2% (flexibility and 33.9% (static strength of variance. CONCLUSION: Unlike other anthropometric traits the 2D:4D digit ratio does not seem to be related to any physical fitness component in adolescent girls and therefore most likely should not be considered in talent detection programs for sporting ability in girls.

PBL, Hands-On/ Digital resources in Geology, (Teaching/ Learning)

Science.gov (United States)

Soares, Rosa; Santos, Cátia; Carvalho, Sara

2015-04-01

several instruments such as small questionnaires (Hot Potatoes), Gowin V, scientific report, a grid to evaluate group work and a grid to evaluate the development of competencies. This study intended to evaluate the success of a PBL intervention program when trying to improve students' outcomes. The positive impact obtained allowed us to advance some conclusions and instructional implications regarding teaching Rock Cycle through PBL and different digital and hands-on resources, obtained, especially in the students' questionnaires and Gowin V, allowed us to verify that students did learn about Rock Cycle and developed collaborative work skills.

Facial Emotion Recognition Using Context Based Multimodal Approach

Directory of Open Access Journals (Sweden)

Priya Metri

2011-12-01

Full Text Available Emotions play a crucial role in person to person interaction. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers. The ability to understand human emotions is desirable for the computer in several applications especially by observing facial expressions. This paper explores a ways of human-computer interaction that enable the computer to be more aware of the user’s emotional expressions we present a approach for the emotion recognition from a facial expression, hand and body posture. Our model uses multimodal emotion recognition system in which we use two different models for facial expression recognition and for hand and body posture recognition and then combining the result of both classifiers using a third classifier which give the resulting emotion . Multimodal system gives more accurate result than a signal or bimodal system

Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot

Directory of Open Access Journals (Sweden)

Godfrey Sasha B

2010-07-01

Full Text Available Abstract Background Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. Methods This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR. This device has been designed to provide full range of motion (ROM for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. Results For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05 between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05. Stroke subjects were capable of performing free hand movements inside of the exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P Conclusions Our pilot study shows that this device is capable of moving the hand's digits through

Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot

Science.gov (United States)

2010-01-01

Background Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. Methods This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. Results For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Conclusions Our pilot study shows that this device

Vocabulary Acquisition through Written Input: Effects of Form-Focused, Message-Oriented, and Comprehension Tasks

Science.gov (United States)

Tajeddin, Zia; Daraee, Dina

2013-01-01

The present study investigated the effect of form-focused and non-form-focused tasks on EFL learners' vocabulary learning through written input. The form-focused task aimed to draw students' attention to the word itself through word recognition activities. Non-form-focused tasks were divided into (a) the comprehension question task, which required…

Recognition of sign language gestures using neural networks

OpenAIRE

Simon Vamplew

2007-01-01

This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan) hand gestures.

The Relationship Between Digit Independence and Digital Sesamoids in Humans and a Proposal of a New Digital Sesamoid Evolutionary Hypothesis.

Science.gov (United States)

Yammine, Kaissar

2018-01-03

Digital sesamoids are found in the metapodial-phalangeal joints of most mammals and quadrupedal tetrapods, yet their functional significance is still unclear. During primate evolution, a slight decline in their frequency has been associated with brachiation in gibbons, followed by a quasi-complete absence in orangutans then a slight resurgence occurred in gorillas and chimpanzees. Simultaneously, forearm muscles showed a progressive division in hominoid evolution towards a more "individualistic" musculature yielding more mobility and independence to some fingers. In humans, sesamoids are consistently observed in thumbs and big toes and frequently in other hypermobile digits such as the index and little fingers. Using a simple mathematical equation, this paper attempted to quantify a presumed association between hypermobile fingers and sesamoid frequency and distribution in humans. To this, an anatomic definition of digital independence has been formulated which includes three variables; (1) number and (2) frequency of independent flexor/extensor forearm muscles destined to a single finger, (3) and number of free/absent webspace. Results of previous meta-analyses and means of big sample studies were used to evaluate the frequency of such muscles. The expected values obtained via this model were found to be very close to the observed (published) values of the ossified sesamoids in human hands, and that in terms of frequency and distribution. The findings in humans showed a quasi-linear association between the degree of mobility and sesamoid frequency. The more the number of independent muscles destined to a finger, the more its metacarpo-phalangeal joint is likely to bear sesamoids. Based on our results and on a new analysis of primates' forearm/hand muscles and sesamoid evolution, a new hypothesis is proposed to answer two questions; the evolution of digital sesamoid frequency in primates and its sesamoid distribution in human digits. It claims that the number

Advanced Digital Preservation

CERN Document Server

Giaretta, David

2011-01-01

There is growing recognition of the need to address the fragility of digital information, on which our society heavily depends for smooth operation in all aspects of daily life. This has been discussed in many books and articles on digital preservation, so why is there a need for yet one more? Because, for the most part, those other publications focus on documents, images and webpages -- objects that are normally rendered to be simply displayed by software to a human viewer. Yet there are clearly many more types of digital objects that may need to be preserved, such as databases, scientific da

Anatomy of a digital coherent receiver

DEFF Research Database (Denmark)

Borkowski, Robert; Zibar, Darko; Tafur Monroy, Idelfonso

2014-01-01

, orthonormaliation, chromatic dispersion compensation/nonlinear compensation, resampling a nd timing recovery, polarization demultiplexing and equalization, frequency and phase recovery, digital demodulation. We also describe novel subsystems of a digital coherent receiver: modulation format recognition......Digital coherent receivers have gained significant attention in the last decade. The reason for this is that coherent detection, along with digital signal processing (DSP) allows for substantial increase of the channel capacity by employing advanced detection techniques. In this paper, we first...

Attitudes of second language students towards self-editing their own written texts

Directory of Open Access Journals (Sweden)

Daniel Kasule

2010-05-01

Full Text Available Recognizing students’ deliberate e!orts to minimize errors in their written texts is valuable in seeing them as responsible active agents in text creation. This paper reports on a brief survey of the attitudes towards self-editing of seventy university students using a questionnaire and class discussion. The context of the study is characterized by its emphasis on evaluating the finished written product. Findings show that students appreciate the role of self-editing in minimizing errors in their texts and that it helps in eventually producing well-written texts. Conceptualizing writing as discourse and therefore as social practice leads to an understanding of writers as socially-situated actors; repositions the student writer as an active agent in text creation; and is central to student-centred pedagogy. We recommend the recognition of self-editing as a vital element in the writing process and that additional error detection mechanisms namely peers, the lecturer, and the computer, increase student autonomy.

Development and Comparative Study of Effects of Training Algorithms on Performance of Artificial Neural Network Based Analog and Digital Automatic Modulation Recognition

Directory of Open Access Journals (Sweden)

Jide Julius Popoola

2015-11-01

Full Text Available This paper proposes two new classifiers that automatically recognise twelve combined analog and digital modulated signals without any a priori knowledge of the modulation schemes and the modulation parameters. The classifiers are developed using pattern recognition approach. Feature keys extracted from the instantaneous amplitude, instantaneous phase and the spectrum symmetry of the simulated signals are used as inputs to the artificial neural network employed in developing the classifiers. The two developed classifiers are trained using scaled conjugate gradient (SCG and conjugate gradient (CONJGRAD training algorithms. Sample results of the two classifiers show good success recognition performance with an average overall recognition rate above 99.50% at signal-to-noise ratio (SNR value from 0 dB and above with the two training algorithms employed and an average overall recognition rate slightly above 99.00% and 96.40% respectively at - 5 dB SNR value for SCG and CONJGRAD training algorithms. The comparative performance evaluation of the two developed classifiers using the two training algorithms shows that the two training algorithms have different effects on both the response rate and efficiency of the two developed artificial neural networks classifiers. In addition, the result of the performance evaluation carried out on the overall success recognition rates between the two developed classifiers in this study using pattern recognition approach with the two training algorithms and one reported classifier in surveyed literature using decision-theoretic approach shows that the classifiers developed in this study perform favourably with regard to accuracy and performance probability as compared to classifier presented in previous study.

SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

OpenAIRE

S.PON SANGEETHA; DR.M.KARNAN

2014-01-01

The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

Skeletal development of the hand and wrist: digital bone age companion - a suitable alternative to the Greulich and Pyle atlas for bone age assessment?

Energy Technology Data Exchange (ETDEWEB)

Bunch, Paul M. [Massachusetts General Hospital, Department of Radiology, Boston, MA (United States); Altes, Talissa A. [University of Missouri, Department of Radiology, Columbia, MO (United States); McIlhenny, Joan; Gaskin, Cree M. [University of Virginia Health System, Department of Radiology and Medical Imaging, PO Box 800170, Charlottesville, VA (United States); Patrie, James [University of Virginia Health System, Department of Health Evaluation Sciences, PO Box 800717, Charlottesville, VA (United States)

2017-06-15

To assess reader performance and subjective workflow experience when reporting bone age studies with a digital bone age reference as compared to the Greulich and Pyle atlas (G and P). We hypothesized that pediatric radiologists would achieve equivalent results with each method while digital workflow would improve speed, experience, and reporting quality. IRB approval was obtained for this HIPAA-compliant study. Two pediatric radiologists performed research interpretations of bone age studies randomized to either the digital (Digital Bone Age Companion, Oxford University Press) or G and P method, generating reports to mimic clinical workflow. Bone age standard selection, interpretation-reporting time, and user preferences were recorded. Reports were reviewed for typographical or speech recognition errors. Comparisons of agreement were conducted by way of Fisher's exact tests. Interpretation-reporting times were analyzed on the natural logarithmic scale via a linear mixed model and transformed to the geometric mean. Subjective workflow experience was compared with an exact binomial test. Report errors were compared via a paired random permutation test. There was no difference in bone age determination between atlases (p = 0.495). The interpretation-reporting time (p < 0.001) was significantly faster with the digital method. The faculty indicated preference for the digital atlas (p < 0.001). Signed reports had fewer errors with the digital atlas (p < 0.001). Bone age study interpretations performed with the digital method were similar to those performed with the Greulich and Pyle atlas. The digital atlas saved time, improved workflow experience, and reduced reporting errors relative to the Greulich and Pyle atlas when integrated into electronic workflow. (orig.)

Iris image enhancement for feature recognition and extraction

CSIR Research Space (South Africa)

Mabuza, GP

2012-10-01

Full Text Available the employment of other algorithms and commands so as to better present and demonstrate the obtained results. Edge detection and enhancing images for use in an iris recognition system allow for efficient recognition and extraction of iris patterns. REFERENCES... Gonzalez, R.C. and Woods, R.E. 2002. Digital Image Processing 2nd Edition, Instructor?s manual .Englewood Cliffs, Prentice Hall, pp 17-36. Proen?a, H. and Alexandre, L.A. 2007. Toward Noncooperative Iris Recognition: A classification approach using...

The hand of Homo naledi

Science.gov (United States)

Kivell, Tracy L.; Deane, Andrew S.; Tocheri, Matthew W.; Orr, Caley M.; Schmid, Peter; Hawks, John; Berger, Lee R.; Churchill, Steven E.

2015-01-01

A nearly complete right hand of an adult hominin was recovered from the Rising Star cave system, South Africa. Based on associated hominin material, the bones of this hand are attributed to Homo naledi. This hand reveals a long, robust thumb and derived wrist morphology that is shared with Neandertals and modern humans, and considered adaptive for intensified manual manipulation. However, the finger bones are longer and more curved than in most australopiths, indicating frequent use of the hand during life for strong grasping during locomotor climbing and suspension. These markedly curved digits in combination with an otherwise human-like wrist and palm indicate a significant degree of climbing, despite the derived nature of many aspects of the hand and other regions of the postcranial skeleton in H. naledi. PMID:26441219

Digital filters

CERN Document Server

Hamming, Richard W

1997-01-01

Digital signals occur in an increasing number of applications: in telephone communications; in radio, television, and stereo sound systems; and in spacecraft transmissions, to name just a few. This introductory text examines digital filtering, the processes of smoothing, predicting, differentiating, integrating, and separating signals, as well as the removal of noise from a signal. The processes bear particular relevance to computer applications, one of the focuses of this book.Readers will find Hamming's analysis accessible and engaging, in recognition of the fact that many people with the s

Recognition of sign language gestures using neural networks

Directory of Open Access Journals (Sweden)

Simon Vamplew

2007-04-01

Full Text Available This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan hand gestures.

Library management for the digital age a new paradigm

CERN Document Server

Todaro, Julie

2014-01-01

This revolutionary introduction to library management is the first conceived in and written for a digital age. Library Management for the Digital Age covers hierarchies, policies, communication, working relationships, facilities, human resources, settings, customer services, budgeting, and emergency management.

Digital Immigrants and Digital Natives: Learning Business Informatics at Higher Educational Level

OpenAIRE

Suša, Dalia

2014-01-01

Background: The term digital natives refer to those born since the 1980s and have been growing up surrounded by technology. On the other hand, digital immigrants are born before 1980s and learned how to use technology later in life. Objectives: Goal of the paper is to explore attitudes of digital native students on the course of Business Informatics at higher educational institutions (HEIs), and to compare them with attitudes of digital immigrants. Methods/Approach: The survey was conducted i...

[Hand hygiene technique assessment using electronic equipment in 26 Hungarian healthcare institutions].

Science.gov (United States)

Lehotsky, Ákos; Morvai, Júlia; Szilágyi, László; Bánsághi, Száva; Benkó, Alíz; Haidegger, Tamás

2017-07-01

Hand hygiene is probably the most effective tool of nosocomial infection prevention, however, proper feedback and control is needed to develop the individual hand hygiene practice. Assessing the efficiency of modern education tools, and digital demonstration and verification equipment during their wide-range deployment. 1269 healthcare workers took part in a training organized by our team. The training included the assessment of the participants' hand hygiene technique to identify the most often missed areas. The hand hygiene technique was examined by a digital device. 33% of the participants disinfected their hands incorrectly. The most often missed sites are the fingertips (33% on the left hand, 37% on the right hand) and the thumbs (42% on the left hand, 32% on the right hand). The feedback has a fundamental role in the development of the hand hygiene technique. With the usage of electronic devices feedback can be provided efficiently and simply. Orv Hetil. 2017; 158(29): 1143-1148.

Understanding Human Hand Gestures for Learning Robot Pick-and-Place Tasks

Directory of Open Access Journals (Sweden)

Hsien-I Lin

2015-05-01

Full Text Available Programming robots by human demonstration is an intuitive approach, especially by gestures. Because robot pick-and-place tasks are widely used in industrial factories, this paper proposes a framework to learn robot pick-and-place tasks by understanding human hand gestures. The proposed framework is composed of the module of gesture recognition and the module of robot behaviour control. For the module of gesture recognition, transport empty (TE, transport loaded (TL, grasp (G, and release (RL from Gilbreth's therbligs are the hand gestures to be recognized. A convolution neural network (CNN is adopted to recognize these gestures from a camera image. To achieve the robust performance, the skin model by a Gaussian mixture model (GMM is used to filter out non-skin colours of an image, and the calibration of position and orientation is applied to obtain the neutral hand pose before the training and testing of the CNN. For the module of robot behaviour control, the corresponding robot motion primitives to TE, TL, G, and RL, respectively, are implemented in the robot. To manage the primitives in the robot system, a behaviour-based programming platform based on the Extensible Agent Behavior Specification Language (XABSL is adopted. Because the XABSL provides the flexibility and re-usability of the robot primitives, the hand motion sequence from the module of gesture recognition can be easily used in the XABSL programming platform to implement the robot pick-and-place tasks. The experimental evaluation of seven subjects performing seven hand gestures showed that the average recognition rate was 95.96%. Moreover, by the XABSL programming platform, the experiment showed the cube-stacking task was easily programmed by human demonstration.

Incidence of Apical Crack Initiation during Canal Preparation using Hand Stainless Steel (K-File) and Hand NiTi (Protaper) Files.

Science.gov (United States)

Soni, Dileep; Raisingani, Deepak; Mathur, Rachit; Madan, Nidha; Visnoi, Suchita

2016-01-01

To evaluate the incidence of apical crack initiation during canal preparation with stainless steel K-files and hand protaper files (in vitro study). Sixty extracted mandibular premo-lar teeth are randomly selected and embedded in an acrylic tube filled with autopolymerizing resin. A baseline image of the apical surface of each specimen was recorded under a digital microscope (80×). The cervical and middle thirds of all samples were flared with #2 and #1 Gates-Glidden (GG) drills, and a second image was recorded. The teeth were randomly divided into four groups of 15 teeth each according to the file type (hand K-file and hand-protaper) and working length (WL) (instrumented at WL and 1 mm less than WL). Final image after dye penetration and photomicrograph of the apical root surface were digitally recorded. Maximum numbers of cracks were observed with hand protaper files compared with hand K-file at the WL and 1 mm short of WL. Chi-square testing revealed a highly significant effect of WL on crack formation at WL and 1 mm short of WL (p = 0.000). Minimum numbers of cracks at WL and 1 mm short of WL were observed with hand K-file and maximum with hand protaper files. Soni D, Raisingani D, Mathur R, Madan N, Visnoi S. Incidence of Apical Crack Initiation during Canal Preparation using Hand Stainless Steel (K-File) and Hand NiTi (Protaper) Files. Int J Clin Pediatr Dent 2016;9(4):303-307.

The processing of auditory and visual recognition of self-stimuli.

Science.gov (United States)

Hughes, Susan M; Nicholson, Shevon E

2010-12-01

This study examined self-recognition processing in both the auditory and visual modalities by determining how comparable hearing a recording of one's own voice was to seeing photograph of one's own face. We also investigated whether the simultaneous presentation of auditory and visual self-stimuli would either facilitate or inhibit self-identification. Ninety-one participants completed reaction-time tasks of self-recognition when presented with their own faces, own voices, and combinations of the two. Reaction time and errors made when responding with both the right and left hand were recorded to determine if there were lateralization effects on these tasks. Our findings showed that visual self-recognition for facial photographs appears to be superior to auditory self-recognition for voice recordings. Furthermore, a combined presentation of one's own face and voice appeared to inhibit rather than facilitate self-recognition and there was a left-hand advantage for reaction time on the combined-presentation tasks. Copyright © 2010 Elsevier Inc. All rights reserved.

Speech recognition implementation in radiology

International Nuclear Information System (INIS)

White, Keith S.

2005-01-01

Continuous speech recognition (SR) is an emerging technology that allows direct digital transcription of dictated radiology reports. The SR systems are being widely deployed in the radiology community. This is a review of technical and practical issues that should be considered when implementing an SR system. (orig.)

When Forgetting Becomes Digital

DEFF Research Database (Denmark)

Marton, Attila; Kallinikos, Jannis

The structure of social memory is in a process of significant change as social operations of forgetting and remembering are increasingly written in IT and mediated in digital media. Based on an in-depth case study about the digitalization of memory institutions (libraries, archives, museums......), the paper demonstrates the emergence of a digital social memory structure that stores data as a means of forgetting. Building on such a concept, we explain the shifting structure of social memory from pre-defined, taxonomic order to algorithmic computation of artefacts and ordering. Finally, we draw...... implications from our study with regards to core organizational concepts of institutions and platforms as well as broader categories of information infrastructures and a sociology of digital knowledge....

The digital spine

DEFF Research Database (Denmark)

Ebbesen, Toke Riis

2019-01-01

In the words of the Oxford English Dictionary, a book is 'a portable volume consisting of a series of written, printed, or illustrated pages bound together for ease of reading' (‘book, n.’nd). Yet, the world of books isn’t what it used to be. If differences between media are material differences...... analyze books as digital or even 'post-digital' artifacts (Cramer 2014), while preserving the material dimension of the book artifact. In other words: is there is such a thing as a (post-)digital spine, and how can it be described? This article outlines an answer to this question within an inferential...... (Seiter 2015), and books are produced, distributed and read on various digital media and devices, it is no longer possible to understand digital books on the basis of the material and syntactical features of the codex artifact. It then becomes important to discuss how to conceptualize and subsequently...

Indoor navigation by image recognition

Science.gov (United States)

Choi, Io Teng; Leong, Chi Chong; Hong, Ka Wo; Pun, Chi-Man

2017-07-01

With the progress of smartphones hardware, it is simple on smartphone using image recognition technique such as face detection. In addition, indoor navigation system development is much slower than outdoor navigation system. Hence, this research proves a usage of image recognition technique for navigation in indoor environment. In this paper, we introduced an indoor navigation application that uses the indoor environment features to locate user's location and a route calculating algorithm to generate an appropriate path for user. The application is implemented on Android smartphone rather than iPhone. Yet, the application design can also be applied on iOS because the design is implemented without using special features only for Android. We found that digital navigation system provides better and clearer location information than paper map. Also, the indoor environment is ideal for Image recognition processing. Hence, the results motivate us to design an indoor navigation system using image recognition.

Recognition and inference of crevice processing on digitized paintings

Science.gov (United States)

Karuppiah, S. P.; Srivatsa, S. K.

2013-03-01

This paper is designed to detect and removal of cracks on digitized paintings. The cracks are detected by threshold. Afterwards, the thin dark brush strokes which have been misidentified as cracks are removed using Median radial basis function neural network on hue and saturation data, Semi-automatic procedure based on region growing. Finally, crack is filled using wiener filter. The paper is well designed in such a way that most of the cracks on digitized paintings have identified and removed. The paper % of betterment is 90%. This paper helps us to perform not only on digitized paintings but also the medical images and bmp images. This paper is implemented by Mat Lab.

Hands on, mobiles on The use of a digital narrative as a scaffolding remedy in a classical science centre

Directory of Open Access Journals (Sweden)

Anne Kahr-Højland

2010-12-01

Full Text Available This article examines an educational design experiment which aimed to support young people’s involvement and reflection in the exhibition at a Danish science centre. The experiment consisted in the examination of the design and implementation of a mobile phone facilitated narrative, which was planned as a so-called scaffolding remedy in the hands-on based exhibition. The digital narrative, called EGO-TRAP, was developed using Design-Based Research as the overall methodological framework. The study of students’ interactions in the exhibition suggests, among other things, that because of its quality as a digital narrative, EGO-TRAP scaffolds pleasurable engagement and counteracts the tendency of "random button pressing" that often occurs in classical science centre exhibitions. In this connection, the mobile phone plays an essential role due to the fact that it, as the favoured media by the young students, offers an experience which they describe as both personal and flexible.

