Cai, Wei; He, Baochun; Fang, Chihua
2016-01-01
This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods— one interactive method, an in‐house‐developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)‐based segmentation, and one automatic probabilistic atlas (PA)‐guided segmentation method on clinical contrast‐enhanced CT images. Forty‐two datasets, including 27 normal liver and 15 space‐occupying liver lesion patients, were retrospectively included in this study. The three methods — one semiautomatic 3DMIA, one automatic ASM‐based, and one automatic PA‐based liver volumetry — achieved an accuracy with VD (volume difference) of −1.69%,−2.75%, and 3.06% in the normal group, respectively, and with VD of −3.20%,−3.35%, and 4.14% in the space‐occupying lesion group, respectively. However, the three methods achieved an efficiency of 27.63 mins, 1.26 mins, 1.18 mins on average, respectively, compared with the manual volumetry, which took 43.98 mins. The high intraclass correlation coefficient between the three methods and the manual method indicated an excellent agreement on liver volumetry. Significant differences in segmentation time were observed between the three methods (3DMIA, ASM, and PA) and the manual volumetry (p<0.001), as well as between the automatic volumetries (ASM and PA) and the semiautomatic volumetry (3DMIA) (p<0.001). The semiautomatic interactive 3DMIA, automatic ASM‐based, and automatic PA‐based liver volumetry agreed well with manual gold standard in both the normal liver group and the space‐occupying lesion group. The ASM‐ and PA‐based automatic segmentation have better efficiency in clinical use. PACS number(s): 87.55.‐x PMID:27929487
Cai, Wei; He, Baochun; Fan, Yingfang; Fang, Chihua; Jia, Fucang
2016-11-08
This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods- one interactive method, an in-house-developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)-based segmentation, and one automatic probabilistic atlas (PA)-guided segmentation method on clinical contrast-enhanced CT images. Forty-two datasets, including 27 normal liver and 15 space-occupying liver lesion patients, were retrospectively included in this study. The three methods - one semiautomatic 3DMIA, one automatic ASM-based, and one automatic PA-based liver volumetry - achieved an accuracy with VD (volume difference) of -1.69%, -2.75%, and 3.06% in the normal group, respectively, and with VD of -3.20%, -3.35%, and 4.14% in the space-occupying lesion group, respectively. However, the three methods achieved an efficiency of 27.63 mins, 1.26 mins, 1.18 mins on average, respectively, compared with the manual volumetry, which took 43.98 mins. The high intraclass correlation coefficient between the three methods and the manual method indicated an excel-lent agreement on liver volumetry. Significant differences in segmentation time were observed between the three methods (3DMIA, ASM, and PA) and the manual volumetry (p < 0.001), as well as between the automatic volumetries (ASM and PA) and the semiautomatic volumetry (3DMIA) (p < 0.001). The semiautomatic interactive 3DMIA, automatic ASM-based, and automatic PA-based liver volum-etry agreed well with manual gold standard in both the normal liver group and the space-occupying lesion group. The ASM- and PA-based automatic segmentation have better efficiency in clinical use. © 2016 The Authors.
Stefanidis, Dimitrios; Scerbo, Mark W; Montero, Paul N; Acker, Christina E; Smith, Warren D
2012-01-01
We hypothesized that novices will perform better in the operating room after simulator training to automaticity compared with traditional proficiency based training (current standard training paradigm). Simulator-acquired skill translates to the operating room, but the skill transfer is incomplete. Secondary task metrics reflect the ability of trainees to multitask (automaticity) and may improve performance assessment on simulators and skill transfer by indicating when learning is complete. Novices (N = 30) were enrolled in an IRB-approved, blinded, randomized, controlled trial. Participants were randomized into an intervention (n = 20) and a control (n = 10) group. The intervention group practiced on the FLS suturing task until they achieved expert levels of time and errors (proficiency), were tested on a live porcine fundoplication model, continued simulator training until they achieved expert levels on a visual spatial secondary task (automaticity) and were retested on the operating room (OR) model. The control group participated only during testing sessions. Performance scores were compared within and between groups during testing sessions. : Intervention group participants achieved proficiency after 54 ± 14 and automaticity after additional 109 ± 57 repetitions. Participants achieved better scores in the OR after automaticity training [345 (range, 0-537)] compared with after proficiency-based training [220 (range, 0-452; P < 0.001]. Simulator training to automaticity takes more time but is superior to proficiency-based training, as it leads to improved skill acquisition and transfer. Secondary task metrics that reflect trainee automaticity should be implemented during simulator training to improve learning and skill transfer.
Efrati, Shai; Bolotin, Gil; Levi, Leon; Zaaroor, Menashe; Guralnik, Ludmila; Weksler, Natan; Levinger, Uriel; Soroksky, Arie; Denman, William T; Gurman, Gabriel M
2017-10-01
Many of the complications of mechanical ventilation are related to inappropriate endotracheal tube (ETT) cuff pressure. The aim of the current study was to evaluate the effectiveness of automatic cuff pressure closed-loop control in patients under prolonged intubation, where presence of carbon dioxide (CO2) in the subglottic space is used as an indicator for leaks. The primary outcome of the study is leakage around the cuff quantified using the area under the curve (AUC) of CO2 leakage over time. This was a multicenter, prospective, randomized controlled, noninferiority trial including intensive care unit patients. All patients were intubated with the AnapnoGuard ETT, which has an extra lumen used to monitor CO2 levels in the subglottic space.The study group was connected to the AnapnoGuard system operating with cuff control adjusted automatically based on subglottic CO2 (automatic group). The control group was connected to the AnapnoGuard system, while cuff pressure was managed manually using a manometer 3 times/d (manual group). The system recorded around cuff CO2 leakage in both groups. Seventy-two patients were recruited and 64 included in the final analysis. The mean hourly around cuff CO2 leak (mm Hg AUC/h) was 0.22 ± 0.32 in the manual group and 0.09 ± 0.04 in the automatic group (P = .01) where the lower bound of the 1-sided 95% confidence interval was 0.05, demonstrating noninferiority (>-0.033). Additionally, the 2-sided 95% confidence interval was 0.010 to 0.196, showing superiority (>0.0) as well. Significant CO2 leakage (CO2 >2 mm Hg) was 0.027 ± 0.057 (mm Hg AUC/h) in the automatic group versus 0.296 ± 0.784 (mm Hg AUC/h) in the manual group (P = .025). In addition, cuff pressures were in the predefined safety range 97.6% of the time in the automatic group compared to 48.2% in the automatic group (P < .001). This study shows that the automatic cuff pressure group is not only noninferior but also superior compared to the manual cuff pressure group. Thus, the use of automatic cuff pressure control based on subglottic measurements of CO2 levels is an effective method for ETT cuff pressure optimization. The method is safe and can be easily utilized with any intubated patient.
ERIC Educational Resources Information Center
Jones, Daniel; Alexa, Melina
As part of the development of a completely sub-symbolic machine translation system, a method for automatically identifying German compounds was developed. Given a parallel bilingual corpus, German compounds are identified along with their English word groupings by statistical processing alone. The underlying principles and the design process are…
Automatic identification of abstract online groups
Engel, David W; Gregory, Michelle L; Bell, Eric B; Cowell, Andrew J; Piatt, Andrew W
2014-04-15
Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.
Microprocessor-controlled hemodynamics: a step towards improved efficiency and safety.
Keogh, B E; Jacobs, J; Royston, D; Taylor, K M
1989-02-01
Manual titration of sodium nitroprusside (SNP) is widely used for treatment of hypertension following cardiac surgery. This study compared conventional manual control with control by a research prototype of an automatic infusion module based on a proportional plus integral plus derivative (PID) negative feedback loop. Two groups of coronary artery bypass patients requiring SNP for postoperative hypertension were studied prospectively. In the first group, hypertension was controlled by manual adjustment of the SNP infusion rate, and in the second, the infusion rate was controlled automatically. The actual and desired mean arterial pressures (MAP) over consecutive ten-second epochs were recorded during the period of infusion. The MAP was maintained within 10% of the desired MAP 45.8% of the time in the manual group, compared with 90.0% in the automatic group, and the mean percent error in the automatic group was significantly less than in the manual group (P less than 0.01). It is concluded that adoption of such systems will result in improved patient safety and may facilitate more effective distribution of nursing staff within intensive care units.
Automatic feature-based grouping during multiple object tracking.
Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J
2013-12-01
Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.
Preservation of memory-based automaticity in reading for older adults.
Rawson, Katherine A; Touron, Dayna R
2015-12-01
Concerning age-related effects on cognitive skill acquisition, the modal finding is that older adults do not benefit from practice to the same extent as younger adults in tasks that afford a shift from slower algorithmic processing to faster memory-based processing. In contrast, Rawson and Touron (2009) demonstrated a relatively rapid shift to memory-based processing in the context of a reading task. The current research extended beyond this initial study to provide more definitive evidence for relative preservation of memory-based automaticity in reading tasks for older adults. Younger and older adults read short stories containing unfamiliar noun phrases (e.g., skunk mud) followed by disambiguating information indicating the combination's meaning (either the normatively dominant meaning or an alternative subordinate meaning). Stories were repeated across practice blocks, and then the noun phrases were presented in novel sentence frames in a transfer task. Both age groups shifted from computation to retrieval after relatively few practice trials (as evidenced by convergence of reading times for dominant and subordinate items). Most important, both age groups showed strong evidence for memory-based processing of the noun phrases in the transfer task. In contrast, older adults showed minimal shifting to retrieval in an alphabet arithmetic task, indicating that the preservation of memory-based automaticity in reading was task-specific. Discussion focuses on important implications for theories of memory-based automaticity in general and for specific theoretical accounts of age effects on memory-based automaticity, as well as fruitful directions for future research. (c) 2015 APA, all rights reserved).