Analysis of Information Remaining on Hand Held Devices Offered for Sale on the Second Hand Market

Directory of Open Access Journals (Sweden)

Andy Jones

2008-06-01

Full Text Available The ownership and use of mobile phones, Personal Digital Assistants and other hand held devices is now ubiquitous both for home and business use. The majority of these devices have a high initial cost, a relatively short period before they become obsolescent and a relatively low second hand value.  As a result of this, when the devices are replaced, there are indications that they tend to be discarded.  As technology has continued to develop, it has led to an increasing diversity in the number and type of devices that are available, and the processing power and the storage capacity of the digital storage in the device. All organisations, whether in the public or private sector increasingly use hand held devices that contain digital media for the storage of information relating to their business, their employees or their customers. Similarly, individual private users increasingly use hand held devices containing digital media for the storage of information relating to their private lives.The research revealed that a significant number of organisations and private users are ignorant or misinformed about the volume and type of information that is stored on the hand held devices and the media on which it is stored.  It is apparent that they have either not considered, or are unaware of, the potential impact of this information becoming available to their competitors or those with criminal intent.This main purpose of this study was to gain an understanding of the volume and type of information that may remain on hand held devices that are offered for sale on the second hand market.  A second aim of the research was to determine the level of damage that could, potentially be caused, if the information that remains on the devices fell into the wrong hands.  The study examined a number of hand held devices that had been obtained from sources in the UK and Australia that ranged from internet auction sites, to private sales and commercial

Hand pose recognition in First Person Vision through graph spectral analysis

NARCIS (Netherlands)

Baydoun, Mohamad; Betancourt, Alejandro; Morerio, Pietro; Marcenaro, Lucio; Rauterberg, Matthias; Regazzoni, Carlo

2017-01-01

© 2017 IEEE. With the growing availability of wearable technology, video recording devices have become so intimately tied to individuals, that they are able to record the movements of users' hands, making hand-based applications one the most explored area in First Person Vision (FPV). In particular,

Humans can integrate force feedback to toes in their sensorimotor control of a robotic hand.

Science.gov (United States)

Panarese, Alessandro; Edin, Benoni B; Vecchi, Fabrizio; Carrozza, Maria C; Johansson, Roland S

2009-12-01

Tactile sensory feedback is essential for dexterous object manipulation. Users of hand myoelectric prostheses without tactile feedback must depend essentially on vision to control their device. Indeed, improved tactile feedback is one of their main priorities. Previous research has provided evidence that conveying tactile feedback can improve prostheses control, although additional effort is required to solve problems related to pattern recognition learning, unpleasant sensations, sensory adaptation, and low spatiotemporal resolution. Still, these studies have mainly focused on providing stimulation to hairy skin regions close to the amputation site, i.e., usually to the upper arm. Here, we explored the possibility to provide tactile feedback to the glabrous skin of toes, which have mechanical and neurophysiological properties similar to the fingertips. We explored this paradigm in a grasp-and-lift task, in which healthy participants controlled two opposing digits of a robotic hand by changing the spacing of their index finger and thumb. The normal forces applied by the robotic fingertips to a test object were fed back to the right big and second toe. We show that within a few lifting trials, all the participants incorporated the force feedback received by the foot in their sensorimotor control of the robotic hand.

Handwriting Moroccan regions recognition using Tifinagh character

Directory of Open Access Journals (Sweden)

B. El Kessab

2015-09-01

In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region. The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand.

The influence of the pregroove on the shape of thermomagnetically written domains

International Nuclear Information System (INIS)

Ichihara, K.

1990-01-01

In order to clarify the influence of pregrooved substrates on the shape of thermomagnetically written domains, the difference between the shape of the domains written on a pregrooved area and that written on a mirror area have been examined. Trilayered magneto-optical media, which had rare-earth- (RE-) rich TbFeCo films, transition-metal-rich TbFeCo films, and RE-rich GdTbFeCo films as a recording layer, were sputtered on disk substrates. The substrates had both a pregrooved area and a mirror area in a recording track. The domains were written in each medium by varying the recording power and the external field, and were observed by an Ar + -laser scanning polarized microscope. In the case of TbFeCo media which were written with lower recording power condition, the shape of the domains on a pregrooved area were almost the same as those written on a mirror area. On the other hand, the widths of the domains written on a mirror area became larger than those of domains written on a pregrooved area when the recording power was increased. In the case of a GdTbFeCo medium, the widths of the domains written on a mirror area were much larger than those of domains written on a pregrooved area independent of the recording conditions. The lengths of the domains written on both areas were almost the same for all cases. It is believed that the reason for the experimental results is that thermal diffusion in the film plane is suppressed at the step of a pregroove. The different result between TbFeCo and GdTbFeCo films is believed to come from the differences in the contracting forces on the domain walls during the writing process

Online handwritten mathematical expression recognition

Science.gov (United States)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

A Survey of Evaluation in Music Genre Recognition

DEFF Research Database (Denmark)

Sturm, Bob L.

2012-01-01

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic data, and other modalities. While reviews have been written of some of this work before, no survey has been made of the approaches to evaluating approaches to MGR. This paper compiles a bibliography of work...

Recognition of sport players' numbers using fast-color segmentation

Science.gov (United States)

Verleysen, Cédric; De Vleeschouwer, Christophe

2012-01-01

This paper builds on a prior work for player detection, and proposes an efficient and effective method to distinguish among players based on the numbers printed on their jerseys. To extract the numbers, the dominant colors of the jersey are learnt during an initial phase and used to speed up the segmentation of the candidate digit regions. An additional set of criteria, considering the relative position and size (compared to the player bounding box) and the density (compared to the digit rectangular support) of the digit, are used to filter out the regions that obviously do not correspond to a digit. Once the plausible digit regions have been extracted, their recognition is based on feature-based classification. A number of original features are proposed to increase the robustness against digit appearance changes, resulting from the font thickness variability and from the deformations of the jersey during the game. Finally, the efficiency and the effectiveness of the proposed method are demonstrated on a real-life basketball dataset. It shows that the proposed segmentation runs about ten times faster than the mean-shift algorithm, but also outlines that the proposed additional features significantly increase the digit recognition accuracy. Despite significant deformations, 40% of the samples, that can be visually recognized as digits, are well classified as numbers. Out of these classified samples, more than 80% of them are correctly recognized. Besides, more than 95% of the samples, that are not numbers, are correctly identified as non-numbers.

Reducing weight precision of convolutional neural networks towards large-scale on-chip image recognition

Science.gov (United States)

Ji, Zhengping; Ovsiannikov, Ilia; Wang, Yibing; Shi, Lilong; Zhang, Qiang

2015-05-01

In this paper, we develop a server-client quantization scheme to reduce bit resolution of deep learning architecture, i.e., Convolutional Neural Networks, for image recognition tasks. Low bit resolution is an important factor in bringing the deep learning neural network into hardware implementation, which directly determines the cost and power consumption. We aim to reduce the bit resolution of the network without sacrificing its performance. To this end, we design a new quantization algorithm called supervised iterative quantization to reduce the bit resolution of learned network weights. In the training stage, the supervised iterative quantization is conducted via two steps on server - apply k-means based adaptive quantization on learned network weights and retrain the network based on quantized weights. These two steps are alternated until the convergence criterion is met. In this testing stage, the network configuration and low-bit weights are loaded to the client hardware device to recognize coming input in real time, where optimized but expensive quantization becomes infeasible. Considering this, we adopt a uniform quantization for the inputs and internal network responses (called feature maps) to maintain low on-chip expenses. The Convolutional Neural Network with reduced weight and input/response precision is demonstrated in recognizing two types of images: one is hand-written digit images and the other is real-life images in office scenarios. Both results show that the new network is able to achieve the performance of the neural network with full bit resolution, even though in the new network the bit resolution of both weight and input are significantly reduced, e.g., from 64 bits to 4-5 bits.

A portable digital speech-rate converter for hearing impairment.

Science.gov (United States)

Nejime, Y; Aritsuka, T; Imamura, T; Ifukube, T; Matsushima, J

1996-06-01

A real-time hand-sized portable device that slows speech speed without changing the pitch is proposed for hearing impairment. By using this device, people can listen to fast speech at a comfortable speed. A combination of solid-state memory recording and real-time digital signal processing with a single chip processor enables this unique function. A simplified pitchsynchronous, time-scale-modification algorithm is proposed to minimize the complexity of the DSP operation. Unlike the traditional algorithm, this dynamic-processing algorithm reduces distortion even when the expansion rate is only just above 1. Seven out of 10 elderly hearing-impaired listeners showed improvement in a sentence recognition test when using speech-rate conversion with the largest expansion rate, although no improvement was observed in a word recognition test. Some subjects who showed large improvement had limited auditory temporal resolution, but the correlation was not significant. The results suggest that, unlike conventional hearing aids, this device can be used to overcome the deterioration of auditory ability by improving the transfer of information from short-term (echoic) memory into a more stable memory trace in the human auditory system.

Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

Science.gov (United States)

Hunter, Cynthia R; Pisoni, David B

Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Science.gov (United States)

Kulkarni, Shruti R; Rajendran, Bipin

2018-07-01

We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse biological spike rates below 300Hz achieves a classification accuracy of 98.17% on the MNIST test database with four times fewer parameters compared to the state-of-the-art. We present several insights from extensive numerical experiments regarding optimization of learning parameters and network configuration to improve its accuracy. We also describe a number of strategies to optimize the SNN for implementation in memory and energy constrained hardware, including approximations in computing the neuronal dynamics and reduced precision in storing the synaptic weights. Experiments reveal that even with 3-bit synaptic weights, the classification accuracy of the designed SNN does not degrade beyond 1% as compared to the floating-point baseline. Further, the proposed SNN, which is trained based on the precise spike timing information outperforms an equivalent non-spiking artificial neural network (ANN) trained using back propagation, especially at low bit precision. Thus, our study shows the potential for realizing efficient neuromorphic systems that use spike based information encoding and learning for real-world applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exhibits Recognition System for Combining Online Services and Offline Services

Science.gov (United States)

Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

2017-10-01

In order to achieve a more convenient and accurate digital museum navigation, we have developed a real-time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

Teaching digital pathology: The international school of digital pathology and proposed syllabus

Directory of Open Access Journals (Sweden)

Vincenzo Della Mea

2017-01-01

Full Text Available Digital pathology is an interdisciplinary field where competency in pathology, laboratory techniques, informatics, computer science, information systems, engineering, and even biology converge. This implies that teaching students about digital pathology requires coverage, expertise, and hands-on experience in all these disciplines. With this in mind, a syllabus was developed for a digital pathology summer school aimed at professionals in the aforementioned fields, as well as trainees and doctoral students. The aim of this communication is to share the context, rationale, and syllabus for this school of digital pathology.

Neural network recognition of mammographic lesions

International Nuclear Information System (INIS)

Oldham, W.J.B.; Downes, P.T.; Hunter, V.

1987-01-01

A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed

Digitized hand-wrist radiographs: comparison of subjective and software-derived image quality at various compression ratios.

Science.gov (United States)

McCord, Layne K; Scarfe, William C; Naylor, Rachel H; Scheetz, James P; Silveira, Anibal; Gillespie, Kevin R

2007-05-01

The objectives of this study were to compare the effect of JPEG 2000 compression of hand-wrist radiographs on observer image quality qualitative assessment and to compare with a software-derived quantitative image quality index. Fifteen hand-wrist radiographs were digitized and saved as TIFF and JPEG 2000 images at 4 levels of compression (20:1, 40:1, 60:1, and 80:1). The images, including rereads, were viewed by 13 orthodontic residents who determined the image quality rating on a scale of 1 to 5. A quantitative analysis was also performed by using a readily available software based on the human visual system (Image Quality Measure Computer Program, version 6.2, Mitre, Bedford, Mass). ANOVA was used to determine the optimal compression level (P quality. When we used quantitative indexes, the JPEG 2000 images had lower quality at all compression ratios compared with the original TIFF images. There was excellent correlation (R2 >0.92) between qualitative and quantitative indexes. Image Quality Measure indexes are more sensitive than subjective image quality assessments in quantifying image degradation with compression. There is potential for this software-based quantitative method in determining the optimal compression ratio for any image without the use of subjective raters.

Identification of digitized particle trajectories

CERN Document Server

Grote, H; Lassalle, J C; Zanella, P

1973-01-01

High-energy Physics Laboratories make increasing use of particle detectors which directly produce digital measurements of trajectories at very high rates. Data collected in vast amounts during experiments are then analysed by computer programs whose first task is the recognition of tracks and reconstruction of the interesting events. This paper discusses the applicability of various Pattern Recognition approaches. Examples are given of the problems and the practical achievements in this field.

Successful replantation in ten-digit amputation.

Science.gov (United States)

Kantarci, Umit; Cepel, Selim; Buldu, Halil

2010-01-01

Amputations involving ten digits are very rare because of different lengths of the digits. A 34-year-old man working in a printing house presented one hour after guillotine amputation involving all ten digits. Surgery was initiated 80 minutes after admission and took seven hours. Under axillary anesthesia, the operation was performed by two teams each consisting of two microsurgeons and two assistants. Replantation was completed without the use of any skin graft or flap. Fingertip examination showed poor arterial circulation in the second, third, and fourth digits of the left hand after 24 hours of replantation and surgical exploration was performed, during which anastomosis of the ulnar digital artery of the second digit was re-established and a Y-shaped vein graft was placed at the level of the third web to restore revascularization of the third and fourth digits. However, these interventions did not prevent the development of necrosis in the distal segment of the fourth digit which resulted in dry gangrene that required amputation. After 38 months of replantation, radiographic examination showed complete union in all fingers without malunion or damage to the joint surface and about 8 degrees of medial angulation in the proximal phalanx of the fourth digit of the right hand. The patient did not have difficulty in performing daily activities and had a considerably good pinching. Losses of active range of motion of the metacarpophalangeal and interphalangeal joints were within the rage of 10 to 30 degrees in both hands. In the assessment of sensation, static and dynamic two-point discrimination test results were 6.1 mm and 4.0 mm, respectively.

Using an Analysis of Behavior Change to Inform Effective Digital Intervention Design: How Did the PRIMIT Website Change Hand Hygiene Behavior Across 8993 Users?

Science.gov (United States)

Ainsworth, B; Steele, M; Stuart, B; Joseph, J; Miller, S; Morrison, L; Little, P; Yardley, L

2017-06-01

In designing digital interventions for healthcare, it is important to understand not just whether interventions work but also how and for whom-including whether individual intervention components have different effects, whether a certain usage threshold is required to change behavior in each intervention and whether usage differs across population subgroups. We investigated these questions using data from a large trial of the digital PRimary care trial of a website based Infection control intervention to Modify Influenza-like illness and respiratory tract infection Transmission) (PRIMIT) intervention, which aimed to reduce respiratory tract infections (RTIs) by increasing hand hygiene behavior. Baseline and follow-up questionnaires measured behaviors, intentions and attitudes in hand hygiene. In conjunction with objective measures of usage of the four PRIMIT sessions, we analysed these observational data to examine mechanisms of behavior change in 8993 intervention users. We found that the PRIMIT intervention changed behavior, intentions and attitudes, and this change was associated with reduced RTIs. The largest hand hygiene change occurred after the first session, with incrementally smaller changes after each subsequent session, suggesting that engagement with the core behavior change techniques included in the first session was necessary and sufficient for behavior change. The intervention was equally effective for men and women, older and younger people and was particularly effective for those with lower levels of education. Our well-powered analysis has implications for intervention development. We were able to determine a 'minimum threshold' of intervention engagement that is required for hand hygiene change, and we discuss the potential implications this (and other analyses of this type) may have for further intervention development. We also discuss the application of similar analyses to other interventions.

Recognition of oral spelling is diagnostic of the central reading processes.

Science.gov (United States)

Schubert, Teresa; McCloskey, Michael

2015-01-01

The task of recognition of oral spelling (stimulus: "C-A-T", response: "cat") is often administered to individuals with acquired written language disorders, yet there is no consensus about the underlying cognitive processes. We adjudicate between two existing hypotheses: Recognition of oral spelling uses central reading processes, or recognition of oral spelling uses central spelling processes in reverse. We tested the recognition of oral spelling and spelling to dictation abilities of a single individual with acquired dyslexia and dysgraphia. She was impaired relative to matched controls in spelling to dictation but unimpaired in recognition of oral spelling. Recognition of oral spelling for exception words (e.g., colonel) and pronounceable nonwords (e.g., larth) was intact. Our results were predicted by the hypothesis that recognition of oral spelling involves the central reading processes. We conclude that recognition of oral spelling is a useful tool for probing the integrity of the central reading processes.

Optical character recognition systems for different languages with soft computing

CERN Document Server

Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

2017-01-01

The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

Pattern recognition in high energy physics

International Nuclear Information System (INIS)

Tenner, A.G.

1980-01-01

In high energy physics experiments tracks of elementary particles are recorded by different types of equipment. Coordinates of points of these tracks have to be measured for the geometrical reconstruction and the further analysis of the observed events. Pattern recognition methods may facilitate the detection of tracks or whole events and the separation of relevant from non-relevant information. They may also serve for the automation of measurement. Generally, all work is done by digital computation. In a bubble chamber tracks appear as strings of vapour bubbles that can be recorded photographically. Two methods of pattern recognition are discussed. The flying spot digitizer encodes the pattern on the photograph into point coordinates in the memory of a computer. The computer carries out the pattern recognition procedure entirely on the basis of the stored information. Cathode ray instruments scan the photograph by means of a computer steered optical device. Data acquisition from the film is performed in a feedback loop of the computation. In electronic experimental equipment tracks are defined by the spacial distribution of hits of counters (wire counters, scintillation counters, spark chambers). Pattern recognition is generally performed in various stages both by on-line and off-line equipment. Problems in the data handling arise both from the great abundance of data and from the time limits imposed on the on-line computation by high measuring rates. The on-line computation is carried out by hardwired logic, small computers, and to an increasing extent by microprocessors. (Auth.)

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

Science.gov (United States)

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

Prospective randomized study of contrast reaction management curricula: Computer-based interactive simulation versus high-fidelity hands-on simulation

Energy Technology Data Exchange (ETDEWEB)

Wang, Carolyn L., E-mail: wangcl@uw.edu [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States); Schopp, Jennifer G.; Kani, Kimia [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States); Petscavage-Thomas, Jonelle M. [Penn State Hershey Medical Center, Department of Radiology, 500 University Drive, Hershey, PA 17033 (United States); Zaidi, Sadaf; Hippe, Dan S.; Paladin, Angelisa M.; Bush, William H. [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States)

2013-12-01

Purpose: We developed a computer-based interactive simulation program for teaching contrast reaction management to radiology trainees and compared its effectiveness to high-fidelity hands-on simulation training. Materials and methods: IRB approved HIPAA compliant prospective study of 44 radiology residents, fellows and faculty who were randomized into either the high-fidelity hands-on simulation group or computer-based simulation group. All participants took separate written tests prior to and immediately after their intervention. Four months later participants took a delayed written test and a hands-on high-fidelity severe contrast reaction scenario performance test graded on predefined critical actions. Results: There was no statistically significant difference between the computer and hands-on groups’ written pretest, immediate post-test, or delayed post-test scores (p > 0.6 for all). Both groups’ scores improved immediately following the intervention (p < 0.001). The delayed test scores 4 months later were still significantly higher than the pre-test scores (p ≤ 0.02). The computer group's performance was similar to the hands-on group on the severe contrast reaction simulation scenario test (p = 0.7). There were also no significant differences between the computer and hands-on groups in performance on the individual core competencies of contrast reaction management during the contrast reaction scenario. Conclusion: It is feasible to develop a computer-based interactive simulation program to teach contrast reaction management. Trainees that underwent computer-based simulation training scored similarly on written tests and on a hands-on high-fidelity severe contrast reaction scenario performance test as those trained with hands-on high-fidelity simulation.

Prospective randomized study of contrast reaction management curricula: Computer-based interactive simulation versus high-fidelity hands-on simulation

International Nuclear Information System (INIS)

Wang, Carolyn L.; Schopp, Jennifer G.; Kani, Kimia; Petscavage-Thomas, Jonelle M.; Zaidi, Sadaf; Hippe, Dan S.; Paladin, Angelisa M.; Bush, William H.

2013-01-01

Purpose: We developed a computer-based interactive simulation program for teaching contrast reaction management to radiology trainees and compared its effectiveness to high-fidelity hands-on simulation training. Materials and methods: IRB approved HIPAA compliant prospective study of 44 radiology residents, fellows and faculty who were randomized into either the high-fidelity hands-on simulation group or computer-based simulation group. All participants took separate written tests prior to and immediately after their intervention. Four months later participants took a delayed written test and a hands-on high-fidelity severe contrast reaction scenario performance test graded on predefined critical actions. Results: There was no statistically significant difference between the computer and hands-on groups’ written pretest, immediate post-test, or delayed post-test scores (p > 0.6 for all). Both groups’ scores improved immediately following the intervention (p < 0.001). The delayed test scores 4 months later were still significantly higher than the pre-test scores (p ≤ 0.02). The computer group's performance was similar to the hands-on group on the severe contrast reaction simulation scenario test (p = 0.7). There were also no significant differences between the computer and hands-on groups in performance on the individual core competencies of contrast reaction management during the contrast reaction scenario. Conclusion: It is feasible to develop a computer-based interactive simulation program to teach contrast reaction management. Trainees that underwent computer-based simulation training scored similarly on written tests and on a hands-on high-fidelity severe contrast reaction scenario performance test as those trained with hands-on high-fidelity simulation

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

Science.gov (United States)

Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

2017-01-01

Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

THE ORTHOGRAPHIC NORM IN SECONDARY SCHOOL STUDENTS’ WRITTEN ASSIGNMENTS

Directory of Open Access Journals (Sweden)

Ivana Đorđev

2016-06-01

Full Text Available This paper presents the results of research conducted with the primary objective to determine in which areas secondary school students usually make orthographic mistakes when writing (official written assignments. Starting from the hypothesis that the punctuation writing of whole and split words are areas in which secondary school students (regardless of age and school orientation achieved the weakest achievements an (exploratory research was conducted on a corpus of 3,135 written assignments written in the school year of 2010/11. The research sample was intentional, descriptive and analytical methods were used for the description and the analysis of the results. The results showed the following (1 secondary school students usually make mistakes in punctuation of written assignments - we recorded 4,487 errors in the use of signs to denote intonation and meaning of a text (errors of this type make 53.93% of the total number of spelling errors reported in the corpus of research; by frequency of errors the second are errors related to writing whole and split words (11.02%, the third error is in the use of the capital letter (9.34%; (2 most problems in orthography have second grade students, quantum of mistakes is almost the same with first graders and seniors, but in all grades the most frequent errors are in punctuation, writing of whole and split words and the use of capital letters; (3 Although school orientation affects the spelling skills of pupils, the weakest orthographic achievements are also recorded in punctuation, writing of whole and split words and capitalization, so those are areas that need to be thoroughly addressed in teaching and methodology literature. The results are, on the one hand, a picture of the current status of teaching orthography and grammar knowledge of secondary school students. On the other hand, the research results can be applied in all phases of methodical practical work in teaching orthography, the upgrading the

Linguistic approach to object recognition by grasping

Energy Technology Data Exchange (ETDEWEB)

Marik, V

1982-01-01

A method for recognizing both the three-dimensional object shapes and their sizes by grasping them with an antropomorphic five-finger artificial hand is described. The hand is equipped with position sensing elements in the joints of the fingers and with a tactile transducer net on the palm surface. The linguistic method uses formal grammars and languages for the pattern description. The recognition is hierarchically arranged, every level being different from the others by a formal language which has been used. On every level the pattern description is generated and verified from the symmetrical and semantical points of view. The results of the implementation of the recognition of cones, pyramides, spheres, prisms and cylinders are presented and discussed. 8 references.

Contribution to automatic handwritten characters recognition. Application to optical moving characters recognition

International Nuclear Information System (INIS)

Gokana, Denis

1986-01-01

This paper describes a research work on computer aided vision relating to the design of a vision system which can recognize isolated handwritten characters written on a mobile support. We use a technique which consists in analyzing information contained in the contours of the polygon circumscribed to the character's shape. These contours are segmented and labelled to give a new set of features constituted by: - right and left 'profiles', - topological and algebraic unvarying properties. A new method of character's recognition induced from this representation based on a multilevel hierarchical technique is then described. In the primary level, we use a fuzzy classification with dynamic programming technique using 'profiles'. The other levels adjust the recognition by using topological and algebraic unvarying properties. Several results are presented and an accuracy of 99 pc was reached for handwritten numeral characters, thereby attesting the robustness of our algorithm. (author) [fr

Use of Poems Written by Physicians to Elicit Critical Reflection by Students in a Medical Biochemistry Course

Science.gov (United States)

Van Winkle, Lon J.; Robson, Chester; Chandar, Nalini; Green, Jacalyn M.; Viselli, Susan M.; Donovan, Kelly

2011-01-01

Purpose: Critical reflection helps to animate humanistic values needed for professional behavior in medical students. We wanted to learn whether poems written by physicians could foster such critical reflection. To do so, we determined whether the poems elicited dissonance (i.e., recognition of their own or others behavior as incongruent with…

Description and recognition of patterns in stochastic signals. [Electroencephalograms

Energy Technology Data Exchange (ETDEWEB)

Flik, T [Technische Univ. Berlin (F.R. Germany). Informatik-Forschungsgruppe Rechnerorganisation und Schaltwerke

1975-10-01

A method is shown for the description and recognition of patterns in stochastic signals such as electroencephalograms. For pattern extraction the signal is segmented at times of minimum amplitudes. The describing features consist of geometric values of the so defined patterns. The classification algorithm is based on the regression analysis, which is well known in the field of character recognition. For an economic classification a method is proposed which reduces the number of features. The quality of this pattern recognition method is demonstrated by the detection of spike wave complexes in electroencephalograms. The pattern description and recognition are provided for processing on a digital computer. (DE)

Hand based visual intent recognition algorithm for wheelchair motion

CSIR Research Space (South Africa)

Luhandjula, T

2010-05-01

Full Text Available This paper describes an algorithm for a visual human-machine interface that infers a person’s intention from the motion of the hand. Work in progress shows a proof of concept tested on static images. The context for which this solution is intended...

[Jan Fryderyk Wolfgang's autobiography (1850) in the light of hand-written and printed sources].

Science.gov (United States)

Kuźnicka, B

2001-01-01

The archival collection of the Lithuanian Academy of Sciences in Vilnius (Wilno) contains many manuscripts relating to the scientific work of Jan Fryderyk Wolfgang (1776-1859), professor of pharmacy and pharmacology of the Wilno University in the years 1807-1831, the founder and main figure in the Wilno pharmacognostic school, a botanist with substantial achievements in wide-ranging research on the flora of the Wilno region, as well as a historian of pharmacy. The most interesting of the manuscripts include Wolfgang's Autobiografia [Autobiography], written in 1850, and a list of his publications covering a total of 57 items (including some that have hitherto remained unknown), a work entitled Historya Farmakologii i Farmacyi [History of pharmacology and pharmacy], and a particularly valuable manuscript (666 + 12 sheets) entitled Farmakologiia [Pharmacology]. Worth mentioning are also two catalogues of books from Wolfgang's library: one compiled by Wolfgang himself (37 sheets) and the other by Adam Ferdynand Adamowicz. The content of the autobiography manuscript is contained on five sheets. The author of the present article analyzes the document, comparing the information contained in it with the biographies of J. F. Wolfgang that hhave been published so far (these being primarily the biography by Dominik Cezary ChodYko, published in 1863, and that by Witold W3odzimierz G3owacki of 1960). The text of the autobiography is quoted in full, together with numerous comments. The analysis of the manuscript as well as the biographical data contained in the above-mentioned biographies indicate that Wolfgang had great achievements as a scientist (in both research and organizational work), as a champion of public causes and as an educator of a generation of botanists-pharmacognostics. It also transpires from the autobiography, as well as from the research by historians, that he was a very good and trustful person, who readily granted access to his research to his collaborators

Digital collections and exhibits

CERN Document Server

Denzer, Juan

2015-01-01

Today's libraries are taking advantage of cutting-edge technologies such as flat panel displays using touch, sound, and hands-free motions to design amazing exhibits using everything from simple computer hardware to advanced technologies such as the Microsoft Kinect. Libraries of all types are striving to add new interactive experiences for their patrons through exciting digital exhibits, both online and off. Digital Collections and Exhibits takes away the mystery of designing stunning digital exhibits to spotlight library trea

Temporal hemodynamic classification of two hands tapping using functional near-infrared spectroscopy.

Science.gov (United States)

Thanh Hai, Nguyen; Cuong, Ngo Q; Dang Khoa, Truong Q; Van Toi, Vo

2013-01-01

In recent decades, a lot of achievements have been obtained in imaging and cognitive neuroscience of human brain. Brain's activities can be shown by a number of different kinds of non-invasive technologies, such as: Near-Infrared Spectroscopy (NIRS), Magnetic Resonance Imaging (MRI), and ElectroEncephaloGraphy (EEG; Wolpaw et al., 2002; Weiskopf et al., 2004; Blankertz et al., 2006). NIRS has become the convenient technology for experimental brain purposes. The change of oxygenation changes (oxy-Hb) along task period depending on location of channel on the cortex has been studied: sustained activation in the motor cortex, transient activation during the initial segments in the somatosensory cortex, and accumulating activation in the frontal lobe (Gentili et al., 2010). Oxy-Hb concentration at the aforementioned sites in the brain can also be used as a predictive factor allows prediction of subject's investigation behavior with a considerable degree of precision (Shimokawa et al., 2009). In this paper, a study of recognition algorithm will be described for recognition whether one taps the left hand (LH) or the right hand (RH). Data with noises and artifacts collected from a multi-channel system will be pre-processed using a Savitzky-Golay filter for getting more smoothly data. Characteristics of the filtered signals during LH and RH tapping process will be extracted using a polynomial regression (PR) algorithm. Coefficients of the polynomial, which correspond to Oxygen-Hemoglobin (Oxy-Hb) concentration, will be applied for the recognition models of hand tapping. Support Vector Machines (SVM) will be applied to validate the obtained coefficient data for hand tapping recognition. In addition, for the objective of comparison, Artificial Neural Networks (ANNs) was also applied to recognize hand tapping side with the same principle. Experimental results have been done many trials on three subjects to illustrate the effectiveness of the proposed method.

Temporal hemodynamic classification of two hands tapping using functional near—infrared spectroscopy

Science.gov (United States)

Thanh Hai, Nguyen; Cuong, Ngo Q.; Dang Khoa, Truong Q.; Van Toi, Vo

2013-01-01

In recent decades, a lot of achievements have been obtained in imaging and cognitive neuroscience of human brain. Brain's activities can be shown by a number of different kinds of non-invasive technologies, such as: Near-Infrared Spectroscopy (NIRS), Magnetic Resonance Imaging (MRI), and ElectroEncephaloGraphy (EEG; Wolpaw et al., 2002; Weiskopf et al., 2004; Blankertz et al., 2006). NIRS has become the convenient technology for experimental brain purposes. The change of oxygenation changes (oxy-Hb) along task period depending on location of channel on the cortex has been studied: sustained activation in the motor cortex, transient activation during the initial segments in the somatosensory cortex, and accumulating activation in the frontal lobe (Gentili et al., 2010). Oxy-Hb concentration at the aforementioned sites in the brain can also be used as a predictive factor allows prediction of subject's investigation behavior with a considerable degree of precision (Shimokawa et al., 2009). In this paper, a study of recognition algorithm will be described for recognition whether one taps the left hand (LH) or the right hand (RH). Data with noises and artifacts collected from a multi-channel system will be pre-processed using a Savitzky–Golay filter for getting more smoothly data. Characteristics of the filtered signals during LH and RH tapping process will be extracted using a polynomial regression (PR) algorithm. Coefficients of the polynomial, which correspond to Oxygen-Hemoglobin (Oxy-Hb) concentration, will be applied for the recognition models of hand tapping. Support Vector Machines (SVM) will be applied to validate the obtained coefficient data for hand tapping recognition. In addition, for the objective of comparison, Artificial Neural Networks (ANNs) was also applied to recognize hand tapping side with the same principle. Experimental results have been done many trials on three subjects to illustrate the effectiveness of the proposed method. PMID:24032008

The tropical diabetic hand syndrome: a surgical perspective.

Science.gov (United States)

Nthumba, Peter; Cavadas, Pedro C; Landin, Luis

2013-01-01

Tropical diabetic hand syndrome (TDHS) is an aggressive type of hand sepsis that results in significant morbidity and mortality among patients with diabetes in the tropics. This study set out to establish a protocol for the holistic management of TDHS to improve digit/hand salvage and function at AIC Kijabe Hospital. This prospective study examined the following demographics of patients presenting to the authors institution between October 2009 and September 2010 with TDHS: their sex, age, comorbidities, length of in-hospital stay, surgical and medical treatment, total cost of treatment, and immediate postdischarge outcomes. A total of 10 patients (3 men and 7 women) were presented with TDHS during the study period. Surgical procedures included a thorough debridement of the hand at initial presentation, followed by procedures aimed at preserving length and hand function, with digit or hand amputation when there was no possibility of salvage. Three hands were salvaged, without the need for an amputation; 2 of these, however, developed severe stiffness with resultant poor function. Fifty percent of the patients developed considerable disability; 3 of these patients had disabilities of the arm, shoulder, and hand, (DASH) scores of >90 at 6 months after treatment. TDHS appears to be more aggressive in some patients than in others; a multidisciplinary approach, with early involvement of the surgical team, and a radical surgical debridement are essential to improved outcomes. Although the goal of medical treatment (ie, glycemic control) is simple and easily achieved, surgical goals (salvage of limb or life, preservation of hand function) are more complex, costly, and difficult to achieve. Educating health care workers, diabetic patients, and their relatives on hand care is an important preventive measure. Diligence in taking antidiabetic medicine, early presentation, and appropriate care of TDHS are required for meaningful improvement in outcomes of patients with

Left hand tactile agnosia after posterior callosal lesion.

Science.gov (United States)

Balsamo, Maddalena; Trojano, Luigi; Giamundo, Arcangelo; Grossi, Dario

2008-09-01

We report a patient with a hemorrhagic lesion encroaching upon the posterior third of the corpus callosum but sparing the splenium. She showed marked difficulties in recognizing objects and shapes perceived through her left hand, while she could appreciate elementary sensorial features of items tactually presented to the same hand flawlessly. This picture, corresponding to classical descriptions of unilateral associative tactile agnosia, was associated with finger agnosia of the left hand. This very unusual case report can be interpreted as an instance of disconnection syndrome, and allows a discussion of mechanisms involved in tactile object recognition.

Digitalisering i offentlig sektor : digital ledelse som ny ledelsesdisiplin : hva hemmer og fremmer god digital ledelse?

OpenAIRE

Fjørtoft, Siw Olsen

2014-01-01

This master thesis originates from my interest in new technology and the digitization processes that we see in society today. Due to my background in the field of education, I have both learned from and experienced many of the opportunities that go with digitization. However, I have also witnessed large variations in the public sector when it comes to the implementation and practice of these processes. The government has ordered public reports and written White Papers. Counties and municipali...

DATABASES FOR RECOGNITION OF HANDWRITTEN ARABIC CHEQUES

NARCIS (Netherlands)

Alohali, Y.; Cheriet, M.; Suen, C.Y.

2004-01-01

This paper describes an effort toward building Arabic cheque databases for research in recognition of handwritten Arabic cheques. Databases of Arabic legal amounts, Arabic sub­ words, courtesy amounts, Indian digits, and Arabic cheques are provided. This paper highlights the characteristics of the

Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

Science.gov (United States)

Fang, Fuming; Shinozaki, Takahiro

2018-01-01

Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

A system of automatic speaker recognition on a minicomputer

International Nuclear Information System (INIS)

El Chafei, Cherif

1978-01-01

This study describes a system of automatic speaker recognition using the pitch of the voice. The pre-treatment consists in the extraction of the speakers' discriminating characteristics taken from the pitch. The programme of recognition gives, firstly, a preselection and then calculates the distance between the speaker's characteristics to be recognized and those of the speakers already recorded. An experience of recognition has been realized. It has been undertaken with 15 speakers and included 566 tests spread over an intermittent period of four months. The discriminating characteristics used offer several interesting qualities. The algorithms concerning the measure of the characteristics on one hand, the speakers' classification on the other hand, are simple. The results obtained in real time with a minicomputer are satisfactory. Furthermore they probably could be improved if we considered other speaker's discriminating characteristics but this was unfortunately not in our possibilities. (author) [fr

Robust 3D Face Recognition in the Presence of Realistic Occlusions

NARCIS (Netherlands)

Alyuz, Nese; Gökberk, B.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Akarun, Lale

2012-01-01

Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems

Assessing readability formula differences with written health information materials: application, results, and recommendations.

Science.gov (United States)

Wang, Lih-Wern; Miller, Michael J; Schmitt, Michael R; Wen, Frances K

2013-01-01

Readability formulas are often used to guide the development and evaluation of literacy-sensitive written health information. However, readability formula results may vary considerably as a result of differences in software processing algorithms and how each formula is applied. These variations complicate interpretations of reading grade level estimates, particularly without a uniform guideline for applying and interpreting readability formulas. This research sought to (1) identify commonly used readability formulas reported in the health care literature, (2) demonstrate the use of the most commonly used readability formulas on written health information, (3) compare and contrast the differences when applying common readability formulas to identical selections of written health information, and (4) provide recommendations for choosing an appropriate readability formula for written health-related materials to optimize their use. A literature search was conducted to identify the most commonly used readability formulas in health care literature. Each of the identified formulas was subsequently applied to word samples from 15 unique examples of written health information about the topic of depression and its treatment. Readability estimates from common readability formulas were compared based on text sample size, selection, formatting, software type, and/or hand calculations. Recommendations for their use were provided. The Flesch-Kincaid formula was most commonly used (57.42%). Readability formulas demonstrated variability up to 5 reading grade levels on the same text. The Simple Measure of Gobbledygook (SMOG) readability formula performed most consistently. Depending on the text sample size, selection, formatting, software, and/or hand calculations, the individual readability formula estimated up to 6 reading grade levels of variability. The SMOG formula appears best suited for health care applications because of its consistency of results, higher level of expected

Unconstrained and contactless hand geometry biometrics.

Science.gov (United States)

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

Unconstrained and Contactless Hand Geometry Biometrics

Directory of Open Access Journals (Sweden)

Carmen Sánchez-Ávila

2011-10-01

Full Text Available This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM and k-Nearest Neighbour (k-NN. Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

Evaluating EMG Feature and Classifier Selection for Application to Partial-Hand Prosthesis Control

Directory of Open Access Journals (Sweden)

Adenike A. Adewuyi

2016-10-01

Full Text Available Pattern recognition-based myoelectric control of upper limb prostheses has the potential to restore control of multiple degrees of freedom. Though this control method has been extensively studied in individuals with higher-level amputations, few studies have investigated its effectiveness for individuals with partial-hand amputations. Most partial-hand amputees retain a functional wrist and the ability of pattern recognition-based methods to correctly classify hand motions from different wrist positions is not well studied. In this study, focusing on partial-hand amputees, we evaluate (1 the performance of non-linear and linear pattern recognition algorithms and (2 the performance of optimal EMG feature subsets for classification of four hand motion classes in different wrist positions for 16 non-amputees and 4 amputees. Our results show that linear discriminant analysis and linear and non-linear artificial neural networks perform significantly better than the quadratic discriminant analysis for both non-amputees and partial-hand amputees. For amputees, including information from multiple wrist positions significantly decreased error (p<0.001 but no further significant decrease in error occurred when more than 4, 2, or 3 positions were included for the extrinsic (p=0.07, intrinsic (p=0.06, or combined extrinsic and intrinsic muscle EMG (p=0.08, respectively. Finally, we found that a feature set determined by selecting optimal features from each channel outperformed the commonly used time domain (p<0.001 and time domain/autoregressive feature sets (p<0.01. This method can be used as a screening filter to select the features from each channel that provide the best classification of hand postures across different wrist positions.

Social communication and emotion difficulties and second to fourth digit ratio in a large community-based sample.

Science.gov (United States)

Barona, Manuela; Kothari, Radha; Skuse, David; Micali, Nadia

2015-01-01

Recent research investigating the extreme male brain theory of autism spectrum disorders (ASD) has drawn attention to the possibility that autistic type social difficulties may be associated with high prenatal testosterone exposure. This study aims to investigate the association between social communication and emotion recognition difficulties and second to fourth digit ratio (2D:4D) and circulating maternal testosterone during pregnancy in a large community-based cohort: the Avon Longitudinal Study of Parents and Children (ALSPAC). A secondary aim is to investigate possible gender differences in the associations. Data on social communication (Social and Communication Disorders Checklist, N = 7165), emotion recognition (emotional triangles, N = 5844 and diagnostics analysis of non-verbal accuracy, N = 7488) and 2D:4D (second to fourth digit ratio, N = 7159) were collected in childhood and early adolescence from questionnaires and face-to-face assessments. Complete data was available on 3515 children. Maternal circulating testosterone during pregnancy was available in a subsample of 89 children. Males had lower 2D:4D ratios than females [t (3513) = -9.775, p emotion recognition, and the lowest 10 % of 2D:4D ratios. A significant association was found between maternal circulating testosterone and left hand 2D:4D [OR = 1.65, 95 % CI 1.1-2.4, p < 0.01]. Previous findings on the association between 2D:4D and social communication difficulties were not confirmed. A novel association between an extreme measure of 2D:4D in males suggests threshold effects and warrants replication.

Are Adult Educators and Learners "Digital Immigrants"? Examining the Evidence and Impacts for Continuing Education

Science.gov (United States)

Smith, Erika

2013-01-01

Over the past decade, Prensky's distinctions between "digital immigrants" and "digital natives" have been oft-referenced. Much has been written about digital native students as a part of the Net generation or as Millennials. However, little work fully considers the impact of digital immigrant discourse within the fields of…

Digital airborne camera introduction and technology

CERN Document Server

Sandau, Rainer

2014-01-01

The last decade has seen great innovations on the airborne camera. This book is the first ever written on the topic and describes all components of a digital airborne camera ranging from the object to be imaged to the mass memory device.

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter.

Science.gov (United States)

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-17

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor's stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

Online, game-based education for melanoma recognition: A pilot study.

Science.gov (United States)

Maganty, Nishita; Ilyas, Muneeb; Zhang, Nan; Sharma, Amit

2018-04-01

To evaluate the effectiveness of a game-based learning (GBL) intervention, Tapamole, in improving recognition of the features of melanoma (MM) compared to a written education intervention. Tapamole, an online education intervention, was developed using GBL. Participants were voluntarily recruited from the Dermatology waiting room and randomized to three groups: game, pamphlet, and no intervention. Participants completed a pre-intervention survey, post-intervention survey, and test on MM recognition. Clustered binary data equations were used to calculate sensitivity, specificity, and accuracy for each group and GEE model with log link was used to compare measures between groups. Sixty participants were recruited. The sensitivity for MM recognition in the game group was 100% compared to 95% for the pamphlet group. The specificity (40.8% vs 53.3%) and accuracy (60.6% vs 67.2%) of the game and pamphlet groups were similar. Participants in the game group reported higher enjoyment than those in the pamphlet group. GBL was as effective as the written intervention in identifying features of MM. With increasing use of the Internet for health information, it is critical to have effective online education interventions. GBL education tools are effective, enjoyable, and should be used to improve MM patient education. Copyright © 2017 Elsevier B.V. All rights reserved.

Robust Pedestrian Tracking and Recognition from FLIR Video: A Unified Approach via Sparse Coding

Directory of Open Access Journals (Sweden)

Xin Li

2014-06-01

Full Text Available Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the analysis of forward-looking infrared (FLIR video to support nighttime machine vision systems. A key technical contribution of this work is to unify existing sparse coding-based approaches toward tracking and recognition under the same framework, so that they can benefit from each other in a closed-loop. On the one hand, tracking the same object through temporal frames allows us to achieve improved recognition performance through dynamical updating of template/dictionary and combining multiple recognition results; on the other hand, the recognition of individual objects facilitates the tracking of multiple objects (i.e., walking pedestrians, especially in the presence of occlusion within a crowded environment. We report experimental results on both the CASIAPedestrian Database and our own collected FLIR video database to demonstrate the effectiveness of the proposed joint tracking-and-recognition approach.