Higgins, Eleanor L; Raskind, Marshall H
2004-12-01
This study was conducted to assess the effectiveness of two programs developed by the Frostig Center Research Department to improve the reading and spelling of students with learning disabilities (LD): a computer Speech Recognition-based Program (SRBP) and a computer and text-based Automaticity Program (AP). Twenty-eight LD students with reading and spelling difficulties (aged 8 to 18) received each program for 17 weeks and were compared with 16 students in a contrast group who did not receive either program. After adjusting for age and IQ, both the SRBP and AP groups showed significant differences over the contrast group in improving word recognition and reading comprehension. Neither program showed significant differences over contrasts in spelling. The SRBP also improved the performance of the target group when compared with the contrast group on phonological elision and nonword reading efficiency tasks. The AP showed significant differences in all process and reading efficiency measures.
Validation of automatic segmentation of ribs for NTCP modeling.
Stam, Barbara; Peulen, Heike; Rossi, Maddalena M G; Belderbos, José S A; Sonke, Jan-Jakob
2016-03-01
Determination of a dose-effect relation for rib fractures in a large patient group has been limited by the time consuming manual delineation of ribs. Automatic segmentation could facilitate such an analysis. We determine the accuracy of automatic rib segmentation in the context of normal tissue complication probability modeling (NTCP). Forty-one patients with stage I/II non-small cell lung cancer treated with SBRT to 54 Gy in 3 fractions were selected. Using the 4DCT derived mid-ventilation planning CT, all ribs were manually contoured and automatically segmented. Accuracy of segmentation was assessed using volumetric, shape and dosimetric measures. Manual and automatic dosimetric parameters Dx and EUD were tested for equivalence using the Two One-Sided T-test (TOST), and assessed for agreement using Bland-Altman analysis. NTCP models based on manual and automatic segmentation were compared. Automatic segmentation was comparable with the manual delineation in radial direction, but larger near the costal cartilage and vertebrae. Manual and automatic Dx and EUD were significantly equivalent. The Bland-Altman analysis showed good agreement. The two NTCP models were very similar. Automatic rib segmentation was significantly equivalent to manual delineation and can be used for NTCP modeling in a large patient group. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Ding, Aimin; Cao, Huling; Wang, Lihua; Chen, Jiangang; Wang, Jian; He, Bosheng
2016-12-01
Benign prostatic hyperplasia is a common progressive disease in aging men, which leads to a significant impact on daily lives of patients. Continuous bladder irrigation (CBI) is a supplementary option for preventing the adverse events following transurethral resection of the prostate (TURP). Regulation of the flow rate based on the color of drainage bag is significant to prevent the clot formation and retention, which is controlled manually at present. To achieve a better control of flow rate and reduce inappropriate flow rate-related adverse effects, we designed an automatic flow rate controller for CBI applied with wireless sensor and evaluated its clinical efficacy. The therapeutic efficacy was evaluated in patients receiving the novel automatic bladder irrigation post-TURP in the experimental group compared with controls receiving traditional bladder irrigation in the control group. A total of 146 patients were randomly divided into 2 groups-the experimental group (n = 76) and the control group (n = 70). The mean irrigation volume of the experimental group (24.2 ± 3.8 L) was significantly lower than that of the controls (54.6 ± 5.4 L) (P < 0.05). Patients treated with automatic irrigation device had significantly decreased incidence of clot retention (8/76) and cystospasm (12/76) compared to controls (21/70; 39/70, P < 0.05). There was no significant difference between the 2 groups with regard to irrigation time (28.6 ± 2.7 vs 29.5 ± 3.4 hours, P = 0.077). The study suggests that the automatic regulating device applied with wireless sensor for CBI is safe and effective for patients after TURP. However, studies with a large population of patients and a long-term follow-up should be conducted to validate our findings.
Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.
Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo
2016-09-01
In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.
Ding, Aimin; Cao, Huling; Wang, Lihua; Chen, Jiangang; Wang, Jian; He, Bosheng
2016-01-01
Abstract Background: Benign prostatic hyperplasia is a common progressive disease in aging men, which leads to a significant impact on daily lives of patients. Continuous bladder irrigation (CBI) is a supplementary option for preventing the adverse events following transurethral resection of the prostate (TURP). Regulation of the flow rate based on the color of drainage bag is significant to prevent the clot formation and retention, which is controlled manually at present. To achieve a better control of flow rate and reduce inappropriate flow rate–related adverse effects, we designed an automatic flow rate controller for CBI applied with wireless sensor and evaluated its clinical efficacy. Methods: The therapeutic efficacy was evaluated in patients receiving the novel automatic bladder irrigation post-TURP in the experimental group compared with controls receiving traditional bladder irrigation in the control group. Results: A total of 146 patients were randomly divided into 2 groups—the experimental group (n = 76) and the control group (n = 70). The mean irrigation volume of the experimental group (24.2 ± 3.8 L) was significantly lower than that of the controls (54.6 ± 5.4 L) (P < 0.05). Patients treated with automatic irrigation device had significantly decreased incidence of clot retention (8/76) and cystospasm (12/76) compared to controls (21/70; 39/70, P < 0.05). There was no significant difference between the 2 groups with regard to irrigation time (28.6 ± 2.7 vs 29.5 ± 3.4 hours, P = 0.077). Conclusion: The study suggests that the automatic regulating device applied with wireless sensor for CBI is safe and effective for patients after TURP. However, studies with a large population of patients and a long-term follow-up should be conducted to validate our findings. PMID:28033276
Resources monitoring and automatic management system for multi-VO distributed computing system
NASA Astrophysics Data System (ADS)
Chen, J.; Pelevanyuk, I.; Sun, Y.; Zhemchugov, A.; Yan, T.; Zhao, X. H.; Zhang, X. M.
2017-10-01
Multi-VO supports based on DIRAC have been set up to provide workload and data management for several high energy experiments in IHEP. To monitor and manage the heterogeneous resources which belong to different Virtual Organizations in a uniform way, a resources monitoring and automatic management system based on Resource Status System(RSS) of DIRAC has been presented in this paper. The system is composed of three parts: information collection, status decision and automatic control, and information display. The information collection includes active and passive way of gathering status from different sources and stores them in databases. The status decision and automatic control is used to evaluate the resources status and take control actions on resources automatically through some pre-defined policies and actions. The monitoring information is displayed on a web portal. Both the real-time information and historical information can be obtained from the web portal. All the implementations are based on DIRAC framework. The information and control including sites, policies, web portal for different VOs can be well defined and distinguished within DIRAC user and group management infrastructure.
Vision Problems and Reduced Reading Outcomes in Queensland Schoolchildren.
Hopkins, Shelley; Sampson, Geoff P; Hendicott, Peter L; Wood, Joanne M
2017-03-01
To assess the relationship between vision and reading outcomes in Indigenous and non-Indigenous schoolchildren to determine whether vision problems are associated with lower reading outcomes in these populations. Vision testing and reading assessments were performed on 508 Indigenous and non-Indigenous schoolchildren in Queensland, Australia divided into two age groups: Grades 1 and 2 (6-7 years of age) and Grades 6 and 7 (12-13 years of age). Vision parameters measured included cycloplegic refraction, near point of convergence, heterophoria, fusional vergence range, rapid automatized naming, and visual motor integration. The following vision conditions were then classified based on the vision findings: uncorrected hyperopia, convergence insufficiency, reduced rapid automatized naming, and delayed visual motor integration. Reading accuracy and reading comprehension were measured with the Neale reading test. The effect of uncorrected hyperopia, convergence insufficiency, reduced rapid automatized naming, and delayed visual motor integration on reading accuracy and reading comprehension were investigated with ANCOVAs. The ANCOVAs explained a significant proportion of variance in both reading accuracy and reading comprehension scores in both age groups, with 40% of the variation in reading accuracy and 33% of the variation in reading comprehension explained in the younger age group, and 27% and 10% of the variation in reading accuracy and reading comprehension, respectively, in the older age group. The vision parameters of visual motor integration and rapid automatized naming were significant predictors in all ANCOVAs (P < .01). The direction of the relationship was such that reduced reading results were explained by reduced visual motor integration and rapid automatized naming results. Both reduced rapid automatized naming and visual motor integration were associated with poorer reading outcomes in Indigenous and non-Indigenous children. This is an important finding given the recent emphasis placed on Indigenous children's reading skills and the fact that reduced rapid automatized naming and visual motor integration skills are more common in this group.
NASA Astrophysics Data System (ADS)
Dowling, J. A.; Burdett, N.; Greer, P. B.; Sun, J.; Parker, J.; Pichler, P.; Stanwell, P.; Chandra, S.; Rivest-Hénault, D.; Ghose, S.; Salvado, O.; Fripp, J.