Applications of pattern recognition theory in diagnostics of nuclear power plants

International Nuclear Information System (INIS)

Cech, J.

1982-01-01

The questions are discussed of the application of the theory of pattern recognition in the diagnostics of nuclear power plants. For the future use of recognition systems in the diagnostics of nuclear power plants it is obvious that like with other complex systems, optimal models will have to be used which will organize the optimal recognition algorithm. The conclusion is presented that for the needs of nuclear power plants special systems will be more suitable for pattern recognition than digital computers which are flexible and adaptible but have a lower decision rate, an insufficient working memory, complicated programs, etc. (Z.M.)

The art of digital video

CERN Document Server

Watkinson, John

2013-01-01

The industry ""bible"" is back and it's better than ever. The Art of Digital Video has served as the ultimate reference guide for those working with digital video for generations. Now this classic has been revised and re-written by international consultant and industry leader John Watkinson to include important technical updates on this ever-evolving topic. The format has also been improved to include optional sections that provide additional information that you can choose to skip or investigate further, depending on your interests and comfort level with the s

Page Recognition: Quantum Leap In Recognition Technology

Science.gov (United States)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

Digital signal processing an experimental approach

CERN Document Server

Engelberg, Shlomo

2008-01-01

Digital Signal Processing is a mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction. Divided into three parts, the book covers various aspects of the digital signal processing (DSP) ""problem."" It begins with the analysis of discrete-time signals and explains sampling and the use of the discrete and fast Fourier transforms. The second part of the book???covering digital to analog and analog to digital conversion???provides a practical interlude in the mathematical content before Part II

3D Digital Modelling

DEFF Research Database (Denmark)

Hundebøl, Jesper

wave of new building information modelling tools demands further investigation, not least because of industry representatives' somewhat coarse parlance: Now the word is spreading -3D digital modelling is nothing less than a revolution, a shift of paradigm, a new alphabet... Research qeustions. Based...... on empirical probes (interviews, observations, written inscriptions) within the Danish construction industry this paper explores the organizational and managerial dynamics of 3D Digital Modelling. The paper intends to - Illustrate how the network of (non-)human actors engaged in the promotion (and arrest) of 3...... important to appreciate the analysis. Before turning to the presentation of preliminary findings and a discussion of 3D digital modelling, it begins, however, with an outline of industry specific ICT strategic issues. Paper type. Multi-site field study...

Digital telephony and network integration

CERN Document Server

Keiser, Bernhard E

1995-01-01

What is "digital telephony"? To the authors, the term digital telephony denotes the technology used to provide a completely digital telecommunication system from end-to-end. This implies the use of digital technology from one end instru­ ment through transmission facilities and switching centers to another end instru­ ment. Digital telephony has become possible only because of the recent and on­ going surge of semiconductor developments, allowing microminiaturization and high reliability along with reduced costs. This book deals with both the future and the present. Thus, the first chapter is entitled, "A Network in Transition." As baselines, Chapters 2 and 11 provide the reader with the present status of teler-hone technology in terms of voice digiti­ zation as well as switching principles. The book is an outgrowth of the authors' consulting and teaching experience in the field since the early 1980s. The book has been written to provide both the engineering student and the practicing engineer a working k...

Digital-forensics based pattern recognition for discovering identities in electronic evidence

NARCIS (Netherlands)

Henseler, Hans; Hofsté, Jop; van Keulen, Maurice

With the pervasiveness of computers and mobile devices, digital forensics becomes more important in law enforcement. Detectives increasingly depend on the scarce support of digital specialists which impedes efficiency of criminal investigations. This paper proposes and algorithm to extract, merge

Batch metadata assignment to archival photograph collections using facial recognition software

Directory of Open Access Journals (Sweden)

Kyle Banerjee

2013-07-01

Full Text Available Useful metadata is essential to giving individual meaning and value within the context of a greater image collection as well as making them more discoverable. However, often little information is available about the photos themselves, so adding consistent metadata to large collections of digital and digitized photographs is a time consuming process requiring highly experienced staff. By using facial recognition software, staff can identify individuals more quickly and reliably. Knowledge of individuals in photos helps staff determine when and where photos are taken and also improves understanding of the subject matter. This article demonstrates simple techniques for using facial recognition software and command line tools to assign, modify, and read metadata for large archival photograph collections.

Real object recognition using moment invariants

Indian Academy of Sciences (India)

are taken from different angles of view are the main features leading us to our objective. ... Two-dimensional moments of a digitally sampled M × M image that has gray function f (x, y), (x, .... in this paper. Information about the original colours of the objects is not used. .... multi-dimensional changes and recognition. Table 1.

Circuit For Control Of Electromechanical Prosthetic Hand

Science.gov (United States)

Bozeman, Richard J., Jr.

1995-01-01

Proposed circuit for control of electromechanical prosthetic hand derives electrical control signals from shoulder movements. Updated, electronic version of prosthesis, that includes two hooklike fingers actuated via cables from shoulder harness. Circuit built around favored shoulder harness, provides more dexterous movement, without incurring complexity of computer-controlled "bionic" or hydraulically actuated devices. Additional harness and potentiometer connected to similar control circuit mounted on other shoulder. Used to control stepping motor rotating hand about prosthetic wrist to one of number of angles consistent with number of digital outputs. Finger-control signals developed by circuit connected to first shoulder harness transmitted to prosthetic hand via sliprings at prosthetic wrist joint.

New ICT in the Peruvian Andes: Theoretical Foundation and Bibliographical Balance

Directory of Open Access Journals (Sweden)

Mario Sánchez-Dávila

2016-04-01

Full Text Available On the one hand, this paper explains the theoretical foundations on which this proposal for digital anthropology in the Peruvian Andes is based (on the origins of digital anthropology, discussions on oral and written technology, and theories of digital technology as social practice. And, on the other hand, this paper presents a bibliographical balance of the studies on the new ICT in the Peruvian Andes (on identity expression, productive development and formal education in the Andean world.

Hands on with ASP.NET MVC covering MVC 6

CERN Document Server

Sahay, Rahul

2014-01-01

MVC (Model-View-Controller) is the popular Microsoft technology which enables you to build dynamic, data-driven, mobile websites, TDD site. Hands-On with ASP.NET MVC is not only written for those who are going to have affair with MVC for the 1st time, rather it is written in such a way that even experienced professional will love reading this book. This book covers all the tiny steps on using MVC at its best. With complete practical tutorials to illustrate the concepts, you will step by step build one End to End application which covers below mentioned techniques - Controllers, Views, Models,

Gamma spectra pictures using a digital plotter. Program MONO; Representacion de Espectros directos mediante un trazado digital. Prograa MONO

Energy Technology Data Exchange (ETDEWEB)

Los Arcos, J M

1978-07-01

The program MONO has been written for a CALCOMP-936 digital plotter operating off- -line with a UMI VAC 1106 computer, to obtain graphic representations of single gamma spectra stored on magnetic tape. It allows to plot the whole spectrum or only a part, as well as to draw a given spectrum on the same or different picture than the previous one. Ten representation scales are available and at up nine comment lines can be written in a graphic. (Author) 4 refs.

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones.

Science.gov (United States)

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-08-20

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user's daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

Directory of Open Access Journals (Sweden)

Seongwan Kim

2017-01-01

Full Text Available The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor, usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

Study on recognition algorithm for paper currency numbers based on neural network

Science.gov (United States)

Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

2008-12-01

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

An introduction to digital signal processing

CERN Document Server

Karl, John H

1989-01-01

An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume.This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how si

Concept of digital nomad: fundamental risks of digital economy development

Directory of Open Access Journals (Sweden)

Elena Lyudvigovna Iakovleva

2017-12-01

Full Text Available Objective to identify the key risks of the digital economy development. Methods abstractlogical and dialectical methods. Results a modern individual cannot imagine their life without digital devices which facilitate their functioning and enable them to be included into the virtual space. The role of digital economy in the changes in all spheres of human life is analyzed in the article. With the growing role of the digital economy the approaches to business models formation are changing as well as the role of digital assets. This also leads to the transformation of human behavior the new risks of the digital economy accelerated development. In this regard the article characterizes an individual as a digital nomad defines the features of their behavior in the socioeconomic environment and highlights the main risks that arise in connection with digital nomadism. It is determined that one of the most characteristic features of a modern person is hypermobility eparkourism. In addition the paper describes the problems of anonymity in virtual space and the emergence of systems that provide anonymity of the individual as well as the risks arising in connection with that. The problem of lack of culture and value systems in the virtual space is highlighted as well the problem of developing contradictions in information leading to the alienation of people from the real world. It was determined that the informatization of economy on the one hand leads to faster business processes reduced transaction costs saving of variable costs due to robotization of production and on the other hand it leads to the transformation of competition growth of tension in society in connection with the job cuts. Another problem is personal and national security associated with the development of social networks the developers of which are other countries and also with the emergence of mechanisms of influence on mass consciousness. Scientific novelty it is shown that the risks

Analogies Between Digital Radio and Chemical Orthogonality as a Method for Enhanced Analysis of Molecular Recognition Events

Directory of Open Access Journals (Sweden)

Sang-Hun Lee

2008-02-01

Full Text Available Acoustic wave biosensors are a real-time, label-free biosensor technology, which have been exploited for the detection of proteins and cells. One of the conventional biosensor approaches involves the immobilization of a monolayer of antibodies onto the surface of the acoustic wave device for the detection of a specific analyte. The method described within includes at least two immobilizations of two different antibodies onto the surfaces of two separate acoustic wave devices for the detection of several analogous analytes. The chemical specificity of the molecular recognition event is achieved by virtue of the extremely high (nM to pM binding affinity between the antibody and its antigen. In a standard ELISA (Enzyme-Linked ImmunoSorbent Assay test, there are multiple steps and the end result is a measure of what is bound so tightly that it does not wash away easily. The fact that this “gold standard” is very much not real time, masks the dance that is the molecular recognition event. X-Ray Crystallographer, Ian Wilson, demonstrated more than a decade ago that antibodies undergo conformational change during a binding event[1, 2]. Further, it is known in the arena of immunochemistry that some antibodies exhibit significant cross-reactivity and this is widely termed antibody promiscuity. A third piece of the puzzle that we will exploit in our system of acoustic wave biosensors is the notion of chemical orthogonality. These three biochemical constructs, the dance, antibody promiscuity and chemical orthogonality will be combined in this paper with the notions of Int. J. Mol. Sci. 2008, 9 155 in-phase (I and quadrature (Q signals from digital radio to manifest an approach to molecular recognition that allows a level of discrimination and analysis unobtainable without the aggregate. As an example we present experimental data on the detection of TNT, RDX, C4, ammonium nitrate and musk oil from a system of antibody-coated acoustic

Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient.

Science.gov (United States)

Lu, Zhiyuan; Tong, Kai-Yu; Shin, Henry; Li, Sheng; Zhou, Ping

2017-01-01

A hand exoskeleton driven by myoelectric pattern recognition was designed for stroke rehabilitation. It detects and recognizes the user's motion intent based on electromyography (EMG) signals, and then helps the user to accomplish hand motions in real time. The hand exoskeleton can perform six kinds of motions, including the whole hand closing/opening, tripod pinch/opening, and the "gun" sign/opening. A 52-year-old woman, 8 months after stroke, made 20× 2-h visits over 10 weeks to participate in robot-assisted hand training. Though she was unable to move her fingers on her right hand before the training, EMG activities could be detected on her right forearm. In each visit, she took 4× 10-min robot-assisted training sessions, in which she repeated the aforementioned six motion patterns assisted by our intent-driven hand exoskeleton. After the training, her grip force increased from 1.5 to 2.7 kg, her pinch force increased from 1.5 to 2.5 kg, her score of Box and Block test increased from 3 to 7, her score of Fugl-Meyer (Part C) increased from 0 to 7, and her hand function increased from Stage 1 to Stage 2 in Chedoke-McMaster assessment. The results demonstrate the feasibility of robot-assisted training driven by myoelectric pattern recognition after stroke.

SIFT Based Vein Recognition Models: Analysis and Improvement

Directory of Open Access Journals (Sweden)

Guoqing Wang

2017-01-01

Full Text Available Scale-Invariant Feature Transform (SIFT is being investigated more and more to realize a less-constrained hand vein recognition system. Contrast enhancement (CE, compensating for deficient dynamic range aspects, is a must for SIFT based framework to improve the performance. However, evidence of negative influence on SIFT matching brought by CE is analysed by our experiments. We bring evidence that the number of extracted keypoints resulting by gradient based detectors increases greatly with different CE methods, while on the other hand the matching result of extracted invariant descriptors is negatively influenced in terms of Precision-Recall (PR and Equal Error Rate (EER. Rigorous experiments with state-of-the-art and other CE adopted in published SIFT based hand vein recognition system demonstrate the influence. What is more, an improved SIFT model by importing the kernel of RootSIFT and Mirror Match Strategy into a unified framework is proposed to make use of the positive keypoints change and make up for the negative influence brought by CE.

The Hand: Shall We Ever Understand How it Works?

Science.gov (United States)

Latash, Mark L

2015-04-01

The target article presents a review of the neural control of the human hand. The review emphasizes the physical approach to motor control. It focuses on such concepts as equilibrium-point control, control with referent body configurations, uncontrolled manifold hypothesis, principle of abundance, hierarchical control, multidigit synergies, and anticipatory synergy adjustments. Changes in aspects of the hand neural control with age and neurological disorder are discussed. The target article is followed by six commentaries written by Alexander Aruin, Kelly Cole, Monica Perez, Robert Sainburg, Marco Sanello, and Wei Zhang.

Compact Acoustic Models for Embedded Speech Recognition

Directory of Open Access Journals (Sweden)

Lévy Christophe

2009-01-01

Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

Second to fourth digit ratio, sex differences and antropometric measuments: their relationship in children.

Science.gov (United States)

Uludag, Aysegul; Tekin, Murat; Ertekin, Yusuf H; Şahin, Erkan M; Cevizci, Sibel; Cibik, Birol; Oguz, Sevilay; Erbag, Oznur

2017-04-01

The aim of this study was to determine the effect of socio-demographic factors and anthropometric measurements on 2/4 digit ratio in the school aged children. This cross-sectional study was completed in primary and secondary schools in the city center of Canakkale, Turkey. The students were seated at a table by the responsible doctor, and were asked to extend the palm of the right and left hand in the schools. Using a Vernier Caliper the 2/4 fingers were measured from the palm twice, and the results were noted together with socio-demographic information. Weight, length, waist and hip measurements were taken while students were behind a folding screen. A total of 1860 students from 5-14 years were included in the study. The right hand 2/4 digit ratio was 0.9765±0.035 and the left hand ratio was 0.9716±0.036 for girls. For the boys the ratios were 0.9688±0.035 for right hand and 0.9653±0.033 for left hand. The digit ratios of girls were significantly higher than boys and the right hand ratio was even greater. The 2/4 digit measurements of both hands of students were positively correlated with each other. In regression model left hand 2/4 ratio is dependent hip circumference, monthly income and gender as adjusted r2 0.051. The right hand 2/4 ratio was dependent gender, monthly income, hip circumference and birthweight as adjusted r2 0.041. The 2/4 digit ratio of school-aged in Turkish children differed based on gender. Digit ratios depend on the hip circumference, gender (girls have higher ratio), birthweight, gestation week and monthly income. Further research, especially the effect of monthly income, is needed.

A STUDY ON OPTICAL CHARACTER RECOGNITION TECHNIQUES

OpenAIRE

Narendra Sahu; Manoj Sonkusare

2018-01-01

Optical Character Recognition (OCR) is the process which enables a system to without human intervention identifies the scripts or alphabets written into the users’ verbal communication. Optical Character identification has grown to be individual of the mainly flourishing applications of knowledge in the field of pattern detection and artificial intelligence. In our survey we study on the various OCR techniques. In this paper we resolve and examine the hypothetical and numerical models of Opti...

Construction of Graduation Certificate Issuing System Based on Digital Signature Technique

Directory of Open Access Journals (Sweden)

Mohammed Issam Younis

2015-06-01

Full Text Available With the development of computer architecture and its technologies in recent years, applications like e-commerce, e-government, e-governance and e-finance are widely used, and they act as active research areas. In addition, in order to increase the quality and quantity of the ordinary everyday transactions, it is desired to migrate from the paper-based environment to a digital-based computerized environment. Such migration increases efficiency, saves time, eliminates paperwork, increases safety and reduces the cost in an organization. Digital signatures are playing an essential role in many electronic and automatic based systems and facilitate this migration. The digital signatures are used to provide many services and solutions that would not have been possible by the conventional hand-written signature. In the educational environment, the process of issuing the graduation certificates can no longer be restricted to the traditional methods. Hence, a computerized system for issuing certificates of graduation in an electronic form is needed and desired. This paper proposes a Graduation Certificates Issuing System (GCIS based on digital signature technology. In doing so, this research highlights the state-of-the-art and the art-of-the-practice for some existing digital signature-based systems in the literatures. In addition, eight intertwined elected services are identified, namely: message authentication, entity authentication, integrity, non-repudiation, time stamping, distinguished signing authorities, delegating signing capability and supporting workflow systems. Moreover, this research examines nine existing systems, showing their merits and demerits in terms of these elected services. Furthermore, the research describes the architectural design using the Unified Modeling Language (UML and provides the concrete implementation of the proposed GCIS. The GCIS is implemented using Visual Basic.Net programming language and SQL Server database

Myelopathy hand in cervical radiculopathy

International Nuclear Information System (INIS)

Hosono, Noboru; Mukai, Yoshihiro; Takenaka, Shota; Fuji, Takeshi; Sakaura, Hironobu; Miwa, Toshitada; Makino, Takahiro

2010-01-01

The so-called 'myelopathy hand', or characteristic finger paralysis, often recognized in cervical compression myelopathy, has been considered a unique manifestation of cervical myelopathy. We used our original grip and release test, a 15-second test in which finger motion is captured with a digital camera, to investigate whether cervical radiculopathy has the same characteristics as myelopathy hand. Thirty patients with pure radiculopathy, id est (i.e.), who had radiating arm pain and evidence of corresponding nerve root impingement on X-ray images or MRI scans, but did not have spinal cord compression, served as the subjects. In contrast to other radiculopathies, C7 radiculopathy was manifested by a significant reduction in the number of finger motion cycles on the affected side in comparison with the unaffected side, the same as in myelopathy hand. Uncoordinated finger motion was significantly more frequent on the affected side in C6 radiculopathy than on the unaffected side. These findings contradict the conventional notion that myelopathy hand is a unique manifestation of cervical myelopathy, but some radiculopathies manifested the same kinds of finger paralysis observed in myelopathy hand. (author)

THE RECOGNITION OF SPOKEN MONO-MORPHEMIC COMPOUNDS IN CHINESE

Directory of Open Access Journals (Sweden)

Yu-da Lai

2012-12-01

Full Text Available This paper explores the auditory lexical access of mono-morphemic compounds in Chinese as a way of understanding the role of orthography in the recognition of spoken words. In traditional Chinese linguistics, a compound is a word written with two or more characters whether or not they are morphemic. A monomorphemic compound may either be a binding word, written with characters that only appear in this one word, or a non-binding word, written with characters that are chosen for their pronunciation but that also appear in other words. Our goal was to determine if this purely orthographic difference affects auditory lexical access by conducting a series of four experiments with materials matched by whole-word frequency, syllable frequency, cross-syllable predictability, cohort size, and acoustic duration, but differing in binding. An auditory lexical decision task (LDT found an orthographic effect: binding words were recognized more quickly than non-binding words. However, this effect disappeared in an auditory repetition and in a visual LDT with the same materials, implying that the orthographic effect during auditory lexical access was localized to the decision component and involved the influence of cross-character predictability without the activation of orthographic representations. This claim was further confirmed by overall faster recognition of spoken binding words in a cross-modal LDT with different types of visual interference. The theoretical and practical consequences of these findings are discussed.

Handwriting or Typewriting? The Influence of Pen- or Keyboard-Based Writing Training on Reading and Writing Performance in Preschool Children.

Science.gov (United States)

Kiefer, Markus; Schuler, Stefanie; Mayer, Carmen; Trumpp, Natalie M; Hille, Katrin; Sachse, Steffi

2015-01-01

Digital writing devices associated with the use of computers, tablet PCs, or mobile phones are increasingly replacing writing by hand. It is, however, controversially discussed how writing modes influence reading and writing performance in children at the start of literacy. On the one hand, the easiness of typing on digital devices may accelerate reading and writing in young children, who have less developed sensory-motor skills. On the other hand, the meaningful coupling between action and perception during handwriting, which establishes sensory-motor memory traces, could facilitate written language acquisition. In order to decide between these theoretical alternatives, for the present study, we developed an intense training program for preschool children attending the German kindergarten with 16 training sessions. Using closely matched letter learning games, eight letters of the German alphabet were trained either by handwriting with a pen on a sheet of paper or by typing on a computer keyboard. Letter recognition, naming, and writing performance as well as word reading and writing performance were assessed. Results did not indicate a superiority of typing training over handwriting training in any of these tasks. In contrast, handwriting training was superior to typing training in word writing, and, as a tendency, in word reading. The results of our study, therefore, support theories of action-perception coupling assuming a facilitatory influence of sensory-motor representations established during handwriting on reading and writing.

Occupational hand eczema and/or contact urticaria

DEFF Research Database (Denmark)

Carøe, Tanja K; Ebbehøj, Niels E; Bonde, Jens P

2018-01-01

BACKGROUND: Occupational hand eczema and/or contact urticaria may have social consequences such as change of profession or not remaining in the workforce. OBJECTIVES: To identify factors associated with job change in a cohort of participants with recognised occupational hand eczema....../contact urticaria METHODS: A registry-based study including 2703 employees with recognised occupational hand eczema/contact urticaria in Denmark in 2010/2011. Four to five years later the participants received a follow-up questionnaire, comprising questions on current job situation (response rate 58.0%). RESULTS...... to specific professions, cleaning personnel changed profession significantly more often than other workers [71.4% (OR = 2.26)], health care workers significantly less often than other workers [34.0% (OR = 0.36)]. CONCLUSION: Job change occurs frequently during the first years after recognition of occupational...

Digital Materia

OpenAIRE

Lindgren, Marcus; Richey, Emma

2014-01-01

Med tankar från pedagogen Montessori och filosoferna Platon och Baudrillard har detta arbete behandlat frågor om datorn och dess betydelse för en grafiker. Frågeställningen formulerades efter hand och lydde tillslut: ”Hur kan materia te sig i digital form?” Forskningen resulterade i en hypotes för hur digital materia skulle födas i datorn: genom att blanda två uppsättningar av data, såsom två genuppsättningar tillsammans skapar en ny organism. Under produktionen utvecklades därmed en metod fö...

Development and validation of a smartphone-based digits-in-noise hearing test in South African English.

Science.gov (United States)

Potgieter, Jenni-Marí; Swanepoel, De Wet; Myburgh, Hermanus Carel; Hopper, Thomas Christopher; Smits, Cas

2015-07-01

The objective of this study was to develop and validate a smartphone-based digits-in-noise hearing test for South African English. Single digits (0-9) were recorded and spoken by a first language English female speaker. Level corrections were applied to create a set of homogeneous digits with steep speech recognition functions. A smartphone application was created to utilize 120 digit-triplets in noise as test material. An adaptive test procedure determined the speech reception threshold (SRT). Experiments were performed to determine headphones effects on the SRT and to establish normative data. Participants consisted of 40 normal-hearing subjects with thresholds ≤15 dB across the frequency spectrum (250-8000 Hz) and 186 subjects with normal-hearing in both ears, or normal-hearing in the better ear. The results show steep speech recognition functions with a slope of 20%/dB for digit-triplets presented in noise using the smartphone application. The results of five headphone types indicate that the smartphone-based hearing test is reliable and can be conducted using standard Android smartphone headphones or clinical headphones. A digits-in-noise hearing test was developed and validated for South Africa. The mean SRT and speech recognition functions correspond to previous developed telephone-based digits-in-noise tests.

Haar-like Rectangular Features for Biometric Recognition

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam

2013-01-01

Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...

Is handwriting constrained by phonology? Evidence from Stroop tasks with written responses and Chinese characters

Directory of Open Access Journals (Sweden)

Markus eDamian

2013-10-01

Full Text Available To what extent is handwritten word production based on phonological codes? A few studies conducted in Western languages have recently provided evidence showing that phonology contributes to the retrieval of graphemic properties in written output tasks. Less is known about how orthographic production works in languages with non-alphabetic scripts such as written Chinese. We report a Stroop study in which Chinese participants wrote the colour of characters on a digital graphic tablet; characters were either neutral, or homophonic to the target (congruent, or homophonic to an alternative (incongruent. Facilitation was found from congruent homophonic distractors, but only when the homophone shared the same tone with the target. This finding suggests a contribution of phonology to written word production. A second experiment served as a control experiment to exclude the possibility that the effect in Experiment 1 had an exclusively semantic locus. Overall, the findings offer new insight into the relative contribution of phonology to handwriting, particularly in non-Western languages.

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones

Directory of Open Access Journals (Sweden)

Hansong Guo

2016-08-01

Full Text Available As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.

On the feasibility of interoperable schemes in hand biometrics.

Science.gov (United States)

Morales, Aythami; González, Ester; Ferrer, Miguel A

2012-01-01

Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

On the Feasibility of Interoperable Schemes in Hand Biometrics

Science.gov (United States)

Morales, Aythami; González, Ester; Ferrer, Miguel A.

2012-01-01

Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors. PMID:22438714

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones †

Science.gov (United States)

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-01-01

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy. PMID:27556461

Interactions between Digital Geometry and Combinatorics on Words

Directory of Open Access Journals (Sweden)

Srečko Brlek

2011-08-01

Full Text Available We review some recent results in digital geometry obtained by using a combinatorics on words approach to discrete geometry. Motivated on the one hand by the well-known theory of Sturmian words which model conveniently discrete lines in the plane, and on the other hand by the development of digital geometry, this study reveals strong links between the two fields. Discrete figures are identified with polyominoes encoded by words. The combinatorial tools lead to elegant descriptions of geometrical features and efficient algorithms. Among these, radix-trees are useful for efficiently detecting path intersection, Lyndon and Christoffel words appear as the main tools for describing digital convexity; equations on words allow to better understand tilings by translations.

Left hand polydactyly: a case report.

Science.gov (United States)

Mumoli, Nicola; Gandini, Daniele; Wamala, Edris Kalanzi; Cei, Marco

2008-11-24

Polydactyly is a congenital anomaly with a wide range of manifestations that occurs in many forms, ranging from varying degrees of mere splitting to completely duplicated thumb. When duplication occurs alone, it is usually unilateral and sporadic. In this case report we describe an otherwise healthy 19-year-old woman of Tibetan heritage with isolated left hand preaxial polydactyly. She experienced working related difficulties in her daily yak's milking. She subsequently underwent surgical correction, and the over number thumb was removed with associated meticulous skeletal and soft tissue reconstruction. Polydactyly is the most common congenital digital anomaly of the hand and foot. It can occur in isolation or as part of a syndrome. Surgery is necessary to create a single, functioning thumb and is indicated to improve cosmesis. Skin, nail, bone, ligament, and musculoskeletal elements must be combined to reconstruct an optimal digit. In this case (Tibetan society is almost exclusively a sheep-breeding one) surgery was necessary to leave a single, functioning thumb for her work as yak milkmaid.

Connected digit speech recognition system for Malayalam language

Indian Academy of Sciences (India)

tance, spoken database querying for novice users, 'hands busy' applications in medical ... ASR is a branch of Artificial Intelligence (AI) and is related with number of ... Artificial neural networks (ANN) (Behrman et al 2000) and Support Vector ...

Investigating the Impact of Possession-Way of a Smartphone on Action Recognition

Directory of Open Access Journals (Sweden)

Zae Myung Kim

2016-06-01

Full Text Available For the past few decades, action recognition has been attracting many researchers due to its wide use in a variety of applications. Especially with the increasing number of smartphone users, many studies have been conducted using sensors within a smartphone. However, a lot of these studies assume that the users carry the device in specific ways such as by hand, in a pocket, in a bag, etc. This paper investigates the impact of providing an action recognition system with the information of the possession-way of a smartphone, and vice versa. The experimental dataset consists of five possession-ways (hand, backpack, upper-pocket, lower-pocket, and shoulder-bag and two actions (walking and running gathered by seven users separately. Various machine learning models including recurrent neural network architectures are employed to explore the relationship between the action recognition and the possession-way recognition. The experimental results show that the assumption of possession-ways of smartphones do affect the performance of action recognition, and vice versa. The results also reveal that a good performance is achieved when both actions and possession-ways are recognized simultaneously.

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors.

Science.gov (United States)

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-09-15

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no

Hands-free administration of subjective workload scales: acceptability in a surgical training environment.

Science.gov (United States)

Carswell, C Melody; Lio, Cindy H; Grant, Russell; Klein, Martina I; Clarke, Duncan; Seales, W Brent; Strup, Stephen

2010-12-01

Subjective workload measures are usually administered in a visual-manual format, either electronically or by paper and pencil. However, vocal responses to spoken queries may sometimes be preferable, for example when experimental manipulations require continuous manual responding or when participants have certain sensory/motor impairments. In the present study, we evaluated the acceptability of the hands-free administration of two subjective workload questionnaires - the NASA Task Load Index (NASA-TLX) and the Multiple Resources Questionnaire (MRQ) - in a surgical training environment where manual responding is often constrained. Sixty-four undergraduates performed fifteen 90-s trials of laparoscopic training tasks (five replications of 3 tasks - cannulation, ring transfer, and rope manipulation). Half of the participants provided workload ratings using a traditional paper-and-pencil version of the NASA-TLX and MRQ; the remainder used a vocal (hands-free) version of the questionnaires. A follow-up experiment extended the evaluation of the hands-free version to actual medical students in a Minimally Invasive Surgery (MIS) training facility. The NASA-TLX was scored in 2 ways - (1) the traditional procedure using participant-specific weights to combine its 6 subscales, and (2) a simplified procedure - the NASA Raw Task Load Index (NASA-RTLX) - using the unweighted mean of the subscale scores. Comparison of the scores obtained from the hands-free and written administration conditions yielded coefficients of equivalence of r=0.85 (NASA-TLX) and r=0.81 (NASA-RTLX). Equivalence estimates for the individual subscales ranged from r=0.78 ("mental demand") to r=0.31 ("effort"). Both administration formats and scoring methods were equally sensitive to task and repetition effects. For the MRQ, the coefficient of equivalence for the hands-free and written versions was r=0.96 when tested on undergraduates. However, the sensitivity of the hands-free MRQ to task demands (�

A real-time vision-based hand gesture interaction system for virtual EAST

International Nuclear Information System (INIS)

Wang, K.R.; Xiao, B.J.; Xia, J.Y.; Li, Dan; Luo, W.L.

2016-01-01

Highlights: • Hand gesture interaction is first introduced to EAST model interaction. • We can interact with EAST model by a bared hand and a web camera. • We can interact with EAST model with a distance to screen. • Interaction is free, direct and effective. - Abstract: The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

A real-time vision-based hand gesture interaction system for virtual EAST

Energy Technology Data Exchange (ETDEWEB)

Wang, K.R., E-mail: wangkr@mail.ustc.edu.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Xiao, B.J.; Xia, J.Y. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Li, Dan [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Luo, W.L. [709th Research Institute, Shipbuilding Industry Corporation (China)

2016-11-15

Highlights: • Hand gesture interaction is first introduced to EAST model interaction. • We can interact with EAST model by a bared hand and a web camera. • We can interact with EAST model with a distance to screen. • Interaction is free, direct and effective. - Abstract: The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

Pure associative tactile agnosia for the left hand: clinical and anatomo-functional correlations.

Science.gov (United States)

Veronelli, Laura; Ginex, Valeria; Dinacci, Daria; Cappa, Stefano F; Corbo, Massimo

2014-09-01

Associative tactile agnosia (TA) is defined as the inability to associate information about object sensory properties derived through tactile modality with previously acquired knowledge about object identity. The impairment is often described after a lesion involving the parietal cortex (Caselli, 1997; Platz, 1996). We report the case of SA, a right-handed 61-year-old man affected by first ever right hemispheric hemorrhagic stroke. The neurological examination was normal, excluding major somaesthetic and motor impairment; a brain magnetic resonance imaging (MRI) confirmed the presence of a right subacute hemorrhagic lesion limited to the post-central and supra-marginal gyri. A comprehensive neuropsychological evaluation detected a selective inability to name objects when handled with the left hand in the absence of other cognitive deficits. A series of experiments were conducted in order to assess each stage of tactile recognition processing using the same stimulus sets: materials, 3D geometrical shapes, real objects and letters. SA and seven matched controls underwent the same experimental tasks during four sessions in consecutive days. Tactile discrimination, recognition, pantomime, drawing after haptic exploration out of vision and tactile-visual matching abilities were assessed. In addition, we looked for the presence of a supra-modal impairment of spatial perception and of specific difficulties in programming exploratory movements during recognition. Tactile discrimination was intact for all the stimuli tested. In contrast, SA was able neither to recognize nor to pantomime real objects manipulated with the left hand out of vision, while he identified them with the right hand without hesitations. Tactile-visual matching was intact. Furthermore, SA was able to grossly reproduce the global shape in drawings but failed to extract details of objects after left-hand manipulation, and he could not identify objects after looking at his own drawings. This case

Object and event recognition for stroke rehabilitation

Science.gov (United States)

Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.

2003-06-01

Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

Efficient Interaction Recognition through Positive Action Representation

Directory of Open Access Journals (Sweden)

Tao Hu

2013-01-01

Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

Automatic system for localization and recognition of vehicle plate numbers

OpenAIRE

Vázquez, N.; Nakano, M.; Pérez-Meana, H.

2003-01-01

This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

Preschoolers Explore Interactive Storybook Apps: The Effect on Word Recognition and Story Comprehension

Science.gov (United States)

Zipke, Marcy

2017-01-01

Two experiments explored the effects of reading digital storybooks on tablet computers with 25 preschoolers, aged 4-5. In the first experiment, the students' word recognition scores were found to increase significantly more when students explored a digital storybook and employed the read-aloud function than when they were read to from a comparable…

Proposals for the production of digital genres in English language textbooks

Directory of Open Access Journals (Sweden)

Karolinne Finamor Couto

2014-06-01

Full Text Available We intend, in this article, to discuss the results of a part of a Master research whose objective was to investigate whether the proposals for the production of digital genres in English language textbooks contribute to the development of literacies. Our theoretical discussions are based on the concept of genre (BAKHTIN, 2000; BRONCKART, 2009; MARCUSCHI, 2004, literacy (BRASIL, 2006; ROJO, 2009 and the guidelines of the National Curriculum Parameters (BRASIL, 1998. Our corpus - consisting of written production activities present in a didactic collection approved by PNLD/2011, Keep in Mind (CHIN; ZAORAB, 2009 - was analyzed in interface with the Guide and Announcement criteria, so that we could answer the research questions. Our results show that the criteria of the Announcement and the Guide are consistent, however, the proposals for written production do not effectively develop literacies, especially for not offering real communication practices in digital format, including therein the steps of the written production process: planning, writing and rewriting.

A Control Strategy with Tactile Perception Feedback for EMG Prosthetic Hand

Directory of Open Access Journals (Sweden)

Changcheng Wu

2015-01-01

Full Text Available To improve the control effectiveness and make the prosthetic hand not only controllable but also perceivable, an EMG prosthetic hand control strategy was proposed in this paper. The control strategy consists of EMG self-learning motion recognition, backstepping controller with stiffness fuzzy observation, and force tactile representation. EMG self-learning motion recognition is used to reduce the influence on EMG signals caused by the uncertainty of the contacting position of the EMG sensors. Backstepping controller with stiffness fuzzy observation is used to realize the position control and grasp force control. Velocity proportional control in free space and grasp force tracking control in restricted space can be realized by the same controller. The force tactile representation helps the user perceive the states of the prosthetic hand. Several experiments were implemented to verify the effect of the proposed control strategy. The results indicate that the proposed strategy has effectiveness. During the experiments, the comments of the participants show that the proposed strategy is a better choice for amputees because of the improved controllability and perceptibility.

Quantitative impact of direct, personal feedback on hand hygiene technique.

Science.gov (United States)

Lehotsky, Á; Szilágyi, L; Ferenci, T; Kovács, L; Pethes, R; Wéber, G; Haidegger, T

2015-09-01

This study investigated the effectiveness of targeting hand hygiene technique using a new training device that provides objective, personal and quantitative feedback. One hundred and thirty-six healthcare workers in three Hungarian hospitals participated in a repetitive hand hygiene technique assessment study. Ultraviolet (UV)-labelled hand rub was used at each event, and digital images of the hands were subsequently taken under UV light. Immediate objective visual feedback was given to participants, showing missed areas on their hands. The rate of inadequate hand rubbing reduced from 50% to 15% (P < 0.001). However, maintenance of this reduced rate is likely to require continuous use of the electronic equipment. Copyright © 2015 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Invariant Face recognition Using Infrared Images

International Nuclear Information System (INIS)

Zahran, E.G.

2012-01-01

Over the past few decades, face recognition has become a rapidly growing research topic due to the increasing demands in many applications of our daily life such as airport surveillance, personal identification in law enforcement, surveillance systems, information safety, securing financial transactions, and computer security. The objective of this thesis is to develop a face recognition system capable of recognizing persons with a high recognition capability, low processing time, and under different illumination conditions, and different facial expressions. The thesis presents a study for the performance of the face recognition system using two techniques; the Principal Component Analysis (PCA), and the Zernike Moments (ZM). The performance of the recognition system is evaluated according to several aspects including the recognition rate, and the processing time. Face recognition systems that use visual images are sensitive to variations in the lighting conditions and facial expressions. The performance of these systems may be degraded under poor illumination conditions or for subjects of various skin colors. Several solutions have been proposed to overcome these limitations. One of these solutions is to work in the Infrared (IR) spectrum. IR images have been suggested as an alternative source of information for detection and recognition of faces, when there is little or no control over lighting conditions. This arises from the fact that these images are formed due to thermal emissions from skin, which is an intrinsic property because these emissions depend on the distribution of blood vessels under the skin. On the other hand IR face recognition systems still have limitations with temperature variations and recognition of persons wearing eye glasses. In this thesis we will fuse IR images with visible images to enhance the performance of face recognition systems. Images are fused using the wavelet transform. Simulation results show that the fusion of visible and

Impacts of Digital Imaging versus Drawing on Student Learning in Undergraduate Biodiversity Labs

Science.gov (United States)

Basey, John M.; Maines, Anastasia P.; Francis, Clinton D.; Melbourne, Brett

2014-01-01

We examined the effects of documenting observations with digital imaging versus hand drawing in inquiry-based college biodiversity labs. Plant biodiversity labs were divided into two treatments, digital imaging (N = 221) and hand drawing (N = 238). Graduate-student teaching assistants (N = 24) taught one class in each treatment. Assessments…

Identification of motion from multi-channel EMG signals for control of prosthetic hand

International Nuclear Information System (INIS)

Geethanjali, P.; Ray, K.K.

2011-01-01

Full text: The authors in this paper propose an effective and efficient pattern recognition technique from four channel electromyogram (EMG) signals for control of multifunction prosthetic hand. Time domain features such as mean absolute value, number of zero crossings, number of slope sign changes and waveform length are considered for pattern recognition. The patterns are classified using simple logistic regression (SLR) technique and decision tree (DT) using J48 algorithm. In this study six specific hand and wrist motions are identified from the EMG signals obtained from ten different able-bodied. By considering relevant dominant features for pattern recognition, the processing time as well as memory space of the SLR and DT classifiers is found to be less in comparison with neural network (NN), k-nearest neighbour model 1 (kNN Model-1), k-nearest neighbour model 2 (kNN-Model-2) and linear discriminant analysis. The classification accuracy of SLR classifier is found to be 91 ± 1.9%. (author)

Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network.

Science.gov (United States)

Sun, Xin; Qian, Huinan

2016-01-01

Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of these hand-crafted features are low-level image representation, which is easily affected by noise and background. Secondly, the medicine images are very clean without any backgrounds, which makes it difficult to use in practical applications. Therefore, designing high-level image representation for recognition and retrieval in real world medicine images is facing a great challenge. Inspired by the recent progress of deep learning in computer vision, we realize that deep learning methods may provide robust medicine image representation. In this paper, we propose to use the Convolutional Neural Network (CNN) for Chinese herbal medicine image recognition and retrieval. For the recognition problem, we use the softmax loss to optimize the recognition network; then for the retrieval problem, we fine-tune the recognition network by adding a triplet loss to search for the most similar medicine images. To evaluate our method, we construct a public database of herbal medicine images with cluttered backgrounds, which has in total 5523 images with 95 popular Chinese medicine categories. Experimental results show that our method can achieve the average recognition precision of 71% and the average retrieval precision of 53% over all the 95 medicine categories, which are quite promising given the fact that the real world images have multiple pieces of occluded herbal and cluttered backgrounds. Besides, our proposed method achieves the state-of-the-art performance by improving previous studies with a large margin.

Hands of early primates.

Science.gov (United States)

Boyer, Doug M; Yapuncich, Gabriel S; Chester, Stephen G B; Bloch, Jonathan I; Godinot, Marc

2013-12-01

Questions surrounding the origin and early evolution of primates continue to be the subject of debate. Though anatomy of the skull and inferred dietary shifts are often the focus, detailed studies of postcrania and inferred locomotor capabilities can also provide crucial data that advance understanding of transitions in early primate evolution. In particular, the hand skeleton includes characteristics thought to reflect foraging, locomotion, and posture. Here we review what is known about the early evolution of primate hands from a comparative perspective that incorporates data from the fossil record. Additionally, we provide new comparative data and documentation of skeletal morphology for Paleogene plesiadapiforms, notharctines, cercamoniines, adapines, and omomyiforms. Finally, we discuss implications of these data for understanding locomotor transitions during the origin and early evolutionary history of primates. Known plesiadapiform species cannot be differentiated from extant primates based on either intrinsic hand proportions or hand-to-body size proportions. Nonetheless, the presence of claws and a different metacarpophalangeal [corrected] joint form in plesiadapiforms indicate different grasping mechanics. Notharctines and cercamoniines have intrinsic hand proportions with extremely elongated proximal phalanges and digit rays relative to metacarpals, resembling tarsiers and galagos. But their hand-to-body size proportions are typical of many extant primates (unlike those of tarsiers, and possibly Teilhardina, which have extremely large hands). Non-adapine adapiforms and omomyids exhibit additional carpal features suggesting more limited dorsiflexion, greater ulnar deviation, and a more habitually divergent pollex than observed plesiadapiforms. Together, features differentiating adapiforms and omomyiforms from plesiadapiforms indicate increased reliance on vertical prehensile-clinging and grasp-leaping, possibly in combination with predatory behaviors in

Handwritten Sindhi Character Recognition Using Neural Networks

Directory of Open Access Journals (Sweden)

Shafique Ahmed Awan

2018-01-01

Full Text Available OCR (OpticalCharacter Recognition is a technology in which text image is used to understand and write text by machines. The work on languages containing isolated characters such as German, English, French and others is at its peak. The OCR and ICR (Intelligent Character Recognition research in Sindhi script is currently at in starting stages and not sufficient work have been cited in this area even though Sindhi language is rich in culture and history. This paper presents one of the initial steps in recognizing Sindhi handwritten characters. The isolated characters of Sindhi script written by thesubjects have been recognized. The various subjects were asked to write Sindhi characters in unconstrained form and then the written samples were collected and scanned through a flatbed scanner. The scanned documents were preprocessedwith the help of binary conversion, removing noise by pepper noise and the lines were segmented with the help of horizontal profile technique. The segmented lines were used to extract characters from scanned pages.This character segmentation was done by vertical projection. The extracted characters have been used to extract features so that the characters can be classified easily. Zoning was used for the feature extraction technique. For the classification, neural network has been used. The recognized characters converted into editable text with an average accuracy of 85%.