2014-03-01
Our group have been developing methods for MRI-alone prostate cancer radiation therapy treatment planning. To assist with clinical validation of the workflow we are investigating a cloud platform solution for research purposes. Benefits of cloud computing can include increased scalability, performance and extensibility while reducing total cost of ownership. In this paper we demonstrate the generation of DICOM-RT directories containing an automatic average atlas based electron density image and fast pelvic organ contouring from whole pelvis MR scans.
Daisne, Jean-François; Blumhofer, Andreas
2013-06-26
Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.
Giersch, Anne; van Assche, Mitsouko; Capa, Rémi L; Marrer, Corinne; Gounot, Daniel
2012-01-01
Looking at a pair of objects is easy when automatic grouping mechanisms bind these objects together, but visual exploration can also be more flexible. It is possible to mentally "re-group" two objects that are not only separate but belong to different pairs of objects. "Re-grouping" is in conflict with automatic grouping, since it entails a separation of each item from the set it belongs to. This ability appears to be impaired in patients with schizophrenia. Here we check if this impairment is selective, which would suggest a dissociation between grouping and "re-grouping," or if it impacts on usual, automatic grouping, which would call for a better understanding of the interactions between automatic grouping and "re-grouping." Sixteen outpatients with schizophrenia and healthy controls had to identify two identical and contiguous target figures within a display of circles and squares alternating around a fixation point. Eye-tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. Identical figures were grouped by a connector (grouped automatically) or not (to be re-grouped). Attention modulation of automatic grouping was tested by manipulating the proportion of connected and unconnected targets, thus prompting subjects to focalize on either connected or unconnected pairs. Both groups were sensitive to automatic grouping in most conditions, but patients were unusually slowed down for connected targets while focalizing on unconnected pairs. In addition, this unusual effect occurred only when targets were presented within the same hemifield. Patients and controls differed on this asymmetry between within- and across-hemifield presentation, suggesting that patients with schizophrenia do not re-group figures in the same way as controls do. We discuss possible implications on how "re-grouping" ties in with ongoing, automatic perception in healthy volunteers.
DELINEATING SUBTYPES OF SELF-INJURIOUS BEHAVIOR MAINTAINED BY AUTOMATIC REINFORCEMENT
Hagopian, Louis P.; Rooker, Griffin W.; Zarcone, Jennifer R.
2016-01-01
Self-injurious behavior (SIB) is maintained by automatic reinforcement in roughly 25% of cases. Automatically reinforced SIB typically has been considered a single functional category, and is less understood than socially reinforced SIB. Subtyping automatically reinforced SIB into functional categories has the potential to guide the development of more targeted interventions and increase our understanding of its biological underpinnings. The current study involved an analysis of 39 individuals with automatically reinforced SIB and a comparison group of 13 individuals with socially reinforced SIB. Automatically reinforced SIB was categorized into 3 subtypes based on patterns of responding in the functional analysis and the presence of self-restraint. These response features were selected as the basis for subtyping on the premise that they could reflect functional properties of SIB unique to each subtype. Analysis of treatment data revealed important differences across subtypes and provides preliminary support to warrant additional research on this proposed subtyping model. PMID:26223959
Giersch, Anne; van Assche, Mitsouko; Capa, Rémi L.; Marrer, Corinne; Gounot, Daniel
2012-01-01
Looking at a pair of objects is easy when automatic grouping mechanisms bind these objects together, but visual exploration can also be more flexible. It is possible to mentally “re-group” two objects that are not only separate but belong to different pairs of objects. “Re-grouping” is in conflict with automatic grouping, since it entails a separation of each item from the set it belongs to. This ability appears to be impaired in patients with schizophrenia. Here we check if this impairment is selective, which would suggest a dissociation between grouping and “re-grouping,” or if it impacts on usual, automatic grouping, which would call for a better understanding of the interactions between automatic grouping and “re-grouping.” Sixteen outpatients with schizophrenia and healthy controls had to identify two identical and contiguous target figures within a display of circles and squares alternating around a fixation point. Eye-tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. Identical figures were grouped by a connector (grouped automatically) or not (to be re-grouped). Attention modulation of automatic grouping was tested by manipulating the proportion of connected and unconnected targets, thus prompting subjects to focalize on either connected or unconnected pairs. Both groups were sensitive to automatic grouping in most conditions, but patients were unusually slowed down for connected targets while focalizing on unconnected pairs. In addition, this unusual effect occurred only when targets were presented within the same hemifield. Patients and controls differed on this asymmetry between within- and across-hemifield presentation, suggesting that patients with schizophrenia do not re-group figures in the same way as controls do. We discuss possible implications on how “re-grouping” ties in with ongoing, automatic perception in healthy volunteers. PMID:22912621
Individual differences in automatic emotion regulation affect the asymmetry of the LPP component.
Zhang, Jing; Zhou, Renlai
2014-01-01
The main goal of this study was to investigate how automatic emotion regulation altered the hemispheric asymmetry of ERPs elicited by emotion processing. We examined the effect of individual differences in automatic emotion regulation on the late positive potential (LPP) when participants were viewing blocks of positive high arousal, positive low arousal, negative high arousal and negative low arousal pictures from International affect picture system (IAPS). Two participant groups were categorized by the Emotion Regulation-Implicit Association Test which has been used in previous research to identify two groups of participants with automatic emotion control and with automatic emotion express. The main finding was that automatic emotion express group showed a right dominance of the LPP component at posterior electrodes, especially in high arousal conditions. But no right dominance of the LPP component was observed for automatic emotion control group. We also found the group with automatic emotion control showed no differences in the right posterior LPP amplitude between high- and low-arousal emotion conditions, while the participants with automatic emotion express showed larger LPP amplitude in the right posterior in high-arousal conditions compared to low-arousal conditions. This result suggested that AER (Automatic emotion regulation) modulated the hemispheric asymmetry of LPP on posterior electrodes and supported the right hemisphere hypothesis.
Does flexibility in perceptual organization compete with automatic grouping?
van Assche, Mitsouko; Gos, Pierre; Giersch, Anne
2012-02-06
Segregated objects can be sought simultaneously, i.e., mentally "re-grouped." Although the mechanisms underlying such "re-grouping" clearly differ from automatic grouping, it is unclear whether or not the end products of "re-grouping" and automatic grouping are the same. If they are, they would have similar impact on visual organization but would be in conflict. We compared the consequences of grouping and re-grouping on the performance cost induced by stimuli presented across hemifields. Two identical and contiguous target figures had to be identified within a display of circles and squares alternating around a fixation point. Eye tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. A large cost of presenting targets across hemifields was observed. Grouping by connectedness yielded two types of target pair, connected and unconnected. Subjects prioritized unconnected pairs efficiently when prompted to do so, suggesting "re-grouping." However, unlike automatic grouping, this did not affect the cost of across-hemifield presentation. The suggestion is that re-grouping yields different outputs to automatic grouping, such that a fresh representation resulting from re-grouping complements the one resulting from automatic grouping but does not replace it. This is one step toward understanding how our mental exploration of the world ties in and coexists with ongoing perception.
Reinecke, Andrea; Waldenmaier, Lara; Cooper, Myra J; Harmer, Catherine J
2013-06-01
Cognitive behavioral therapy (CBT) is an effective treatment for emotional disorders such as anxiety or depression, but the mechanisms underlying successful intervention are far from understood. Although it has been a long-held view that psychopharmacological approaches work by directly targeting automatic emotional information processing in the brain, it is usually postulated that psychological treatments affect these processes only over time, through changes in more conscious thought cycles. This study explored the role of early changes in emotional information processing in CBT action. Twenty-eight untreated patients with panic disorder were randomized to a single session of exposure-based CBT or waiting group. Emotional information processing was measured on the day after intervention with an attentional visual probe task, and clinical symptoms were assessed on the day after intervention and at 4-week follow-up. Vigilance for threat information was decreased in the treated group, compared with the waiting group, the day after intervention, before reductions in clinical symptoms. The magnitude of this early effect on threat vigilance predicted therapeutic response after 4 weeks. Cognitive behavioral therapy rapidly affects automatic processing, and these early effects are predictive of later therapeutic change. Such results suggest very fast action on automatic processes mediating threat sensitivity, and they provide an early marker of treatment response. Furthermore, these findings challenge the notion that psychological treatments work directly on conscious thought processes before automatic information processing and imply a greater similarity between early effects of pharmacological and psychological treatments for anxiety than previously thought. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Automatic control of pressure support for ventilator weaning in surgical intensive care patients.