WRITTEN COMMUNICATION IN BUSINESS

OpenAIRE

Oana COSMAN

2013-01-01

The article examines the work of researchers primarily interested in the investigation of written communication in business settings. The author regards 'business discourse' as a field of study with distinct features in the domain of discourse analysis. Thus, the paper overviews the most important contributions to the development of written business discourse with a number of landmark studies. To gain a greater understanding of the written business discourse, the author also investigates some...

Learner autonomy development through digital gameplay

Directory of Open Access Journals (Sweden)

Alice Chik

2011-04-01

Full Text Available Playing digital games is undeniably a popular leisure activity, and digital gaming is also gaining academic attention and recognition for enhancing digital literacies and learning motivation. One tricky issue when exploring digital gaming in Asian contexts is the popularity of English and Japanese games. Though Chinese and Korean online games are readily available, many of the more popular commercial off-the-shelf (COTS digital games are in English and Japanese. Students in Hong Kong are required to take English as a foreign language, which resulted in a huge range of proficiency, but Japanese is not offered at public schools. So, most Hong Kong gamers are playing foreign language games. Yet language barriers do not diminish the market demand for foreign language digital games. This paper explores the phenomenon of digital gaming in foreign languages. Based on findings from an on-going research project with ten undergraduate video gamers (F=4, M=6, this paper argues that gamers exercise learner autonomy by managing their gaming both as leisure and learning experiences.

The Anatomy of Digital Trade Infrastructures

DEFF Research Database (Denmark)

Rukanova, Boriana; Zinner Henriksen, Helle; Henningsson, Stefan

2017-01-01

In global supply chains information about transactions resides in fragmented pockets within business and government systems. The introduction of digital trade infrastructures (DTI) that transcend organizational and systems domains is driven by the prospect of reducing this information fragmentation......, thereby enabling improved security and efficiency in trade process. To understand the problem at hand and build cumulative knowledge about its resolution a way to conceptualize the different digital trade infrastructure initiatives is needed. This paper develops the Digital Trade Infrastructure Framework...

Towards a Digital Infrastructure for Illustrated Handwritten Archives

NARCIS (Netherlands)

Weber, Andreas; Ameryan, Mahya; Wolstencroft, Katherine; Stork, Lise; Heerlien, Maarten; Schomaker, Lambert; Ioannides, Marinos

Large and important parts of cultural heritage are stored in archives that are difficult to access, even after digitization. Documents and notes are written in hard-to-read historical handwriting and are often interspersed with illustrations. Such collections are weakly structured and largely

Advanced digital video surveillance for safeguard and physical protection

International Nuclear Information System (INIS)

Kumar, R.

2002-01-01

Full text: Video surveillance is a very crucial component in safeguard and physical protection. Digital technology has revolutionized the surveillance scenario and brought in various new capabilities like better image quality, faster search and retrieval of video images, less storage space for recording, efficient transmission and storage of video, better protection of recorded video images, and easy remote accesses to live and recorded video etc. The basic safeguard requirement for verifiably uninterrupted surveillance has remained largely unchanged since its inception. However, changes to the inspection paradigm to admit automated review and remote monitoring have dramatically increased the demands on safeguard surveillance system. Today's safeguard systems can incorporate intelligent motion detection with very low rate of false alarm and less archiving volume, embedded image processing capability for object behavior and event based indexing, object recognition, efficient querying and report generation etc. It also demands cryptographically authenticating, encrypted, and highly compressed video data for efficient, secure, tamper indicating and transmission. In physical protection, intelligent on robust video motion detection, real time moving object detection and tracking from stationary and moving camera platform, multi-camera cooperative tracking, activity detection and recognition, human motion analysis etc. is going to play a key rote in perimeter security. Incorporation of front and video imagery exploitation tools like automatic number plate recognition, vehicle identification and classification, vehicle undercarriage inspection, face recognition, iris recognition and other biometric tools, gesture recognition etc. makes personnel and vehicle access control robust and foolproof. Innovative digital image enhancement techniques coupled with novel sensor design makes low cost, omni-directional vision capable, all weather, day night surveillance a reality

Standard digital reference images for titanium castings

CERN Document Server

American Society for Testing and Materials. Philadelphia

2010-01-01

1.1 The digital reference images provided in the adjunct to this standard illustrate various types and degrees of discontinuities occurring in titanium castings. Use of this standard for the specification or grading of castings requires procurement of the adjunct digital reference images, which illustrate the discontinuity types and severity levels. They are intended to provide the following: 1.1.1 A guide enabling recognition of titanium casting discontinuities and their differentiation both as to type and degree through digital radiographic examination. 1.1.2 Example digital radiographic illustrations of discontinuities and a nomenclature for reference in acceptance standards, specifications and drawings. 1.2 The digital reference images consist of seventeen digital files each illustrating eight grades of increasing severity. The files illustrate seven common discontinuity types representing casting sections up to 1-in. (25.4-mm). 1.3 The reference radiographs were developed for casting sections up to 1...

Digital supply chain management by using it systems

OpenAIRE

Stanišauskas, Ramūnas

2018-01-01

There are a lot of researches done to better understand the main principles of supply chain management, therefore supply chain management is well understood and quite common. On the other hand, nowadays more and more products and services are developed in digital environment, therefore regular supply chains are no longer viable and it is quite hard to adapt them. Suppliers in digital supply chain are creating digital products by using computer technologies and therefore digital products never...

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Digital Immigrants and Digital Natives: Learning Business Informatics at Higher Educational Level

Directory of Open Access Journals (Sweden)

Suša Dalia

2014-09-01

Full Text Available Background: The term digital natives refer to those born since the 1980s and have been growing up surrounded by technology. On the other hand, digital immigrants are born before 1980s and learned how to use technology later in life. Objectives: Goal of the paper is to explore attitudes of digital native students on the course of Business Informatics at higher educational institutions (HEIs, and to compare them with attitudes of digital immigrants. Methods/Approach: The survey was conducted in 2014 using the sample of first-year Business Informatics students from the Faculty of Economics and Business in Zagreb, Croatia. Results were compared with a research conducted in 1998. Results: In comparison to an earlier research, digital natives perceive their level of competency in the subject of Business Informatics before teaching practices much higher compared to digital immigrants. However, there is still an increase in digital native students’ level of competency in the subject before and after teaching practices. Conclusions: The research confirms a shift from digital immigrants to digital natives who show high level of interest for Business Informatics course topics and find its utility very high. However, constant improvement of delivering knowledge is needed in order to keep these high levels.

Optical character recognition of camera-captured images based on phase features

Science.gov (United States)

Diaz-Escobar, Julia; Kober, Vitaly

2015-09-01

Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

The nuclear fuel rod character recognition system based on neural network technique

International Nuclear Information System (INIS)

Kim, Woong-Ki; Park, Soon-Yong; Lee, Yong-Bum; Kim, Seung-Ho; Lee, Jong-Min; Chien, Sung-Il.

1994-01-01

The nuclear fuel rods should be discriminated and managed systematically by numeric characters which are printed at the end part of each rod in the process of producing fuel assembly. The characters are used to examine manufacturing process of the fuel rods in the inspection process of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies to establish automatic manufacturing process of fuel assembly. In the developed character recognition system, mesh feature set extracted from each character written in the fuel rod is employed to train a neural network based on back-propagation algorithm as a classifier for character recognition system. Performance evaluation has been achieved on a test set which is not included in a training character set. (author)

On the Feasibility of Interoperable Schemes in Hand Biometrics

Directory of Open Access Journals (Sweden)

Miguel A. Ferrer

2012-02-01

Full Text Available Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

Nippon Cinema at the digital turning point

Directory of Open Access Journals (Sweden)

Marek Bochniarz

2014-01-01

Full Text Available This article is a review of a book written by Mitsuyo Wada Marciano – Japanese Cinema in the Digital Age. The author of this book examines the recent developments in the Japanese film industry at the turning point in the development of digital technologies. The book seeks to overcome the western approach to the subject, reinterprets classic films and explores new trends in transnational Japanese cinema (the term was proposed by the author to explain the situation of Japanese films in the context of Asian countries.

Digital terrestrial television broadcasting technology and system

CERN Document Server

2015-01-01

Now under massive deployment worldwide, digital terrestrial television broadcasting (DTTB) offers one of the most attractive ways to deliver digital TV over the VHF/UHF band. Written by a team of experts for specialists and non-specialists alike, this book serves as a comprehensive guide to DTTB. It covers the fundamentals of channel coding and modulation technologies used in DTTB, as well as receiver technology for synchronization, channel estimation, and equalization. It also covers the recently introduced Chinese DTTB standard, using the SFN network in Hong Kong as an example.

ASERA: A Spectrum Eye Recognition Assistant

Science.gov (United States)

Yuan, Hailong; Zhang, Haotong; Zhang, Yanxia; Lei, Yajuan; Dong, Yiqiao; Zhao, Yongheng

2018-04-01

ASERA, ASpectrum Eye Recognition Assistant, aids in quasar spectral recognition and redshift measurement and can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). This interactive software allows users to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. ASERA is an efficient and user-friendly semi-automated toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope) and is available as a standalone Java application and as a Java applet. The software offers several functions, including wavelength and flux scale settings, zoom in and out, redshift estimation, and spectral line identification.

A hard tissue cephalometric comparative study between hand tracing and computerized tracing

Directory of Open Access Journals (Sweden)

Ramachandra Prabhakar

2014-01-01

Full Text Available Aims: To analyze and compare the angular and linear hard tissue cephalometric measurements using hand-tracing and computerized tracings with Nemoceph and Dolphin software systems. Subjects and Methods: A total of 30 cephalograms were randomly chosen for study with the following criteria, cephalograms of patients with good contrast, no distortion, and minimal radiographic artifacts were considered using the digital method (Kodak 8000 C with 12 angular and nine linear parameters selected for the study. Comparisons were determined by post-hoc test using Tukey HSD method. The N-Par tests were performed using Kruskal-Walli′s method. Statistical Analysis Used: ANOVA and post-hoc. Results: The results of this study show that there is no significant difference in the angular and linear measurements recorded. The P values were significant at 0.05 levels for two parameters, Co-A and Co-Gn with the hand-tracing method. This was significant in ANOVA and post-hoc test by Tukey HSD method. Conclusions: This study of comparison provides support for transition from digital hand to computerized tracing methodology. In fact, digital computerized tracings were easier and less time consuming, with the same reliability irrespective of each method of tracing.

Documents at hand: learning from paper to improve digital technologies

NARCIS (Netherlands)

Bondarenko, O.; Janssen, Ruud; Veer, van der G.C.; Gayle, C.

2005-01-01

In this paper the results of a two-year ethnographic study of the personal document management of 28 information workers is described. Both the paper and digital domain were taken into account during the study. The results reaffirmed that document management is strongly related to task management.

Digitally programmable signal generator

International Nuclear Information System (INIS)

Priatko, G.J.; Kaskey, J.A.

1988-01-01

A digitally programmable signal generator (DPSG) includes a first memory from which data is written into a second memory formed of n banks. Each bank includes four memories and a multiplexer, the banks being read once during each time frame, the read-out bits being multiplexed and fed out serially in synchronism with a plurality of clock pulses occuring during a time frame. The resulting serial bit streams may be fed in parallel to a digital-to-analog converter. The DPSG can be used in applications such as Atomic Vapor Laser Isotope Separation (AVLIS) to create an optimal match between the process laser's spectral profile and that of the vaporized material, optical telecommunications, non-optical telecommunication in the microwave and radio spectrum, radar, electronic countermeasures, high speed computer interconnects, local area networks, high definition video transport and the multiplexing of large quantities of slow digital memory into high speed data streams. This invention extends the operation of DPSGs into the GHz range. (author)

[A case with apraxia of tool use: selective inability to form a hand posture for a tool].

Science.gov (United States)

Hayakawa, Yuko; Fujii, Toshikatsu; Yamadori, Atsushi; Meguro, Kenichi; Suzuki, Kyoko

2015-03-01

Impaired tool use is recognized as a symptom of ideational apraxia. While many studies have focused on difficulties in producing gestures as a whole, using tools involves several steps; these include forming hand postures appropriate for the use of certain tool, selecting objects or body parts to act on, and producing gestures. In previously reported cases, both producing and recognizing hand postures were impaired. Here we report the first case showing a selective impairment of forming hand postures appropriate for tools with preserved recognition of the required hand postures. A 24-year-old, right-handed man was admitted to hospital because of sensory impairment of the right side of the body, mild aphasia, and impaired tool use due to left parietal subcortical hemorrhage. His ability to make symbolic gestures, copy finger postures, and orient his hand to pass a slit was well preserved. Semantic knowledge for tools and hand postures was also intact. He could flawlessly select the correct hand postures in recognition tasks. He only demonstrated difficulties in forming a hand posture appropriate for a tool. Once he properly grasped a tool by trial and error, he could use it without hesitation. These observations suggest that each step of tool use should be thoroughly examined in patients with ideational apraxia.

Gamma spectra pictures using a digital plotter. Program MONO

International Nuclear Information System (INIS)

Los Arcos Merino, J.M.

1978-01-01

The program MONO has been written for a CALCOMP-936 digital plotter operating off- -line with a UMI VAC 1106 computer, to obtain graphic representations of single gamma spectra stored on magnetic tape. It allows to plot the whole spectrum or only a part, as well as to draw a given spectrum on the same or different picture than the previous one. Ten representation scales are available and at up nine comment lines can be written in a graphic. (Author) 4 refs

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

Science.gov (United States)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Scrolling forward, second edition making sense of documents in the digital age

CERN Document Server

Levy, David M

2015-01-01

A fascinating, insightful, and wonderfully written exploration of the document. Like Henry Petroski's The Pencil, David Levy's Scrolling Forward takes a common, everyday object, the document, and illuminates what it reveals about us, both in the past and in the digital age. We are surrounded daily by documents of all kinds—letters and credit card receipts, business memos and books, television images and web pages—yet we rarely stop to reflect on their significance. Now, in this period of digital transition, our written forms as well as our reading and writing habits are being disturbed and transformed by new technologies and practices. An expert on information and written forms, and a former researcher for the document pioneer Xerox, Levy masterfully navigates these concerns, offering reassurance while sharing his own excitement about many of the new kinds of emerging documents. He demonstrates how today's technologies, particularly the personal computer and the World Wide Web, are having analogous effects ...

Network analysis of named entity co-occurrences in written texts

Science.gov (United States)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

Pattern recognition and modelling of earthquake registrations with interactive computer support

International Nuclear Information System (INIS)

Manova, Katarina S.

2004-01-01

The object of the thesis is Pattern Recognition. Pattern recognition i.e. classification, is applied in many fields: speech recognition, hand printed character recognition, medical analysis, satellite and aerial-photo interpretations, biology, computer vision, information retrieval and so on. In this thesis is studied its applicability in seismology. Signal classification is an area of great importance in a wide variety of applications. This thesis deals with the problem of (automatic) classification of earthquake signals, which are non-stationary signals. Non-stationary signal classification is an area of active research in the signal and image processing community. The goal of the thesis is recognition of earthquake signals according to their epicentral zone. Source classification i.e. recognition is based on transformation of seismograms (earthquake registrations) to images, via time-frequency transformations, and applying image processing and pattern recognition techniques for feature extraction, classification and recognition. The tested data include local earthquakes from seismic regions in Macedonia. By using actual seismic data it is shown that proposed methods provide satisfactory results for classification and recognition.(Author)

Development of a digital reactivity meter and reactor physics data processor

International Nuclear Information System (INIS)

Shimazu, Y.; Nakano, Y.; Tahara, Y.; Okayama, T.

1986-01-01

Reactor physics tests at initial startup and after refueling are performed to verify the nuclear design and to assure safe operations thereafter. Analogue computers and instruments have been widely used for the acquisition of data and those data have been reduced by hand. These conventional procedures, however, require much time and labor. On the other hand, the development of digital computers and devices has made great progress. Under these circumstances the authors have digitalized the procedures mentioned. As described in the paper, the digitalized reactivity meter and data processor system proved to function satisfactorily as intended at the design stage

Relating the Content and Confidence of Recognition Judgments

Science.gov (United States)

Selmeczy, Diana; Dobbins, Ian G.

2014-01-01

The Remember/Know procedure, developed by Tulving (1985) to capture the distinction between the conscious correlates of episodic and semantic retrieval, has spawned considerable research and debate. However, only a handful of reports have examined the recognition content beyond this dichotomous simplification. To address this, we collected…

Effects of non-surgical factors on digital replantation survival rate: a meta-analysis.

Science.gov (United States)

Ma, Z; Guo, F; Qi, J; Xiang, W; Zhang, J

2016-02-01

This study aimed to evaluate the risk factors affecting survival rate of digital replantation by a meta-analysis. A computer retrieval of MEDLINE, OVID, EMBASE, and CNKI databases was conducted to identify citations for digital replantation with digit or finger or thumb or digital or fingertip and replantation as keywords. RevMan 5.2 software was used to calculate the pooled odds ratios. In total, there were 4678 amputated digits in 2641 patients. Gender and ischemia time had no significant influence on the survival rate of amputation replantation (P > 0.05). Age, injured hand, injury type, zone, and the method of preservation the amputated digit significantly influence the survival rate of digital replantation (P < 0.05). Children, right hand, crush, or avulsion and little finger are the risk factors that adversely affect the outcome. Level 5*. © The Author(s) 2015.

2nd International Symposium on Signal Processing and Intelligent Recognition Systems

CERN Document Server

Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

2016-01-01

This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

Impaired processing of self-face recognition in anorexia nervosa.

Science.gov (United States)

Hirot, France; Lesage, Marine; Pedron, Lya; Meyer, Isabelle; Thomas, Pierre; Cottencin, Olivier; Guardia, Dewi

2016-03-01

Body image disturbances and massive weight loss are major clinical symptoms of anorexia nervosa (AN). The aim of the present study was to examine the influence of body changes and eating attitudes on self-face recognition ability in AN. Twenty-seven subjects suffering from AN and 27 control participants performed a self-face recognition task (SFRT). During the task, digital morphs between their own face and a gender-matched unfamiliar face were presented in a random sequence. Participants' self-face recognition failures, cognitive flexibility, body concern and eating habits were assessed with the Self-Face Recognition Questionnaire (SFRQ), Trail Making Test (TMT), Body Shape Questionnaire (BSQ) and Eating Disorder Inventory-2 (EDI-2), respectively. Subjects suffering from AN exhibited significantly greater difficulties than control participants in identifying their own face (p = 0.028). No significant difference was observed between the two groups for TMT (all p > 0.1, non-significant). Regarding predictors of self-face recognition skills, there was a negative correlation between SFRT and body mass index (p = 0.01) and a positive correlation between SFRQ and EDI-2 (p face recognition.

The Plastic Surgery Hand Curriculum.

Science.gov (United States)

Silvestre, Jason; Levin, L Scott; Serletti, Joseph M; Chang, Benjamin

2015-12-01

Designing an effective hand rotation for plastic surgery residents is difficult. The authors address this limitation by elucidating the critical components of the hand curriculum during plastic surgery residency. Hand questions on the Plastic Surgery In-Service Training Exam for six consecutive years (2008 to 2013) were characterized by presence of imaging, vignette setting, question taxonomy, answer domain, anatomy, and topic. Answer references were quantified by source and year of publication. Two hundred sixty-six questions were related to hand surgery (22.7 percent of all questions; 44.3 per year) and 61 were accompanied by an image (22.9 percent). Vignettes tended to be clinic- (50.0 percent) and emergency room-based (35.3 percent) (p < 0.001). Questions required decision-making (60.5 percent) over interpretation (25.9 percent) and recall skills (13.5 percent) (p < 0.001). Answers focused on interventions (57.5 percent) over anatomy/pathology (25.2 percent) and diagnoses (17.3 percent) (p < 0.001). Nearly half of the questions focused on the digits. The highest yield topics were trauma (35.3 percent), reconstruction (24.4 percent), and aesthetic and functional problems (14.2 percent). The Journal of Hand Surgery (American volume) (20.5 percent) and Plastic and Reconstructive Surgery (18.0 percent) were the most-cited journals, and the median publication lag was 7 years. Green's Operative Hand Surgery was the most-referenced textbook (41.8 percent). These results will enable trainees to study hand surgery topics with greater efficiency. Faculty can use these results to ensure that tested topics are covered during residency training. Thus, a benchmark is established to improve didactic, clinical, and operative experiences in hand surgery.

First-Hand Accounts of Sensory Perceptual Experiences in Autism: A Qualitative Analysis.

Science.gov (United States)

Jones, Robert S. P.; Quigney, Ciara; Huws, Jaci C.

2003-01-01

Five first-hand Web page accounts of unusual sensory perceptual experiences written by persons with high-functioning autism were selected for qualitative analysis. Four core categories emerged: turbulent sensory perceptual experiences; coping mechanisms; enjoyable sensory perceptual experiences; and awareness of being different, suggesting they…

Clinical aspects of the hand-arm vibration syndrome. A review.

Science.gov (United States)

Pyykkö, I

1986-10-01

At present it seems likely that the different components of the hand-arm vibration syndrome, eg, vibration-induced white finger (VWF), numbing of the hands and arms, muscular fatigue, and occasionally prevalent bone degeneration, may arise independently, and therefore they should be evaluated separately. Evidence of changes caused in the autonomic nervous functions of the body by local vibration is not conclusive. The vascular history should be confirmed objectively with a cold provocation test under laboratory conditions. In individual diagnostics it is useful to record (with modern plethysmographic techniques) the recovery of digital temperature, digital blood pressure, and flow after local cooling. Vibrotactile perception measurement seems to be suitable for group diagnosis. Much of the diagnostic weight for VWF can be obtained from accurate case histories, although, for early changes, the history may be atypical. The lack of simple objective tests for evaluating the hand-arm vibration syndrome makes it difficult to, eg, confirm the history of its different components objectively and estimate the extent of the disability it causes.

Targeted Query Expansions as a Method for Searching Mixed Quality Digitized Cultural Heritage Documents

NARCIS (Netherlands)

Keskustalo, H.; Kettunen, K.; Kumpulainen, S.; Ferro, N.; Silvello, G.; Järvelin, A.; Kekäläinen, J.; Arvola, P.; Saastamoinen, M.; Sormunen, E.; Järvelin, K.

2015-01-01

Digitization of cultural heritage is a huge ongoing effort in many countries. In digitized historical documents, words may occur in different surface forms due to three types of variation - morphological variation, historical variation, and errors in optical character recognition (OCR). Because

Implementation of perceptual aspects in a face recognition algorithm

International Nuclear Information System (INIS)

Crenna, F; Bovio, L; Rossi, G B; Zappa, E; Testa, R; Gasparetto, M

2013-01-01

Automatic face recognition is a biometric technique particularly appreciated in security applications. In fact face recognition presents the opportunity to operate at a low invasive level without the collaboration of the subjects under tests, with face images gathered either from surveillance systems or from specific cameras located in strategic points. The automatic recognition algorithms perform a measurement, on the face images, of a set of specific characteristics of the subject and provide a recognition decision based on the measurement results. Unfortunately several quantities may influence the measurement of the face geometry such as its orientation, the lighting conditions, the expression and so on, affecting the recognition rate. On the other hand human recognition of face is a very robust process far less influenced by the surrounding conditions. For this reason it may be interesting to insert perceptual aspects in an automatic facial-based recognition algorithm to improve its robustness. This paper presents a first study in this direction investigating the correlation between the results of a perception experiment and the facial geometry, estimated by means of the position of a set of repere points

Hybrid gesture recognition system for short-range use

Science.gov (United States)

Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun

2012-03-01

In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.

Advanced techniques in digital mammographic images recognition

International Nuclear Information System (INIS)

Aliu, R. Azir

2011-01-01

Computer Aided Detection and Diagnosis is used in digital radiography as a second thought in the process of determining diagnoses, which reduces the percentage of wrong diagnoses of the established interpretation of mammographic images. The issues that are discussed in the dissertation are the analyses and improvement of advanced technologies in the field of artificial intelligence, more specifically in the field of machine learning for solving diagnostic problems and automatic detection of speculated lesions in digital mammograms. The developed of SVM-based ICAD system with cascade architecture for analyses and comparison mammographic images in both projections (CC and MLO) gives excellent result for detection and masses and microcalcifications. In order to develop a system with optimal performances of sensitivity, specificity and time complexity, a set of relevant characteristics need to be created which will show all the pathological regions that might be present in the mammographic image. The structure of the mammographic image, size and the large number of pathological structures in this area are the reason why the creation of a set of these features is necessary for the presentation of good indicators. These pathological structures are a real challenge today and the world of science is working in that direction. The doctoral dissertation showed that the system has optimal results, which are confirmed by experts, and institutions, which are dealing with these same issues. Also, the thesis presents a new approach for automatic identification of regions of interest in the mammographic image where regions of interest are automatically selected for further processing mammography in cases when the number of examined patients is higher. Out of 480 mammographic images downloaded from MIAS database and tested with ICAD system the author shows that, after separation and selection of relevant features of ICAD system the accuracy is 89.7% (96.4% for microcalcifications

Postura da mão e imagética motora: um estudo sobre reconhecimento de partes do corpo Hand posture and motor imagery: a body-part recognition study

Directory of Open Access Journals (Sweden)

AP Lameira

2008-10-01

Full Text Available OBJETIVOS: Assim como a imagética motora, o reconhecimento de partes do corpo aciona representações somatosensoriais específicas. Essas representações são ativadas implicitamente para comparar o corpo com o estímulo. No presente estudo, investigou-se a influência da informação proprioceptiva da postura no reconhecimento de partes do corpo (mãos e propõe-se a utilização dessa tarefa na reabilitação de pacientes neurológicos. MATERIAIS E MÉTODOS: Dez voluntários destros participaram do experimento. A tarefa era reconhecer a lateralidade de figuras da mão apresentada, em várias perspectivas e em vários ângulos de orientação. Para a figura da mão direita, o voluntário pressionava a tecla direita e para a figura da mão esquerda, a tecla esquerda. Os voluntários realizavam duas sessões: uma com as mãos na postura prona e outra com as mãos na postura supina. RESULTADOS: Os tempos de reação manual (TRM eram maiores para as vistas e orientações, nas quais é difícil realizar o movimento real, mostrando que durante a tarefa, existe um acionamento de representações motoras para comparar o corpo com o estímulo. Além disso, existe uma influência da postura do sujeito em vistas e ângulos específicos. CONCLUSÕES: Estes resultados mostram que representações motoras são ativadas para comparar o corpo com o estímulo e que a postura da mão influencia esta ressonância entre estímulo e parte do corpo.OBJECTIVE: Recognition of body parts activates specific somatosensory representations in a way that is similar to motor imagery. These representations are implicitly activated to compare the body with the stimulus. In the present study, we investigate the influence of proprioceptive information relating to body posture on the recognition of body parts (hands. It proposes that this task could be used for rehabilitation of neurological patients. METHODS: Ten right-handed volunteers participated in this experiment. The

Human motion sensing and recognition a fuzzy qualitative approach

CERN Document Server

Liu, Honghai; Ji, Xiaofei; Chan, Chee Seng; Khoury, Mehdi

2017-01-01

This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the ...

Optical character recognition based on nonredundant correlation measurements.

Science.gov (United States)

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Specificity and affinity quantification of flexible recognition from underlying energy landscape topography.

Directory of Open Access Journals (Sweden)

Xiakun Chu

2014-08-01

Full Text Available Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less flexibility leads to weaker (stronger coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

Implicit multisensory associations influence voice recognition.

Directory of Open Access Journals (Sweden)

Katharina von Kriegstein

2006-10-01

Full Text Available Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.

Glyph Identification and Character Recognition for Sindhi OCR

Directory of Open Access Journals (Sweden)

NISAR AHMEDMEMON

2017-10-01

Full Text Available A computer can read and write multiple languages and today?s computers are capable of understanding various human languages. A computer can be given instructions through various input methods but OCR (Optical Character Recognition and handwritten character recognition are the input methods in which a scanned page containing text is converted into written or editable text. The change in language text available on scanned page demands different algorithm to recognize text because every language and script pose varying number of challenges to recognize text. The Latin language recognition pose less difficulties compared to Arabic script and languages that use Arabic script for writing and OCR systems for these Latin languages are near to perfection. Very little work has been done on regional languages of Pakistan. In this paper the Sindhi glyphs are identified and the number of characters and connected components are identified for this regional language of Pakistan. A graphical user interface has been created to perform identification task for glyphs and characters of Sindhi language. The glyphs of characters are successfully identified from scanned page and this information can be used to recognize characters. The language glyph identification can be used to apply suitable algorithm to identify language as well as to achieve a higher recognition rate.

Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers

DEFF Research Database (Denmark)

Borkowski, Robert; Zibar, Darko; Caballero Jambrina, Antonio

2013-01-01

We present a technique for modulation format recognition for heterogeneous reconfigurable optical networks. The method is based on Stokes space signal representation and uses a variational Bayesian expectation maximization machine learning algorithm. Differentiation between diverse common coheren...

Flexible frontiers for text division into rows

Directory of Open Access Journals (Sweden)

Dan L. Lacrămă

2009-01-01

Full Text Available This paper presents an original solution for flexible hand-written text division into rows. Unlike the standard procedure, the proposed method avoids the isolated characters extensions amputation and reduces the recognition error rate in the final stage.

Handwriting or Typewriting? The Influence of Pen- or Keyboard-Based Writing Training on Reading and Writing Performance in Preschool Children

Science.gov (United States)

Kiefer, Markus; Schuler, Stefanie; Mayer, Carmen; Trumpp, Natalie M.; Hille, Katrin; Sachse, Steffi

2015-01-01

Digital writing devices associated with the use of computers, tablet PCs, or mobile phones are increasingly replacing writing by hand. It is, however, controversially discussed how writing modes influence reading and writing performance in children at the start of literacy. On the one hand, the easiness of typing on digital devices may accelerate reading and writing in young children, who have less developed sensory-motor skills. On the other hand, the meaningful coupling between action and perception during handwriting, which establishes sensory-motor memory traces, could facilitate written language acquisition. In order to decide between these theoretical alternatives, for the present study, we developed an intense training program for preschool children attending the German kindergarten with 16 training sessions. Using closely matched letter learning games, eight letters of the German alphabet were trained either by handwriting with a pen on a sheet of paper or by typing on a computer keyboard. Letter recognition, naming, and writing performance as well as word reading and writing performance were assessed. Results did not indicate a superiority of typing training over handwriting training in any of these tasks. In contrast, handwriting training was superior to typing training in word writing, and, as a tendency, in word reading. The results of our study, therefore, support theories of action-perception coupling assuming a facilitatory influence of sensory-motor representations established during handwriting on reading and writing. PMID:26770286

Our Digital Conversion

Science.gov (United States)

Edwards, Mark

2012-01-01

In this article, the author describes their digital conversion initiative at Mooresville Graded School District. The project has placed a MacBook Air laptop in the hands of every 3rd through 12th grader and their teachers in the district over the past four years, with over 5,000 computers distributed. But they believe their academic successes have…

Hand hygiene in the nursery during diaper changing.

Science.gov (United States)

Phang, Koh Ni; Maznin, Nur Liyanna; Yip, Wai Kin

2012-12-01

This project aimed to improve hand hygiene practice during diaper changing among nurses working in the nursery. This project was conducted in one of the nurseries in a 935-bed acute care hospital with a sample of 15 nurses. A pre- and post-intervention audit was conducted utilising the Joanna Briggs Institute Practical Application of Clinical Evidence System and Getting Research into Practice module. A revised written workflow, which specified the occasions and process for hand hygiene during diaper changing, was introduced. Modifications to the baby bassinets and nursery were made after barriers to good hand hygiene were identified. The project was carried out over 4 months, from March to June 2011. The post-intervention audit results show an improvement in performing hand washing after changing diapers (20%) and performing the correct steps of hand rubbing (25%). However, the compliance rates decreased for the other criteria that measured whether hand rubbing or hand washing was performed prior to contacting the infant and after wrapping the infant, and whether hand washing was performed correctly. The improvement in compliance with hand washing--the main focus of the new workflow--after changing diapers was especially significant. The results indicated that having a workflow on the occasions and process for hand hygiene during diaper changing was useful in standardising practice. Pre- and post-implementation audits were effective methods for evaluating the effect of translating evidence into practice. However, this project had limited success in improving compliance with hand hygiene. This suggested that more effort is needed to reinforce the importance of hand hygiene and compliance to the proposed workflow. In addition, this project showed that for change to take place successfully, environmental modifications, increased awareness and adequate communication to every staff member are essential. © 2012 The Authors. International Journal of Evidence

Digital TV, advertising and audience

Directory of Open Access Journals (Sweden)

Ângelo Cruz

2011-04-01

Full Text Available This article aims to analyze the advertisingsegment and their relationship with the development process of the digital television. We intent to observe the new perspectives of production and consumption of media. Among other things, that involves the issues of interactivity, the exhaustion of the traditional media models, and the relationship of the new media with the audience, considering the analysis of the tripod: digital television, advertising and audience. In Brazil, with the implementation of the Brazilian System of Digital Television (SBTVD, the problem takes bigger proportions, as a consequence of the possibility to issue and track down the digital content consumed. That happens as a consequence of the consumer ability to watch the program withor without the commercial break. At the current model of television, the public is the legitimizing factor: the broadcasters issues the public a ention asan instrument to obtain pecuniary rewarding of theadvertisers. That model constitutes itself as the main funding source of the channels and networks. On the one hand, digital television represents an advantage at the quality of picture and audio, multiplying the capacity to transmit television signals and to transport new features and services. On the other hand, it seems impossible to transform this industry without some reaction. The many interests involved constitute the main cause of that scenario: the agents interested in advertising are those concerned with the role of ideology, the support of capitalism and the industrial culture. Considering all these questions, it seems almost impossible to produce deep chances,contrary to the interests involved.

The Hand-Foot Skin Reaction and Quality of Life Questionnaire: An Assessment Tool for Oncology

OpenAIRE

Anderson, Roger T.; Keating, Karen N.; Doll, Helen A.; Camacho, Fabian

2015-01-01

This study describes the development and validation of a brief, patient self-reported questionnaire (the hand-foot skin reaction and quality of life questionnaire) supporting its suitability for use in clinical research to aid in early recognition of symptoms, to evaluate the effectiveness of agents for hand-foot skin reaction (HFSR) or hand-foot syndrome (HFS) treatment within clinical trials, and to evaluate the impact of these treatments on HFS/R-associated patients’ health-related quality...

Attributing Authorship in the Noisy Digitized Correspondence of Jacob and Wilhelm Grimm

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Greta Franzini

2018-04-01

Full Text Available This article presents the results of a multidisciplinary project aimed at better understanding the impact of different digitization strategies in computational text analysis. More specifically, it describes an effort to automatically discern the authorship of Jacob and Wilhelm Grimm in a body of uncorrected correspondence processed by HTR (Handwritten Text Recognition and OCR (Optical Character Recognition, reporting on the effect this noise has on the analyses necessary to computationally identify the different writing style of the two brothers. In summary, our findings show that OCR digitization serves as a reliable proxy for the more painstaking process of manual digitization, at least when it comes to authorship attribution. Our results suggest that attribution is viable even when using training and test sets from different digitization pipelines. With regards to HTR, this research demonstrates that even though automated transcription significantly increases the risk of text misclassification when compared to OCR, a cleanliness above ≈ 20% is already sufficient to achieve a higher-than-chance probability of correct binary attribution.

Digital Archiving: Where the Past Lives Again

Science.gov (United States)

Paxson, K. B.

2012-06-01

The process of digital archiving for variable star data by manual entry with an Excel spreadsheet is described. Excel-based tools including a Step Magnitude Calculator and a Julian Date Calculator for variable star observations where magnitudes and Julian dates have not been reduced are presented. Variable star data in the literature and the AAVSO International Database prior to 1911 are presented and reviewed, with recent archiving work being highlighted. Digitization using optical character recognition software conversion is also demonstrated, with editing and formatting suggestions for the OCR-converted text.

Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

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MORARIU, N.

2007-04-01

Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

A Survey of 2D Face Recognition Techniques

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Mejda Chihaoui

2016-09-01

Full Text Available Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as hand geometry, the most efficient and more widely-used one is face recognition. This is because it is inexpensive, non-intrusive and natural. Therefore, researchers have developed dozens of face recognition techniques over the last few years. These techniques can generally be divided into three categories, based on the face data processing methodology. There are methods that use the entire face as input data for the proposed recognition system, methods that do not consider the whole face, but only some features or areas of the face and methods that use global and local face characteristics simultaneously. In this paper, we present an overview of some well-known methods in each of these categories. First, we expose the benefits of, as well as the challenges to the use of face recognition as a biometric tool. Then, we present a detailed survey of the well-known methods by expressing each method’s principle. After that, a comparison between the three categories of face recognition techniques is provided. Furthermore, the databases used in face recognition are mentioned, and some results of the applications of these methods on face recognition databases are presented. Finally, we highlight some new promising research directions that have recently appeared.

Collaboration between student art teachers and communication and digital media students promoting subject specific didactics in digital visual learning design

DEFF Research Database (Denmark)

Skov, Kirsten; Buhl, Mie

into account. Our discussion of the potential for developing digital learning application from a collaborative approach is based on the visual design products, interviews and written reports, as well as shared experiences from the stakeholders in the project. Results: The project revealed three digital visual......=pdf Dunleavy, M. & Dede, C. (2014). Augmented reality teaching and learning. in. J.M. Spector, M.D. Merrill, J. Elen & M.J. Bishop (eds), The handbook og research for educational communications and technology New York: Springer http://isites.harvard.edu/fs/docs/icb.topic1116077.files....../DunleavyDedeARfinal.pdf Rasmussen, H. (2015). Digital Picture Production and Picture aesthetic Competency in It-didactic Design. Risk and opportunities for visual arts education in Europe. Proceedings, InSEA conferene, Lisbon, Portugal...

T-ray spectroscopy of biomolecules: from chemical recognition toward biochip analysis - horizons and hurdles

DEFF Research Database (Denmark)

Fischer, Bernd M.; Helm, Hanspeter; Jepsen, Peter Uhd

2006-01-01

In the recent years, there has been an increased interest in the exploitation of the far-infrared spectral region for applications based on chemical recognition. The fact that on the one hand many packaging materials are transparent for THz radiation and on the other hand the THz-spectra of many ...

The Neuropsychology of Familiar Person Recognition from Face and Voice

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Guido Gainotti

2014-05-01

Full Text Available Prosopagnosia has been considered for a long period of time as the most important and almost exclusive disorder in the recognition of familiar people. In recent years, however, this conviction has been undermined by the description of patients showing a concomitant defect in the recognition of familiar faces and voices as a consequence of lesions encroaching upon the right anterior temporal lobe (ATL. These new data have obliged researchers to reconsider on one hand the construct of ‘associative prosopagnosia’ and on the other hand current models of people recognition. A systematic review of the patterns of familiar people recognition disorders observed in patients with right and left ATL lesions has shown that in patients with right ATL lesions face familiarity feelings and the retrieval of person-specific semantic information from faces are selectively affected, whereas in patients with left ATL lesions the defect selectively concerns famous people naming. Furthermore, some patients with right ATL lesions and intact face familiarity feelings show a defect in the retrieval of person-specific semantic knowledge greater from face than from name. These data are at variance with current models assuming: (a that familiarity feelings are generated at the level of person identity nodes (PINs where information processed by various sensory modalities converge, and (b that PINs provide a modality-free gateway to a single semantic system, where information about people is stored in an amodal format. They suggest, on the contrary: (a that familiarity feelings are generated at the level of modality-specific recognition units; (b that face and voice recognition units are represented more in the right than in the left ATLs; (c that in the right ATL are mainly stored person-specific information based on a convergence of perceptual information, whereas in the left ATLs are represented verbally-mediated person-specific information.

Fast digitizing and digital signal processing of detector signals

International Nuclear Information System (INIS)

Hannaske, Roland

2008-01-01

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

Mental rotation of anthropoid hands: a chronometric study

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L.G. Gawryszewski

2007-03-01

Full Text Available It has been shown that mental rotation of objects and human body parts is processed differently in the human brain. But what about body parts belonging to other primates? Does our brain process this information like any other object or does it instead maximize the structural similarities with our homologous body parts? We tried to answer this question by measuring the manual reaction time (MRT of human participants discriminating the handedness of drawings representing the hands of four anthropoid primates (orangutan, chimpanzee, gorilla, and human. Twenty-four right-handed volunteers (13 males and 11 females were instructed to judge the handedness of a hand drawing in palm view by pressing a left/right key. The orientation of hand drawings varied from 0º (fingers upwards to 90º lateral (fingers pointing away from the midline, 180º (fingers downwards and 90º medial (finger towards the midline. The results showed an effect of rotation angle (F(3, 69 = 19.57, P < 0.001, but not of hand identity, on MRTs. Moreover, for all hand drawings, a medial rotation elicited shorter MRTs than a lateral rotation (960 and 1169 ms, respectively, P < 0.05. This result has been previously observed for drawings of the human hand and related to biomechanical constraints of movement performance. Our findings indicate that anthropoid hands are essentially equivalent stimuli for handedness recognition. Since the task involves mentally simulating the posture and rotation of the hands, we wondered if "mirror neurons" could be involved in establishing the motor equivalence between the stimuli and the participants' own hands.

Handwritten Digit Recognition using Edit Distance-Based KNN

OpenAIRE

Bernard , Marc; Fromont , Elisa; Habrard , Amaury; Sebban , Marc

2012-01-01

We discuss the student project given for the last 5 years to the 1st year Master Students which follow the Machine Learning lecture at the University Jean Monnet in Saint Etienne, France. The goal of this project is to develop a GUI that can recognize digits and/or letters drawn manually. The system is based on a string representation of the dig- its using Freeman codes and on the use of an edit-distance-based K-Nearest Neighbors classifier. In addition to the machine learning knowledge about...

Investigations of Hemispheric Specialization of Self-Voice Recognition

Science.gov (United States)

Rosa, Christine; Lassonde, Maryse; Pinard, Claudine; Keenan, Julian Paul; Belin, Pascal

2008-01-01

Three experiments investigated functional asymmetries related to self-recognition in the domain of voices. In Experiment 1, participants were asked to identify one of three presented voices (self, familiar or unknown) by responding with either the right or the left-hand. In Experiment 2, participants were presented with auditory morphs between the…

Grip-pattern recognition: Applied to a smart gun

NARCIS (Netherlands)

Shang, X.

2008-01-01

In our work the verification performance of a biometric recognition system based on grip patterns, as part of a smart gun for use by the police ocers, has been investigated. The biometric features are extracted from a two-dimensional pattern of the pressure, exerted on the grip of a gun by the hand

Evaluating a voice recognition system: finding the right product for your department.

Science.gov (United States)

Freeh, M; Dewey, M; Brigham, L

2001-06-01

The Department of Radiology at the University of Utah Health Sciences Center has been in the process of transitioning from the traditional film-based department to a digital imaging department for the past 2 years. The department is now transitioning from the traditional method of dictating reports (dictation by radiologist to transcription to review and signing by radiologist) to a voice recognition system. The transition to digital operations will not be complete until we have the ability to directly interface the dictation process with the image review process. Voice recognition technology has advanced to the level where it can and should be an integral part of the new way of working in radiology and is an integral part of an efficient digital imaging department. The transition to voice recognition requires the task of identifying the product and the company that will best meet a department's needs. This report introduces the methods we used to evaluate the vendors and the products available as we made our purchasing decision. We discuss our evaluation method and provide a checklist that can be used by other departments to assist with their evaluation process. The criteria used in the evaluation process fall into the following major categories: user operations, technical infrastructure, medical dictionary, system interfaces, service support, cost, and company strength. Conclusions drawn from our evaluation process will be detailed, with the intention being to shorten the process for others as they embark on a similar venture. As more and more organizations investigate the many products and services that are now being offered to enhance the operations of a radiology department, it becomes increasingly important that solid methods are used to most effectively evaluate the new products. This report should help others complete the task of evaluating a voice recognition system and may be adaptable to other products as well.