Schädler, Dirk; Engel, Christoph; Elke, Gunnar; Pulletz, Sven; Haake, Nils; Frerichs, Inéz; Zick, Günther; Scholz, Jens; Weiler, Norbert
2012-03-15
Despite its ability to reduce overall ventilation time, protocol-guided weaning from mechanical ventilation is not routinely used in daily clinical practice. Clinical implementation of weaning protocols could be facilitated by integration of knowledge-based, closed-loop controlled protocols into respirators. To determine whether automated weaning decreases overall ventilation time compared with weaning based on a standardized written protocol in an unselected surgical patient population. In this prospective controlled trial patients ventilated for longer than 9 hours were randomly allocated to receive either weaning with automatic control of pressure support ventilation (automated-weaning group) or weaning based on a standardized written protocol (control group) using the same ventilation mode. The primary end point of the study was overall ventilation time. Overall ventilation time (median [25th and 75th percentile]) did not significantly differ between the automated-weaning (31 [19-101] h; n = 150) and control groups (39 [20-118] h; n = 150; P = 0.178). Patients who underwent cardiac surgery (n = 132) exhibited significantly shorter overall ventilation times in the automated-weaning (24 [18-57] h) than in the control group (35 [20-93] h; P = 0.035). The automated-weaning group exhibited shorter ventilation times until the first spontaneous breathing trial (1 [0-15] vs. 9 [1-51] h; P = 0.001) and a trend toward fewer tracheostomies (17 vs. 28; P = 0.075). Overall ventilation times did not significantly differ between weaning using automatic control of pressure support ventilation and weaning based on a standardized written protocol. Patients after cardiac surgery may benefit from automated weaning. Implementation of additional control variables besides the level of pressure support may further improve automated-weaning systems. Clinical trial registered with www.clinicaltrials.gov (NCT 00445289).
Kliemann, Nathalie; Vickerstaff, Victoria; Croker, Helen; Johnson, Fiona; Nazareth, Irwin; Beeken, Rebecca J
2017-09-05
Habit-interventions are designed to promote the automaticity of healthy behaviours and may also enhance self-regulatory skills during the habit-formation process. A recent trial of habit-based advice for weight loss (10 Top Tips; 10TT), found that patients allocated to 10TT lost significantly more weight over 3 months than those allocated to usual care, and reported greater increases in automaticity for the target behaviours. The current study aimed to test the hypothesis that i) 10TT increased self-regulatory skills more than usual care, and ii) that self-regulatory skills and automaticity changes mediated the effect of 10TT on weight loss. 537 obese patients from 14 primary care practices in the UK were randomized to receive 10TT or usual care. Patients in the 10TT group received a leaflet containing tips for weight loss and healthy habits formation, a self-monitoring log book and a wallet-sized shopping guide on how to read food labels. Patients were weighed and completed validated questionnaires for self-regulation and automaticity at baseline and 3-month follow-up. Within-group and Between-group effects were explored using Paired T-test and ANCOVA, respectively. Mediation was assessed using bootstrapping to estimate indirect effects and the sobel test. Over 3 months patients who were given 10TT reported greater increases in self-regulatory skills (Mean difference: .08; 95% CI .01; .15) than those who received usual care. Changes in self-regulatory skills and automaticity over 3 months mediated the effect of the intervention on weight loss (β = .52, 95% Bias Corrected CI .17; .91). As hypothesised, 10TT enhanced self-regulatory skills and changes in self-regulatory skills and automaticity mediated the effect of the intervention on weight loss. This supports the proposition that self-regulatory training and habit formation are important features of weight loss interventions. This study was prospectively registered with the International Standard Randomised Controlled Trials ( ISRCTN16347068 ) on 26 September 2011.
[Application of automatic photography in Schistosoma japonicum miracidium hatching experiments].
Ming-Li, Zhou; Ai-Ling, Cai; Xue-Feng, Wang
2016-05-20
To explore the value of automatic photography in the observation of results of Schistosoma japonicum miracidium hatching experiments. Some fresh S. japonicum eggs were added into cow feces, and the samples of feces were divided into a low infested experimental group and a high infested group (40 samples each group). In addition, there was a negative control group with 40 samples of cow feces without S. japonicum eggs. The conventional nylon bag S. japonicum miracidium hatching experiments were performed. The process was observed with the method of flashlight and magnifying glass combined with automatic video (automatic photography method), and, at the same time, with the naked eye observation method. The results were compared. In the low infested group, the miracidium positive detection rates were 57.5% and 85.0% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 11.723, P < 0.05). In the high infested group, the positive detection rates were 97.5% and 100% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 1.253, P > 0.05). In the two infested groups, the average positive detection rates were 77.5% and 92.5% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 6.894, P < 0.05). The automatic photography can effectively improve the positive detection rate in the S. japonicum miracidium hatching experiments.
Boudissa, M; Orfeuvre, B; Chabanas, M; Tonetti, J
2017-09-01
The Letournel classification of acetabular fracture shows poor reproducibility in inexperienced observers, despite the introduction of 3D imaging. We therefore developed a method of semi-automatic segmentation based on CT data. The present prospective study aimed to assess: (1) whether semi-automatic bone-fragment segmentation increased the rate of correct classification; (2) if so, in which fracture types; and (3) feasibility using the open-source itksnap 3.0 software package without incurring extra cost for users. Semi-automatic segmentation of acetabular fractures significantly increases the rate of correct classification by orthopedic surgery residents. Twelve orthopedic surgery residents classified 23 acetabular fractures. Six used conventional 3D reconstructions provided by the center's radiology department (conventional group) and 6 others used reconstructions obtained by semi-automatic segmentation using the open-source itksnap 3.0 software package (segmentation group). Bone fragments were identified by specific colors. Correct classification rates were compared between groups on Chi 2 test. Assessment was repeated 2 weeks later, to determine intra-observer reproducibility. Correct classification rates were significantly higher in the "segmentation" group: 114/138 (83%) versus 71/138 (52%); P<0.0001. The difference was greater for simple (36/36 (100%) versus 17/36 (47%); P<0.0001) than complex fractures (79/102 (77%) versus 54/102 (53%); P=0.0004). Mean segmentation time per fracture was 27±3min [range, 21-35min]. The segmentation group showed excellent intra-observer correlation coefficients, overall (ICC=0.88), and for simple (ICC=0.92) and complex fractures (ICC=0.84). Semi-automatic segmentation, identifying the various bone fragments, was effective in increasing the rate of correct acetabular fracture classification on the Letournel system by orthopedic surgery residents. It may be considered for routine use in education and training. III: prospective case-control study of a diagnostic procedure. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom
2015-12-23
The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.
Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.
Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A
2015-02-01
Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.
Tóth, László; Hoffmann, Ildikó; Gosztolya, Gábor; Vincze, Veronika; Szatlóczki, Gréta; Bánréti, Zoltán; Pákáski, Magdolna; Kálmán, János
2018-01-01
Background: Even today the reliable diagnosis of the prodromal stages of Alzheimer’s disease (AD) remains a great challenge. Our research focuses on the earliest detectable indicators of cognitive de-cline in mild cognitive impairment (MCI). Since the presence of language impairment has been reported even in the mild stage of AD, the aim of this study is to develop a sensitive neuropsychological screening method which is based on the analysis of spontaneous speech production during performing a memory task. In the future, this can form the basis of an Internet-based interactive screening software for the recognition of MCI. Methods: Participants were 38 healthy controls and 48 clinically diagnosed MCI patients. The provoked spontaneous speech by asking the patients to recall the content of 2 short black and white films (one direct, one delayed), and by answering one question. Acoustic parameters (hesitation ratio, speech tempo, length and number of silent and filled pauses, length of utterance) were extracted from the recorded speech sig-nals, first manually (using the Praat software), and then automatically, with an automatic speech recogni-tion (ASR) based tool. First, the extracted parameters were statistically analyzed. Then we applied machine learning algorithms to see whether the MCI and the control group can be discriminated automatically based on the acoustic features. Results: The statistical analysis showed significant differences for most of the acoustic parameters (speech tempo, articulation rate, silent pause, hesitation ratio, length of utterance, pause-per-utterance ratio). The most significant differences between the two groups were found in the speech tempo in the delayed recall task, and in the number of pauses for the question-answering task. The fully automated version of the analysis process – that is, using the ASR-based features in combination with machine learning - was able to separate the two classes with an F1-score of 78.8%. Conclusion: The temporal analysis of spontaneous speech can be exploited in implementing a new, auto-matic detection-based tool for screening MCI for the community. PMID:29165085
Toth, Laszlo; Hoffmann, Ildiko; Gosztolya, Gabor; Vincze, Veronika; Szatloczki, Greta; Banreti, Zoltan; Pakaski, Magdolna; Kalman, Janos
2018-01-01
Even today the reliable diagnosis of the prodromal stages of Alzheimer's disease (AD) remains a great challenge. Our research focuses on the earliest detectable indicators of cognitive decline in mild cognitive impairment (MCI). Since the presence of language impairment has been reported even in the mild stage of AD, the aim of this study is to develop a sensitive neuropsychological screening method which is based on the analysis of spontaneous speech production during performing a memory task. In the future, this can form the basis of an Internet-based interactive screening software for the recognition of MCI. Participants were 38 healthy controls and 48 clinically diagnosed MCI patients. The provoked spontaneous speech by asking the patients to recall the content of 2 short black and white films (one direct, one delayed), and by answering one question. Acoustic parameters (hesitation ratio, speech tempo, length and number of silent and filled pauses, length of utterance) were extracted from the recorded speech signals, first manually (using the Praat software), and then automatically, with an automatic speech recognition (ASR) based tool. First, the extracted parameters were statistically analyzed. Then we applied machine learning algorithms to see whether the MCI and the control group can be discriminated automatically based on the acoustic features. The statistical analysis showed significant differences for most of the acoustic parameters (speech tempo, articulation rate, silent pause, hesitation ratio, length of utterance, pause-per-utterance ratio). The most significant differences between the two groups were found in the speech tempo in the delayed recall task, and in the number of pauses for the question-answering task. The fully automated version of the analysis process - that is, using the ASR-based features in combination with machine learning - was able to separate the two classes with an F1-score of 78.8%. The temporal analysis of spontaneous speech can be exploited in implementing a new, automatic detection-based tool for screening MCI for the community. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Maison, Dominika; Maliszewski, Norbert
2016-01-01
The goal of this project was to investigate whether consumer ethnocentrism is purely conscious mechanism based on ideology, as suggested by Shimp and Sharma (1987), or rather is an automatic, unconscious process. The aim of the project was an introduction of the Implicit Consumer Ethnocentrism (ICE) concept, measured by the Implicit Association Test (IAT). The goal of the four studies conducted was to investigate the following issues: (a) whether ICE - an automatic mechanism underlying the preference for local products over foreign - this could be observed next to the more ideologically based classic consumer ethnocentrism; (b) what happens when the consumer's automatic preference for local products (ICE) is confronted by objective evidence of the superiority of foreign products or by the inferiority of local products. It was assumed that ICE could be reduced when foreign products were associated with a higher level of competence than local products, and this could explain the preference for foreign products over local often observed in less developed countries. In study 1 the ICE for different product categories of existing brands was tested, and in study 2 the ICE was measured in the context of non-existent brands. Both studies showed a strong in-group brand preference and confirmed the existence of new phenomena - ICE. The results of studies 3 and 4 again indicated a strong, automatic in-group brand favoritism effect as measured by IAT - participants preferred local brands over foreign. However, the inclusion of well-known foreign brands associated with high competence reduced the IAT effect (in-group preference).