What Is Digital Labour? What Is Digital Work? What’s their Difference? And Why Do These Questions Matter for Understanding Social Media?

Directory of Open Access Journals (Sweden)

Christian Fuchs

2013-06-01

Full Text Available This paper deals with the questions: What is digital labour? What is digital work? Based on Marx’s theory, we distinguish between work and labour as anthropological and historical forms of human activity. The notion of alienated labour is grounded in a general model of the work process that is conceptualized based on a dialectic of subject and object in the economy that we present in the form of a model, the Hegelian-Marxist dialectical triangle of the work process. Various aspects of a Marxist theory of work and labour, such as the notions of abstract and concrete labour, double-free labour, productive labour, the collective worker and general work are presented. Labour is based on a fourfold alienation of the human being. After these concepts are introduced, they are used for discussing the notions of digital labour and digital work. The presentation is on the one hand general and on the other hand uses Facebook as a concrete case for explaining how digital labour functions. Digital work is the organisation of human experiences with the help of the human brain, digital media and speech in such a way that new products are created. Digital labour is the valorisation dimension of digital work. We conclude that we require the transformation of digital labour into digital work, a true social media revolution that makes “social media” truly and fully social. We also argue why in our view work is not the same as labour by discussing the concept of playful work and pointing out limits of concepts such as antiwork, postwork and zerowork.

Interactive Digital Narratives for iTV and Online Video

NARCIS (Netherlands)

Koenitz, H.; Knoller, N.; Nakatsu, R.; Rauterberg, M.; Ciancarini, P.

2015-01-01

In iTV and online video, narrative interaction has long been a Holy Grail for both audiences and creators of these digital audiovisual works. On the one hand, interactive digital narrative promises interactors some exciting opportunities: to enter the world of the story, to affect the story and

New technique for real-time distortion-invariant multiobject recognition and classification

Science.gov (United States)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

Media identities and media-influenced indentifications Visibility and identity recognition in the media

Directory of Open Access Journals (Sweden)

Víctor Fco. Sampedro Blanco

2004-10-01

Full Text Available The media establish, in large part, the patterns of visibility and public recognition of collective identities. We define media identities as those that are the object of production and diffusion by the media. From this discourse, the communities and individuals elaborate media-influenced identifications; that is, processes of recognition or banishment; (rearticulating the identity markers that the media offer with other cognitive and emotional sources. The generation and appropriation of the identities are subjected to a media hierarchisation that influences their normalisation or marginalisation. The identities presented by the media and assumed by the audience as part of the official, hegemonic discourse are normalised, whereas the identities and identifications formulated in popular and minority terms are marginalised. After presenting this conceptual and analytical framework, this study attempts to outline the logics that condition the presentation, on the one hand, andthe public recognition, on the other hand, of contemporary identities.

Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices

Directory of Open Access Journals (Sweden)

Xuemiao Xu

2015-02-01

Full Text Available We propose a novel biometric recognition method that identifies the inner knuckle print (IKP. It is robust enough to confront uncontrolled lighting conditions, pose variations and low imaging quality. Such robustness is crucial for its application on portable devices equipped with consumer-level cameras. We achieve this robustness by two means. First, we propose a novel feature extraction scheme that highlights the salient structure and suppresses incorrect and/or unwanted features. The extracted IKP features retain simple geometry and morphology and reduce the interference of illumination. Second, to counteract the deformation induced by different hand orientations, we propose a novel structure-context descriptor based on local statistics. To our best knowledge, we are the first to simultaneously consider the illumination invariance and deformation tolerance for appearance-based low-resolution hand biometrics. Settings in previous works are more restrictive. They made strong assumptions either about the illumination condition or the restrictive hand orientation. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods in terms of recognition accuracy, especially under uncontrolled lighting conditions and the flexible hand orientation requirement.

Kinesthetic sensitivity and related measures of hand sensitivity in children with nonproficient handwriting.

Science.gov (United States)

Brink, Anne O'Leary; Jacobs, Anne Burleigh

2011-01-01

This study compared measures of hand sensitivity and handwriting quality in children aged 10 to 12 years identified by their teachers as having nonproficient or proficient handwriting. We hypothesized that children with nonproficient handwriting have decreased kinesthetic sensitivity of the hands and digits. Sixteen subjects without documented motor or cognitive concerns were tested for kinesthetic sensitivity, discriminate tactile awareness, diadochokinesia, stereognosis, and graphesthesia. Eight children were considered to have nonproficient handwriting; 8 had proficient handwriting. Nonparametric Mann-Whitney U tests were used to identify differences between groups on sensory tests. The 2 groups showed a statistically significant difference in handwriting legibility (P = .018). No significant difference was found on tests of kinesthetic sensitivity or other measures of sensation. Children presenting with handwriting difficulty as the only complaint have similar sensitivity in hands and digits as those with proficient handwriting. Failure to detect differences may result from a small sample size.

Virtual Control of Prosthetic Hand Based on Grasping Patterns and Estimated Force from Semg

Directory of Open Access Journals (Sweden)

Zhu Gao-Ke

2016-01-01

Full Text Available Myoelectric prosthetic hands aim to serve upper limb amputees. The myoelectric control of the hand grasp action is a kind of real-time or online method. Thus it is of great necessity to carry on a study of online prosthetic hand electrical control. In this paper, the strategy of simultaneous EMG decoding of grasping patterns and grasping force was realized by controlling a virtual multi-degree-freedom prosthetic hand and a real one-degree-freedom prosthetic hand simultaneously. The former realized the grasping patterns from the recognition of the sEMG pattern. The other implemented the grasping force from sEMG force decoding. The results show that the control method is effective and feasible.

Hand hygiene in the intensive care unit.

Science.gov (United States)

Tschudin-Sutter, Sarah; Pargger, Hans; Widmer, Andreas F

2010-08-01

Healthcare-associated infections affect 1.4 million patients at any time worldwide, as estimated by the World Health Organization. In intensive care units, the burden of healthcare-associated infections is greatly increased, causing additional morbidity and mortality. Multidrug-resistant pathogens are commonly involved in such infections and render effective treatment challenging. Proper hand hygiene is the single most important, simplest, and least expensive means of preventing healthcare-associated infections. In addition, it is equally important to stop transmission of multidrug-resistant pathogens. According to the Centers for Disease Control and Prevention and World Health Organization guidelines on hand hygiene in health care, alcohol-based handrub should be used as the preferred means for routine hand antisepsis. Alcohols have excellent in vitro activity against Gram-positive and Gram-negative bacteria, including multidrug-resistant pathogens, such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci, Mycobacterium tuberculosis, a variety of fungi, and most viruses. Some pathogens, however, such as Clostridium difficile, Bacillus anthracis, and noroviruses, may require special hand hygiene measures. Failure to provide user friendliness of hand hygiene equipment and shortage of staff are predictors for noncompliance, especially in the intensive care unit setting. Therefore, practical approaches to promote hand hygiene in the intensive care unit include provision of a minimal number of handrub dispensers per bed, monitoring of compliance, and choice of the most attractive product. Lack of knowledge of guidelines for hand hygiene, lack of recognition of hand hygiene opportunities during patient care, and lack of awareness of the risk of cross-transmission of pathogens are barriers to good hand hygiene practices. Multidisciplinary programs to promote increased use of alcoholic handrub lead to an increased compliance of healthcare

Why is digit ratio correlated to sports performance?

Science.gov (United States)

Kim, Tae Beom; Kim, Khae Hawn

2016-12-01

Second to fourth digit ratio is the ratio of second to fourth digit length. It has been known that digit ratio is sexually dimorphic in humans, such that males tend to have lower digit ratio (longer fourth digits relative to second digits) than females. Digit ratio is thought to be a biomarker of the balance between fetal testosterone (FT) and fetal estrogen (FE) in a relatively narrow developmental window at the end of the first trimester of pregnancy. On the contrary, the relationships between digit ratio and levels of sex steroids in adults are not clear. Most correlational studies between digit ratio and adult sex steroids have revealed that this association is statistically not significant. However, for many years, a lot of researches showed negative relationships between digit ratio and sports performance such as rugby, surfing, rowing, sprinting, endurance, and hand grip strength. Here, we discuss possible mechanisms about the relationships between digit ratio and sports performance.

Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.

Science.gov (United States)

Kutafina, Ekaterina; Laukamp, David; Bettermann, Ralf; Schroeder, Ulrik; Jonas, Stephan M

2016-08-03

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98 . 30 % ( ± 1 . 26 % ) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

Science.gov (United States)

Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

An analysis of whorl patterns for determination of hand.

Science.gov (United States)

Kapoor, Neeti; Badiye, Ashish

2015-05-01

On crime scenes, whole set of the ten digit fingerprints are rarely found and usually chance prints in the form of single digit fingerprint are encountered. Determination of hand (Right or left) can be of vital importance to reduce the burden on the investigator and may thereby aid in fixation of absolute identity of the donor. In the present investigation, 500 randomly selected and bilateral rolled fingerprints of 250 healthy, consenting adult subjects of a central Indian (Marathi) population with whorl patterns were examined to determine the hand. It was found that by studying various parameters like; slope of apex ridges (towards right, left or absent), rotation of innermost ridges (either clockwise, anti-clockwise or absent), angle formed at both sides of core, position of the perpendicular bisector on the delta line (with respect to core), ridge tracing (outer, inner or meeting), higher ridge count, angle between deltas and core (at deltas), direction of the pattern (tilting/inclination) and distance between the deltas & the core; it is possible to successfully determine the hand of the print. Applying chi-square test, the results were found to be statistically significant at p < 0.01 levels. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Real-Time Multiview Recognition of Human Gestures by Distributed Image Processing

Directory of Open Access Journals (Sweden)

Sato Kosuke

2010-01-01

Full Text Available Since a gesture involves a dynamic and complex motion, multiview observation and recognition are desirable. For the better representation of gestures, one needs to know, in the first place, from which views a gesture should be observed. Furthermore, it becomes increasingly important how the recognition results are integrated when larger numbers of camera views are considered. To investigate these problems, we propose a framework under which multiview recognition is carried out, and an integration scheme by which the recognition results are integrated online and in realtime. For performance evaluation, we use the ViHASi (Virtual Human Action Silhouette public image database as a benchmark and our Japanese sign language (JSL image database that contains 18 kinds of hand signs. By examining the recognition rates of each gesture for each view, we found gestures that exhibit view dependency and the gestures that do not. Also, we found that the view dependency itself could vary depending on the target gesture sets. By integrating the recognition results of different views, our swarm-based integration provides more robust and better recognition performance than individual fixed-view recognition agents.

Illumination-invariant face recognition with a contrast sensitive silicon retina

Energy Technology Data Exchange (ETDEWEB)

Buhmann, J.M. [Rheinische Friedrich-Wilhelms-Univ., Bonn (Germany). Inst. fuer Informatik II; Lades, M. [Bochum Univ. (Germany). Inst. fuer Neuroinformatik; Eeckman, F. [Lawrence Livermore National Lab., CA (United States)

1993-11-29

Changes in lighting conditions strongly effect the performance and reliability of computer vision systems. We report face recognition results under drastically changing lighting conditions for a computer vision system which concurrently uses a contrast sensitive silicon retina and a conventional, gain controlled CCD camera. For both input devices the face recognition system employs an elastic matching algorithm with wavelet based features to classify unknown faces. To assess the effect of analog on-chip preprocessing by the silicon retina the CCD images have been digitally preprocessed with a bandpass filter to adjust the power spectrum. The silicon retina with its ability to adjust sensitivity increases the recognition rate up to 50 percent. These comparative experiments demonstrate that preprocessing with an analog VLSI silicon retina generates image data enriched with object-constant features.

Morphological Processing during Visual Word Recognition in Hebrew as a First and a Second Language

Science.gov (United States)

Norman, Tal; Degani, Tamar; Peleg, Orna

2017-01-01

The present study examined whether sublexical morphological processing takes place during visual word-recognition in Hebrew, and whether morphological decomposition of written words depends on lexical activation of the complete word. Furthermore, it examined whether morphological processing is similar when reading Hebrew as a first language (L1)…

Digital Communication and Modulation

DEFF Research Database (Denmark)

Sørensen, John Aasted

2011-01-01

system. Having passed the course, the student will be able to accomplish the following, within the areas shown below: Model for Communication System. Prepare and explain the functional block in a digital communication system, corresponding to the specific course contents. Model for Communication Channel...... system.   Sessions in class with active participation by the students. The time will be divided between lectures and the students solving problems, including simulating digital communication building blocks in Matlab. Combines lectures and hands-on work. Semester: E2011 Extent: 7.5 ects......, the fundamental principles for modulation and detection in Gaussian noise is treated. This includes the principles for the determination of the bit-error rate for a digital communication system. During the course, a selection of small Matlab exercises are prepared, for simulation of parts of a communication...

Digital Communication and Modulation

DEFF Research Database (Denmark)

Sørensen, John Aasted

2011-01-01

system. Having passed the course, the student will be able to accomplish the following, within the areas shown below: Model for Communication System. Prepare and explain the functional block in a digital communication system, corresponding to the specific course contents. Model for Communication Channel...... system. Sessions in class with active participation by the students. The time will be divided between lectures and the students solving problems, including simulating digital communication building blocks in Matlab. Combines lectures and hands-on work. Semester: F2011 Extent: 7.5 ects......, the fundamental principles for modulation and detection in Gaussian noise is treated. This includes the principles for the determination of the bit-error rate for a digital communication system. During the course, a selection of small Matlab exercises are prepared, for simulation of parts of a communication...

Contactless and pose invariant biometric identification using hand surface.

Science.gov (United States)

Kanhangad, Vivek; Kumar, Ajay; Zhang, David

2011-05-01

This paper presents a novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations. The proposed method utilizes a 3-D digitizer to simultaneously acquire intensity and range images of the user's hand presented to the system in an arbitrary pose. The approach involves determination of the orientation of the hand in 3-D space followed by pose normalization of the acquired 3-D and 2-D hand images. Multimodal (2-D as well as 3-D) palmprint and hand geometry features, which are simultaneously extracted from the user's pose normalized textured 3-D hand, are used for matching. Individual matching scores are then combined using a new dynamic fusion strategy. Our experimental results on the database of 114 subjects with significant pose variations yielded encouraging results. Consistent (across various hand features considered) performance improvement achieved with the pose correction demonstrates the usefulness of the proposed approach for hand based biometric systems with unconstrained and contact-free imaging. The experimental results also suggest that the dynamic fusion approach employed in this work helps to achieve performance improvement of 60% (in terms of EER) over the case when matching scores are combined using the weighted sum rule.

Study of resolution and linearity in LaBr3: Ce scintillator through digital-pulse processing

International Nuclear Information System (INIS)

Abhinav Kumar; Mishra, Gaurav; Ramachandran, K.

2014-01-01

Advent of digital pulse processing has led to a paradigm shift in pulse processing techniques by replacing analog electronics processing chain with equivalent algorithms acting on pulse profiles digitized at high sampling rates. In this paper, we have carried out offline digital pulse processing of Cerium-doped Lanthanum bromide scintillator (LaBr 3 : Ce) detector pulses, acquired using CAEN V1742 VME digitizer module. Algorithms have been written to approximate the functioning of peak sensing analog-to-digital convertor (ADC) and charge-to-digital convertor (QDC). Energy dependence of resolution and energy linearity of LaBr 3 : Ce scintillator detector has been studied by utilizing aforesaid algorithms

sEMG-Based Gesture Recognition with Convolution Neural Networks

Directory of Open Access Journals (Sweden)

Zhen Ding

2018-06-01

Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

Digital color imaging

CERN Document Server

Fernandez-Maloigne, Christine; Macaire, Ludovic

2013-01-01

This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images.For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing.It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. <

Enhancing global positioning by image recognition

OpenAIRE

Marimon Sanjuan, David; Adamek, Tomasz; Bonnin, Arturo; Trzcinski, Tomasz

2011-01-01

Current commercial outdoor Mobile AR applications rely mostly on GPS antennas, digital compasses and accelerometers. Due to imprecise readings, the 2D placement of points of interest (POI) on the display can be uncorrelated with reality. We present a novel method to geo-locate a mobile device by rec- ognizing what is captured by its camera. A visual recognition algo- rithm in the cloud is used to identify geo-located reference images that match the camera’s view. Upon correct identification, ...

High-Pressure Injection Injuries to the Hand

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Davod Jafari

2016-07-01

Full Text Available Background High-pressure injections into the hand, burden devastating and permanent functional impairments. Many materials including paint, paint thinner, gasoline, oil and grease are reported as the causative agents. These injuries need multiple procedures and reconstructions most of the time and 40% of the injuries may end with amputation of the injured part. Objectives The aim of this study was to report the treatment outcomes and methods of treatments of patients with high-pressure injection injuries of the hand. Methods We retrospectively reviewed the medical records, imaging files and demographic data of patients, who were treated at our center due to the high-pressure injuries to their hands. We recorded the kind of the injected materials, time to the first treatment procedure, times of operation, and methods of their treatments. The outcomes of the injuries as well as the deficiency of the digital joints motion were also reported. Results Nine cases with high-pressure injury of the hand were enrolled in this study. All patients were male with mean age of 26.88 ± 7.52. Mean follow-up time was 28.55 ± 12.49 months. The dominant hand was the right side in seven patients and left in two patients. Injury was in the left hand of seven patients and right hand of two patients. Index finger was the most common involved part (five cases followed by the thumb (two cases. Injected material was grease in seven cases, water-base paint and water, each in one case.Mean time delay to the first treatment procedure was 29.16 ± 25.66 hours for seven patients. This was exceptionally long for two patients (seven days and 24 months. Type of treatment was debridement and skin graft for three cases, debridement and cross finger flap for two cases, debridement for two cases and nerve graft for one case. Amputation of the necrotic digit was performed for one case. Mean hospitalization time was 8.33 ± 3.64 days for all patients.Mean total active range of motion

Three-to Four-Year-Olds' Recognition That Symbols Have a Stable Meaning: Pictures Are Understood Before Written Words

Science.gov (United States)

Apperly, Ian. A.; Williams, Emily; Williams, Joelle

2004-01-01

In 4 experiments 120 three-to four-year-old non readers were asked the identity of a symbolic representation as it appeared with different objects. Consistent with Bialystok (2000), many children judged the identity of written words to vary according to the object with which they appeared but few made such errors with recognizable pictures.…

MEDIA INDUSTRY IN THE DIGITAL WORLD

OpenAIRE

Daniel Burtic

2014-01-01

The development of the internet and the expansion of digitalization changed the way society works, especially mass-media. The question is if the internet was an advantage or a disadvantage for mass-media? Apparently, on one hand digitalization determined the reduction of production and distribution costs but also content diversification. At the same time, social media and rapid documentation brought an accession in the quality of journalistic product as well as the entering on the market of m...

Real-time intelligent pattern recognition algorithm for surface EMG signals

Directory of Open Access Journals (Sweden)

Jahed Mehran

2007-12-01

Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

Automated Categorization Scheme for Digital Libraries in Distance Learning: A Pattern Recognition Approach

Science.gov (United States)

Gunal, Serkan

2008-01-01

Digital libraries play a crucial role in distance learning. Nowadays, they are one of the fundamental information sources for the students enrolled in this learning system. These libraries contain huge amount of instructional data (text, audio and video) offered by the distance learning program. Organization of the digital libraries is…

Anti Theft Mechanism Through Face recognition Using FPGA

Science.gov (United States)

Sundari, Y. B. T.; Laxminarayana, G.; Laxmi, G. Vijaya

2012-11-01

The use of vehicle is must for everyone. At the same time, protection from theft is also very important. Prevention of vehicle theft can be done remotely by an authorized person. The location of the car can be found by using GPS and GSM controlled by FPGA. In this paper, face recognition is used to identify the persons and comparison is done with the preloaded faces for authorization. The vehicle will start only when the authorized personís face is identified. In the event of theft attempt or unauthorized personís trial to drive the vehicle, an MMS/SMS will be sent to the owner along with the location. Then the authorized person can alert the security personnel for tracking and catching the vehicle. For face recognition, a Principal Component Analysis (PCA) algorithm is developed using MATLAB. The control technique for GPS and GSM is developed using VHDL over SPTRAN 3E FPGA. The MMS sending method is written in VB6.0. The proposed application can be implemented with some modifications in the systems wherever the face recognition or detection is needed like, airports, international borders, banking applications etc.

"Digit anatomy": a new technique for learning anatomy using motor memory.

Science.gov (United States)

Oh, Chang-Seok; Won, Hyung-Sun; Kim, Kyong-Jee; Jang, Dong-Su

2011-01-01

Gestural motions of the hands and fingers are powerful tools for expressing meanings and concepts, and the nervous system has the capacity to retain multiple long-term motor memories, especially including movements of the hands. We developed many sets of successive movements of both hands, referred to as "digit anatomy," and made students practice the movements which express (1) the aortic arch, subclavian, and thoracoacromial arteries and their branches, (2) the celiac trunk, superior mesenteric artery and their branches, and formation of the portal vein, (3) the heart and the coronary arteries, and (4) the brachial, lumbar, and sacral plexuses. A feedback survey showed that digit anatomy was helpful for the students not only in memorizing anatomical structures but also in understanding their functions. Out of 40 students, 34 of them who learned anatomy with the help of digit anatomy were "very satisfied" or "generally satisfied" with this new teaching method. Digit anatomy that was used to express the aortic arch, subclavian, and thoracoacromial arteries and their branches was more helpful than those representing other structures. Although the movements of digit anatomy are expected to be remembered longer than the exact meaning of each movement, invoking the motor memory of the movement may help to make relearning of the same information easier and faster in the future. Copyright © 2011 American Association of Anatomists.

Random number generation based on digital differential chaos

KAUST Repository

Zidan, Mohammed A.

2012-07-29

In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing technique to improve the distribution and statistical properties of the generated data. The post-processed output passes the NIST Sp. 800-22 statistical tests. The system is written in Verilog VHDL and realized on Xilinx Virtex® FPGA. The generator can fit into a very small area and have a maximum throughput of 2.1 Gb/s.