O'Connor Mooney, Rory; Davis, Niall Francis; Hoey, David; Hogan, Lisa; McGloughlin, Timothy M; Walsh, Michael T
2016-01-01
To investigate the repeatability of automatic decellularisation of porcine aortae using a non-enzymatic approach, addressing current limitations associated with other automatic decellularisation processes. Individual porcine aortae (n = 3) were resected and every third segment (n = 4) was allocated to one of three different groups: a control or a manually or automatically decellularised group. Manual and automatic decellularisation was performed using Triton X-100 (2% v/v) and sodium deoxycholate. Protein preservation and the elimination of a galactosyl-α(1,3)galactose (GAL) epitope were measured using immunohistochemistry and protein binding assays. The presence of residual DNA was determined with gel electrophoresis and spectrophotometry. Scaffold integrity was characterised with scanning electron microscopy and uni-axial tensile testing. Manual and automatic results were compared to one another, to control groups and to current gold standards. The results were comparable to those of current gold standard decellularisation techniques. Successful repeatability was achieved, both manually and automatically, with little effect on mechanical characteristics. Complete acellularity was not confirmed in either decellularisation group. Protein preservation was consistent in both the manually and automatically decellularised groups and between each individual aorta. Elimination of GAL was not achieved. Repeatable automatic decellularisation of porcine aortae is feasible using a Triton X-100-sodium deoxycholate protocol. Protein preservation was satisfactory; however, gold standard thresholds for permissible residual DNA levels were not achieved. Future research will focus on addressing this issue by optimisation of the existing protocol for thick tissues. © 2016 S. Karger AG, Basel.
Makeyev, Oleksandr; Liu, Xiang; Luna-Munguía, Hiram; Rogel-Salazar, Gabriela; Mucio-Ramirez, Samuel; Liu, Yuhong; Sun, Yan L.; Kay, Steven M.; Besio, Walter G.
2012-01-01
Epilepsy affects approximately one percent of the world population. Antiepileptic drugs are ineffective in approximately 30% of patients and have side effects. We are developing a noninvasive, or minimally invasive, transcranial focal electrical stimulation system through our novel tripolar concentric ring electrodes to control seizures. In this study we demonstrate feasibility of an automatic seizure control system in rats with pentylenetetrazole-induced seizures through single and multiple stimulations. These stimulations are automatically triggered by a real-time electrographic seizure activity detector based on a disjunctive combination of detections from a cumulative sum algorithm and a generalized likelihood ratio test. An average seizure onset detection accuracy of 76.14% was obtained for the test set (n = 13). Detection of electrographic seizure activity was accomplished in advance of the early behavioral seizure activity in 76.92% of the cases. Automatically triggered stimulation significantly (p = 0.001) reduced the electrographic seizure activity power in the once stimulated group compared to controls in 70% of the cases. To the best of our knowledge this is the first closed-loop automatic seizure control system based on noninvasive electrical brain stimulation using tripolar concentric ring electrode electrographic seizure activity as feedback. PMID:22772373
Makeyev, Oleksandr; Liu, Xiang; Luna-Munguía, Hiram; Rogel-Salazar, Gabriela; Mucio-Ramirez, Samuel; Liu, Yuhong; Sun, Yan L; Kay, Steven M; Besio, Walter G
2012-07-01
Epilepsy affects approximately 1% of the world population. Antiepileptic drugs are ineffective in approximately 30% of patients and have side effects. We are developing a noninvasive, or minimally invasive, transcranial focal electrical stimulation system through our novel tripolar concentric ring electrodes to control seizures. In this study, we demonstrate feasibility of an automatic seizure control system in rats with pentylenetetrazole-induced seizures through single and multiple stimulations. These stimulations are automatically triggered by a real-time electrographic seizure activity detector based on a disjunctive combination of detections from a cumulative sum algorithm and a generalized likelihood ratio test. An average seizure onset detection accuracy of 76.14% was obtained for the test set (n = 13). Detection of electrographic seizure activity was accomplished in advance of the early behavioral seizure activity in 76.92% of the cases. Automatically triggered stimulation significantly (p = 0.001) reduced the electrographic seizure activity power in the once stimulated group compared to controls in 70% of the cases. To the best of our knowledge this is the first closed-loop automatic seizure control system based on noninvasive electrical brain stimulation using tripolar concentric ring electrode electrographic seizure activity as feedback.
Automatic liver volume segmentation and fibrosis classification
NASA Astrophysics Data System (ADS)
Bal, Evgeny; Klang, Eyal; Amitai, Michal; Greenspan, Hayit
2018-02-01
In this work, we present an automatic method for liver segmentation and fibrosis classification in liver computed-tomography (CT) portal phase scans. The input is a full abdomen CT scan with an unknown number of slices, and the output is a liver volume segmentation mask and a fibrosis grade. A multi-stage analysis scheme is applied to each scan, including: volume segmentation, texture features extraction and SVM based classification. Data contains portal phase CT examinations from 80 patients, taken with different scanners. Each examination has a matching Fibroscan grade. The dataset was subdivided into two groups: first group contains healthy cases and mild fibrosis, second group contains moderate fibrosis, severe fibrosis and cirrhosis. Using our automated algorithm, we achieved an average dice index of 0.93 ± 0.05 for segmentation and a sensitivity of 0.92 and specificity of 0.81for classification. To the best of our knowledge, this is a first end to end automatic framework for liver fibrosis classification; an approach that, once validated, can have a great potential value in the clinic.
Effectiveness of Feedback for Enhancing English Pronunciation in an ASR-Based CALL System
ERIC Educational Resources Information Center
Wang, Y.-H.; Young, S. S.-C.
2015-01-01
This paper presents a study on implementing the ASR-based CALL (computer-assisted language learning based upon automatic speech recognition) system embedded with both formative and summative feedback approaches and using implicit and explicit strategies to enhance adult and young learners' English pronunciation. Two groups of learners including 18…
Zare, Marzieh; Rezvani, Zahra; Benasich, April A
2016-07-01
This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Maison, Dominika; Maliszewski, Norbert
2016-01-01
The goal of this project was to investigate whether consumer ethnocentrism is purely conscious mechanism based on ideology, as suggested by Shimp and Sharma (1987), or rather is an automatic, unconscious process. The aim of the project was an introduction of the Implicit Consumer Ethnocentrism (ICE) concept, measured by the Implicit Association Test (IAT). The goal of the four studies conducted was to investigate the following issues: (a) whether ICE – an automatic mechanism underlying the preference for local products over foreign – this could be observed next to the more ideologically based classic consumer ethnocentrism; (b) what happens when the consumer’s automatic preference for local products (ICE) is confronted by objective evidence of the superiority of foreign products or by the inferiority of local products. It was assumed that ICE could be reduced when foreign products were associated with a higher level of competence than local products, and this could explain the preference for foreign products over local often observed in less developed countries. In study 1 the ICE for different product categories of existing brands was tested, and in study 2 the ICE was measured in the context of non-existent brands. Both studies showed a strong in-group brand preference and confirmed the existence of new phenomena – ICE. The results of studies 3 and 4 again indicated a strong, automatic in-group brand favoritism effect as measured by IAT – participants preferred local brands over foreign. However, the inclusion of well-known foreign brands associated with high competence reduced the IAT effect (in-group preference). PMID:27920746
Motor signatures of emotional reactivity in frontotemporal dementia.
Marshall, Charles R; Hardy, Chris J D; Russell, Lucy L; Clark, Camilla N; Bond, Rebecca L; Dick, Katrina M; Brotherhood, Emilie V; Mummery, Cath J; Schott, Jonathan M; Rohrer, Jonathan D; Kilner, James M; Warren, Jason D
2018-01-18
Automatic motor mimicry is essential to the normal processing of perceived emotion, and disrupted automatic imitation might underpin socio-emotional deficits in neurodegenerative diseases, particularly the frontotemporal dementias. However, the pathophysiology of emotional reactivity in these diseases has not been elucidated. We studied facial electromyographic responses during emotion identification on viewing videos of dynamic facial expressions in 37 patients representing canonical frontotemporal dementia syndromes versus 21 healthy older individuals. Neuroanatomical associations of emotional expression identification accuracy and facial muscle reactivity were assessed using voxel-based morphometry. Controls showed characteristic profiles of automatic imitation, and this response predicted correct emotion identification. Automatic imitation was reduced in the behavioural and right temporal variant groups, while the normal coupling between imitation and correct identification was lost in the right temporal and semantic variant groups. Grey matter correlates of emotion identification and imitation were delineated within a distributed network including primary visual and motor, prefrontal, insular, anterior temporal and temporo-occipital junctional areas, with common involvement of supplementary motor cortex across syndromes. Impaired emotional mimesis may be a core mechanism of disordered emotional signal understanding and reactivity in frontotemporal dementia, with implications for the development of novel physiological biomarkers of socio-emotional dysfunction in these diseases.
A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC
Clematide, Simon; Akhondi, Saber A; van Mulligen, Erik M; Rebholz-Schuhmann, Dietrich
2015-01-01
Objective To create a multilingual gold-standard corpus for biomedical concept recognition. Materials and methods We selected text units from different parallel corpora (Medline abstract titles, drug labels, biomedical patent claims) in English, French, German, Spanish, and Dutch. Three annotators per language independently annotated the biomedical concepts, based on a subset of the Unified Medical Language System and covering a wide range of semantic groups. To reduce the annotation workload, automatically generated preannotations were provided. Individual annotations were automatically harmonized and then adjudicated, and cross-language consistency checks were carried out to arrive at the final annotations. Results The number of final annotations was 5530. Inter-annotator agreement scores indicate good agreement (median F-score 0.79), and are similar to those between individual annotators and the gold standard. The automatically generated harmonized annotation set for each language performed equally well as the best annotator for that language. Discussion The use of automatic preannotations, harmonized annotations, and parallel corpora helped to keep the manual annotation efforts manageable. The inter-annotator agreement scores provide a reference standard for gauging the performance of automatic annotation techniques. Conclusion To our knowledge, this is the first gold-standard corpus for biomedical concept recognition in languages other than English. Other distinguishing features are the wide variety of semantic groups that are being covered, and the diversity of text genres that were annotated. PMID:25948699
Detecting and measuring metabolic byproducts by electrochemical sensing
NASA Technical Reports Server (NTRS)
Wilkins, J. R.; Stoner, G. E.
1974-01-01
Method of detecting certain groups of bacteria is based on sensing buildup in molecular hydrogen. Apparatus is easy to assemble and use, and it has added advantage that hydrogen evolution by test micro-organisms can be measured automatically and accurately. System has been used to detect and enumerate variety of gram-negative bacteria of enterobacteriaceae group.
Virgincar, Rohan S.; Cleveland, Zackary I.; Kaushik, S. Sivaram; Freeman, Matthew S.; Nouls, John; Cofer, Gary P.; Martinez-Jimenez, Santiago; He, Mu; Kraft, Monica; Wolber, Jan; McAdams, H. Page; Driehuys, Bastiaan
2013-01-01
In this study, hyperpolarized (HP) 129Xe MR ventilation and 1H anatomical images were obtained from 3 subject groups: young healthy volunteers (HV), subjects with chronic obstructive pulmonary disease (COPD), and age-matched control subjects (AMC). Ventilation images were quantified by 2 methods: an expert reader-based ventilation defect score percentage (VDS%) and a semi-automatic segmentation-based ventilation defect percentage (VDP). Reader-based values were assigned by two experienced radiologists and resolved by consensus. In the semi-automatic analysis, 1H anatomical images and 129Xe ventilation images were both segmented following registration, to obtain the thoracic cavity volume (TCV) and ventilated volume (VV), respectively, which were then expressed as a ratio to obtain the VDP. Ventilation images were also characterized by generating signal intensity histograms from voxels within the TCV, and heterogeneity was analyzed using the coefficient of variation (CV). The reader-based VDS% correlated strongly with the semi-automatically generated VDP (r = 0.97, p < 0.0001), and with CV (r = 0.82, p < 0.0001). Both 129Xe ventilation defect scoring metrics readily separated the 3 groups from one another and correlated significantly with FEV1 (VDS%: r = -0.78, p = 0.0002; VDP: r = -0.79, p = 0.0003; CV: r = -0.66, p = 0.0059) and other pulmonary function tests. In the healthy subject groups (HV and AMC), the prevalence of ventilation defects also increased with age (VDS%: r = 0.61, p = 0.0002; VDP: r = 0.63, p = 0.0002). Moreover, ventilation histograms and their associated CVs distinguished between COPD subjects with similar ventilation defect scores but visibly different ventilation patterns. PMID:23065808
Die Starter: A New System to Manage Early Feasibility in Sheet Metal Forming
NASA Astrophysics Data System (ADS)
Narainen, Rodrigue; Porzner, Harald
2016-08-01
Die Starter, a new system developed by ESI Group, allows the user to drastically reduce the number of iterations during the early tool process feasibility. This innovative system automatically designs the first quick die face, generating binder and addendum surfaces (NURBS surfaces) by taking account the full die process. Die Starter also improves the initial die face based on feasibility criteria (avoiding splits, wrinkles) by automatically generating the geometrical modifications of the binder and addendum and the bead restraining forces with minimal material usage. This paper presents a description of the new system and the methodology of Die Starter. Some industrial examples are presented from the part geometry to final die face including automatic developed flanges, part on binder and inner binder.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCarroll, R; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX; Beadle, B
Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrectmore » contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to flag auto-contours for special review or used with safety margins in a fully automatic treatment planning system.« less
Muñoz-Organero, Mario; Davies, Richard; Mawson, Sue
2017-01-01
Insole pressure sensors capture the force distribution patterns during the stance phase while walking. By comparing patterns obtained from healthy individuals to patients suffering different medical conditions based on a given similarity measure, automatic impairment indexes can be computed in order to help in applications such as rehabilitation. This paper uses the data sensed from insole pressure sensors for a group of healthy controls to train an auto-encoder using patterns of stochastic distances in series of consecutive steps while walking at normal speeds. Two experiment groups are compared to the healthy control group: a group of patients suffering knee pain and a group of post-stroke survivors. The Mahalanobis distance is computed for every single step by each participant compared to the entire dataset sensed from healthy controls. The computed distances for consecutive steps are fed into the previously trained autoencoder and the average error is used to assess how close the walking segment is to the autogenerated model from healthy controls. The results show that automatic distortion indexes can be used to assess each participant as compared to normal patterns computed from healthy controls. The stochastic distances observed for the group of stroke survivors are bigger than those for the people with knee pain.
Team-Based Learning in Honors Science Education: The Benefit of Complex Writing Assignments
ERIC Educational Resources Information Center
Wiegant, Fred; Boonstra, Johannes; Peeters, Anton; Scager, Karin
2012-01-01
Cooperative learning and team-based learning have been widely recognized as beneficial strategies to improve all levels of education, including higher education. Just forming groups, however, does not automatically lead to better learning and motivation; cooperation flourishes only under appropriate conditions (Fink; Gillies; Parmelee et al.).…
Minimization In Digital Design As A Meta-Planning Problem
NASA Astrophysics Data System (ADS)
Ho, William P. C.; Wu, Jung-Gen
1987-05-01
In our model-based expert system for automatic digital system design, we formalize the design process into three sub-processes - compiling high-level behavioral specifications into primitive behavioral operations, grouping primitive operations into behavioral functions, and grouping functions into modules. Consideration of design minimization explicitly controls decision-making in the last two subprocesses. Design minimization, a key task in the automatic design of digital systems, is complicated by the high degree of interaction among the time sequence and content of design decisions. In this paper, we present an AI approach which directly addresses these interactions and their consequences by modeling the minimization prob-lem as a planning problem, and the management of design decision-making as a meta-planning problem.
The role of awareness of repetition during the development of automaticity in a dot-counting task
Shadbolt, Emma
2018-01-01
This study examined whether being aware of the repetition of stimuli in a simple numerosity task could aid the development of automaticity. The numerosity task used in this study was a simple counting task. Thirty-four participants were divided into two groups. One group was instructed that the stimuli would repeat many times throughout the experiment. The results showed no significant differences in the way automatic processing developed between the groups. Similarly, there was no correlation between the point at which automatic processing developed and the point at which participants felt they benefitted from the repetition of stimuli. These results suggest that extra-trial features of a task may have no effect on the development of automaticity, a finding consistent with the instance theory of automatisation. PMID:29404220
Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A
2017-01-15
Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.
Development and evaluation of an automatic labeling technique for spring small grains
NASA Technical Reports Server (NTRS)
Crist, E. P.; Malila, W. A. (Principal Investigator)
1981-01-01
A labeling technique is described which seeks to associate a sampling entity with a particular crop or crop group based on similarity of growing season and temporal-spectral patterns of development. Human analyst provide contextual information, after which labeling decisions are made automatically. Results of a test of the technique on a large, multi-year data set are reported. Grain labeling accuracies are similar to those achieved by human analysis techniques, while non-grain accuracies are lower. Recommendations for improvments and implications of the test results are discussed.
Automatic stereotyping against people with schizophrenia, schizoaffective and affective disorders
Rüsch, Nicolas; Corrigan, Patrick W.; Todd, Andrew R.; Bodenhausen, Galen V.
2010-01-01
Similar to members of the public, people with mental illness may exhibit general negative automatic prejudice against their own group. However, it is unclear whether more specific negative stereotypes are automatically activated among diagnosed individuals and how such automatic stereotyping may be related to self-reported attitudes and emotional reactions. We therefore studied automatically activated reactions toward mental illness among 85 people with schizophrenia, schizoaffective or affective disorders as well as among 50 members of the general public, using a Lexical Decision Task to measure automatic stereotyping. Deliberately endorsed attitudes and emotional reactions were assessed by self-report. Independent of diagnosis, people with mental illness showed less negative automatic stereotyping than did members of the public. Among members of the public, stronger automatic stereotyping was associated with more self-reported shame about a potential mental illness and more anger toward stigmatized individuals. Reduced automatic stereotyping in the diagnosed group suggests that people with mental illness might not entirely internalize societal stigma. Among members of the public, automatic stereotyping predicted negative emotional reactions to people with mental illness. Initiatives to reduce the impact of public stigma and internalized stigma should take automatic stereotyping and related emotional aspects of stigma into account. PMID:20843560
USSR Report, Kommunist, No. 13, September 1986.
1987-01-07
all-union) program for specialization of NPO and industrial enterprises and their scientific research institutes and design bureaus could play a major...machine tools with numerical programming (ChPU), processing centers, automatic machines and groups of automatic machines controlled by computers, and...automatic lines, computer- controlled groups of equipment, comprehensively automated shops and sections) is the most important feature of high technical
ERIC Educational Resources Information Center
Schlechty, Phillip C.
1993-01-01
Advocates of participatory leadership, site-based management, and decentralization often assume that changing decision-making group composition will automatically improve the quality of decisions being made. Stakeholder satisfaction does not guarantee quality results. This article offers a framework for moving the decision-making discussion from…
Automatic Configuration of Programmable Logic Controller Emulators
2015-03-01
25 11 Example tree generated using UPGMA [Edw13] . . . . . . . . . . . . . . . . . . . . 33 12 Example sequence alignment for two... UPGMA Unweighted Pair Group Method with Arithmetic Mean URL uniform resource locator VM virtual machine XML Extensible Markup Language xx List of...appearance in the ses- sion, and then they are clustered again using Unweighted Pair Group Method with Arithmetic Mean ( UPGMA ) with a distance matrix based
Toews, Matthew; Wells, William M.; Collins, Louis; Arbel, Tal
2013-01-01
This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer’s (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102
Ostafin, Brian D; Palfai, Tibor P
2012-12-07
Research indicates that brief motivational interventions are efficacious treatments for hazardous drinking. Little is known, however, about the psychological processes that may moderate intervention success. Based on growing evidence that drinking behavior may be influenced by automatic (nonvolitional) mental processes, the current study examined whether automatic alcohol-approach associations moderated the effect of a brief motivational intervention. Specifically, we examined whether the efficacy of a single-session intervention designed to increase motivation to reduce alcohol consumption would be moderated by the strength of participants' automatic alcohol-approach associations. Eighty-seven undergraduate hazardous drinkers participated for course credit. Participants completed an Implicit Association Test to measure automatic alcohol-approach associations, a baseline measure of readiness to change drinking behavior, and measures of alcohol involvement. Participants were then randomly assigned to either a brief (15-minute) motivational intervention or a control condition. Participants completed a measure of readiness to change drinking at the end of the first session and returned for a follow-up session six weeks later in which they reported on their drinking over the previous month. Compared with the control group, those in the intervention condition showed higher readiness to change drinking at the end of the baseline session but did not show decreased drinking quantity at follow-up. Automatic alcohol-approach associations moderated the effects of the intervention on change in drinking quantity. Among participants in the intervention group, those with weak automatic alcohol-approach associations showed greater reductions in the amount of alcohol consumed per occasion at follow-up compared with those with strong automatic alcohol-approach associations. Automatic appetitive associations with alcohol were not related with change in amount of alcohol consumed per occasion in control participants. Furthermore, among participants who showed higher readiness to change, those who exhibited weaker alcohol-approach associations showed greater reductions in drinking quantity compared with those who exhibited stronger alcohol-approach associations. The results support the idea that automatic mental processes may moderate the influence of brief motivational interventions on quantity of alcohol consumed per drinking occasion. The findings suggest that intervention efficacy may be improved by utilizing implicit measures to identify those who may be responsive to brief interventions and by developing intervention elements to address the influence of automatic processes on drinking behavior.
Automatic indexing and retrieval of encounter-specific evidence for point-of-care support.
O'Sullivan, Dympna M; Wilk, Szymon A; Michalowski, Wojtek J; Farion, Ken J
2010-08-01
Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient-physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts - diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories. Copyright 2010 Elsevier Inc. All rights reserved.
A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC.
Kors, Jan A; Clematide, Simon; Akhondi, Saber A; van Mulligen, Erik M; Rebholz-Schuhmann, Dietrich
2015-09-01
To create a multilingual gold-standard corpus for biomedical concept recognition. We selected text units from different parallel corpora (Medline abstract titles, drug labels, biomedical patent claims) in English, French, German, Spanish, and Dutch. Three annotators per language independently annotated the biomedical concepts, based on a subset of the Unified Medical Language System and covering a wide range of semantic groups. To reduce the annotation workload, automatically generated preannotations were provided. Individual annotations were automatically harmonized and then adjudicated, and cross-language consistency checks were carried out to arrive at the final annotations. The number of final annotations was 5530. Inter-annotator agreement scores indicate good agreement (median F-score 0.79), and are similar to those between individual annotators and the gold standard. The automatically generated harmonized annotation set for each language performed equally well as the best annotator for that language. The use of automatic preannotations, harmonized annotations, and parallel corpora helped to keep the manual annotation efforts manageable. The inter-annotator agreement scores provide a reference standard for gauging the performance of automatic annotation techniques. To our knowledge, this is the first gold-standard corpus for biomedical concept recognition in languages other than English. Other distinguishing features are the wide variety of semantic groups that are being covered, and the diversity of text genres that were annotated. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Enhancing acronym/abbreviation knowledge bases with semantic information.
Torii, Manabu; Liu, Hongfang
2007-10-11
In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.
NASA Astrophysics Data System (ADS)
Cong, Chao; Liu, Dingsheng; Zhao, Lingjun
2008-12-01
This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie point pairs according to geographic characters from such heterogeneous images. Since there are big differences between such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.
Zou, Yingmin; Li, Huanhuan; Shi, Chuan; Lin, Yixuan; Zhou, Hanyu; Zhang, Jiaqi
2017-03-01
The present study aimed to explore the effects of psychological pain theory-based cognitive therapy (PPTBCT) on suicide among depressed patients, compared with a control group who received usual psychological care (UPC). The sample consisted of 32 depressed patients and 32 healthy control subjects. All participants completed the Beck Scale for Suicide Ideation (BSI), Beck Depression Inventory, Three-Dimensional Psychological Pain Scale (TDPPS), and Problem Solving Inventory(PSI), and Automatic Thoughts Questionnaire (ATQ). All measures differed significantly between depressed patients and healthy controls. Then clinical participants were assigned randomly to the PPTBCT (n=19) and control (n=13) groups. During the 8-week intervention, scores related to depression, suicidal ideation, psychological pain, and automatic thoughts were decreased in both groups at the post-intervention and 4-week follow-up time points, compared with pre-intervention scores. BSI scores remained low at follow up and did not differ significantly from post-intervention scores in the PPTBCT group, but were significantly higher at follow up than at post-intervention in the control group. PPTBCT may effectively reduce suicide risk in patients with major depressive disorder, although the effects of its application need to be confirmed. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
Improving Cluster Analysis with Automatic Variable Selection Based on Trees
2014-12-01
regression trees Daisy DISsimilAritY PAM partitioning around medoids PMA penalized multivariate analysis SPC sparse principal components UPGMA unweighted...unweighted pair-group average method ( UPGMA ). This method measures dissimilarities between all objects in two clusters and takes the average value
Moeller, Birte; Frings, Christian
2014-01-01
Grégoire, Perruchet, and Poulin-Charronnat (2013) investigated a musical variant of the reversed Stroop effect. According to the authors, one big advantage of this variant is that the automaticity of note naming can be better controlled than in other Stroop variants as musicians are very practiced in note reading whereas non-musicians are not. In this comment we argue that at present the exact impact of automaticity in this Stroop variant remains somewhat unclear for at least three reasons, namely due to the type of information that is automatically retrieved when notes are encountered, due to the possible influence of object-based attention, and finally due to the fact that the exact influence of expertise on interference cannot be pinpointed with an extreme group design.
Neurosurgical robotic arm drilling navigation system.
Lin, Chung-Chih; Lin, Hsin-Cheng; Lee, Wen-Yo; Lee, Shih-Tseng; Wu, Chieh-Tsai
2017-09-01
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process. The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled-through. Three kinds of experiment were designed. The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto-stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non-drilled-through cases (8.42% and 4.21% in control groups 1 and 2). The system may be useful for neurosurgical robotic arm drilling navigation. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Demedeiros, J. S.; Desantana, C. C.; Alves, E. C. M.
1981-01-01
The state of Mato Grosso do Sul was selected as the study area to define the recognizable classes of Eucalyptus spp. and Pinus spp. by visual and automatic analyses. For visual analysis, a preliminary interpretation key and a legend of 6 groups were derived. Based on these six groups, three final classes were defined for analysis: (1) area prepared for reforestation; (2) area reforested with Eucalyptus spp.; and (3) area reforested with Pinus spp. For automatic interpretation the area along the highway from Ribas do Rio Pardo to Agua Clara was classified into the following classes: eucalytus, bare soil, plowed soil, pine and "cerrado". The results of visual analysis show that 67% of the reforested farms have relative differences in area estimate below 5%, 22%, between 5% and 10%; and 11% between 10% and 20%. The reforested eucalyptus area is 17 times greater than the area of reforested pine. Automatic classification of eucalyptus ranged from 73.03% to 92.30% in the training areas.
Delineation and geometric modeling of road networks
NASA Astrophysics Data System (ADS)
Poullis, Charalambos; You, Suya
In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.
Lim, Jiyeon; Park, Eun-Ah; Lee, Whal; Shim, Hackjoon; Chung, Jin Wook
2015-06-01
To assess the image quality and radiation exposure of 320-row area detector computed tomography (320-ADCT) coronary angiography with optimal tube voltage selection with the guidance of an automatic exposure control system in comparison with a body mass index (BMI)-adapted protocol. Twenty-two patients (study group) underwent 320-ADCT coronary angiography using an automatic exposure control system with the target standard deviation value of 33 as the image quality index and the lowest possible tube voltage. For comparison, a sex- and BMI-matched group (control group, n = 22) using a BMI-adapted protocol was established. Images of both groups were reconstructed by an iterative reconstruction algorithm. For objective evaluation of the image quality, image noise, vessel density, signal to noise ratio (SNR), and contrast to noise ratio (CNR) were measured. Two blinded readers then subjectively graded the image quality using a four-point scale (1: nondiagnostic to 4: excellent). Radiation exposure was also measured. Although the study group tended to show higher image noise (14.1 ± 3.6 vs. 9.3 ± 2.2 HU, P = 0.111) and higher vessel density (665.5 ± 161 vs. 498 ± 143 HU, P = 0.430) than the control group, the differences were not significant. There was no significant difference between the two groups for SNR (52.5 ± 19.2 vs. 60.6 ± 21.8, P = 0.729), CNR (57.0 ± 19.8 vs. 67.8 ± 23.3, P = 0.531), or subjective image quality scores (3.47 ± 0.55 vs. 3.59 ± 0.56, P = 0.960). However, radiation exposure was significantly reduced by 42 % in the study group (1.9 ± 0.8 vs. 3.6 ± 0.4 mSv, P = 0.003). Optimal tube voltage selection with the guidance of an automatic exposure control system in 320-ADCT coronary angiography allows substantial radiation reduction without significant impairment of image quality, compared to the results obtained using a BMI-based protocol.
Murray, Andrea K; Feng, Kaiyan; Moore, Tonia L; Allen, Phillip D; Taylor, Christopher J; Herrick, Ariane L
2011-08-01
Nailfold capillaroscopy is well established in screening patients with Raynaud's phenomenon for underlying SSc-spectrum disorders, by identifying abnormal capillaries. Our aim was to compare semi-automatic feature measurement from newly developed software with manual measurements, and determine the degree to which semi-automated data allows disease group classification. Images from 46 healthy controls, 21 patients with PRP and 49 with SSc were preprocessed, and semi-automated measurements of intercapillary distance and capillary width, tortuosity, and derangement were performed. These were compared with manual measurements. Features were used to classify images into the three subject groups. Comparison of automatic and manual measures for distance, width, tortuosity, and derangement had correlations of r=0.583, 0.624, 0.495 (p<0.001), and 0.195 (p=0.040). For automatic measures, correlations were found between width and intercapillary distance, r=0.374, and width and tortuosity, r=0.573 (p<0.001). Significant differences between subject groups were found for all features (p<0.002). Overall, 75% of images correctly matched clinical classification using semi-automated features, compared with 71% for manual measurements. Semi-automatic and manual measurements of distance, width, and tortuosity showed moderate (but statistically significant) correlations. Correlation for derangement was weaker. Semi-automatic measurements are faster than manual measurements. Semi-automatic parameters identify differences between groups, and are as good as manual measurements for between-group classification. © 2011 John Wiley & Sons Ltd.
Automatic Processing of Changes in Facial Emotions in Dysphoria: A Magnetoencephalography Study.
Xu, Qianru; Ruohonen, Elisa M; Ye, Chaoxiong; Li, Xueqiao; Kreegipuu, Kairi; Stefanics, Gabor; Luo, Wenbo; Astikainen, Piia
2018-01-01
It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck's Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria.
Almeida, Diogo F; Ruben, Rui B; Folgado, João; Fernandes, Paulo R; Audenaert, Emmanuel; Verhegghe, Benedict; De Beule, Matthieu
2016-12-01
Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.
Training and subjective workload in a category search task
NASA Technical Reports Server (NTRS)
Vidulich, Michael A.; Pandit, Parimal
1986-01-01
This study examined automaticity as a means by which training influences mental workload. Two groups were trained in a category search task. One group received a training paradigm designed to promote the development of automaticity; the other group received a training paradigm designed to prohibit it. Resultant performance data showed the expected improvement as a result of the development of automaticity. Subjective workload assessments mirrored the performance results in most respects. The results supported the position that subjective mental workload assessments may be sensitive to the effect of training when it produces a lower level of cognitive load.
Clerkin, Elise M.; Fisher, Christopher R.; Sherman, Jeffrey W.; Teachman, Bethany A.
2013-01-01
Objective This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. Method The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n=28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n=31). Results Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. Conclusions This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person’s ability to use reflective processing to overcome biased automatic processing. PMID:24275066
Automatic affective appraisal of sexual penetration stimuli in women with vaginismus or dyspareunia.
Huijding, Jorg; Borg, Charmaine; Weijmar-Schultz, Willibrord; de Jong, Peter J
2011-03-01
Current psychological views are that negative appraisals of sexual stimuli lie at the core of sexual dysfunctions. It is important to differentiate between deliberate appraisals and more automatic appraisals, as research has shown that the former are most relevant to controllable behaviors, and the latter are most relevant to reflexive behaviors. Accordingly, it can be hypothesized that in women with vaginismus, the persistent difficulty to allow vaginal entry is due to global negative automatic affective appraisals that trigger reflexive pelvic floor muscle contraction at the prospect of penetration. To test whether sexual penetration pictures elicited global negative automatic affective appraisals in women with vaginismus or dyspareunia and to examine whether deliberate appraisals and automatic appraisals differed between the two patient groups. Women with persistent vaginismus (N = 24), dyspareunia (N = 23), or no sexual complaints (N = 30) completed a pictorial Extrinsic Affective Simon Task (EAST), and then made a global affective assessment of the EAST stimuli using visual analogue scales (VAS). The EAST assessed global automatic affective appraisals of sexual penetration stimuli, while the VAS assessed global deliberate affective appraisals of these stimuli. Automatic affective appraisals of sexual penetration stimuli tended to be positive, independent of the presence of sexual complaints. Deliberate appraisals of the same stimuli were significantly more negative in the women with vaginismus than in the dyspareunia group and control group, while the latter two groups did not differ in their appraisals. Unexpectedly, deliberate appraisals seemed to be most important in vaginismus, whereas dyspareunia did not seem to implicate negative deliberate or automatic affective appraisals. These findings dispute the view that global automatic affect lies at the core of vaginismus and indicate that a useful element in therapeutic interventions may be the modification of deliberate global affective appraisals of sexual penetration (e.g., via counter-conditioning). © 2010 International Society for Sexual Medicine.
Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Hajnal, Joseph V.; Duncan, John S.; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander
2012-01-01
Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study. PMID:22523539
Collette, Fabienne; Van der Linden, Martial; Salmon, Eric
2010-01-01
A decline of cognitive functioning affecting several cognitive domains was frequently reported in patients with frontotemporal dementia. We were interested in determining if these deficits can be interpreted as reflecting an impairment of controlled cognitive processes by using an assessment tool specifically developed to explore the distinction between automatic and controlled processes, namely the process dissociation procedure (PDP) developed by Jacoby. The PDP was applied to a word stem completion task to determine the contribution of automatic and controlled processes to episodic memory performance and was administered to a group of 12 patients with the behavioral variant of frontotemporal dementia (bv-FTD) and 20 control subjects (CS). Bv-FTD patients obtained a lower performance than CS for the estimates of controlled processes, but no group differences was observed for estimates of automatic processes. The between-groups comparison of the estimates of controlled and automatic processes showed a larger contribution of automatic processes to performance in bv-FTD, while a slightly more important contribution of controlled processes was observed in control subjects. These results are clearly indicative of an alteration of controlled memory processes in bv-FTD.
Sun, Ming-Shen; Zhang, Li; Guo, Ning; Song, Yan-Zheng; Zhang, Feng-Ju
2018-01-01
To evaluate and compare the uniformity of angle Kappa adjustment between Oculyzer and Topolyzer Vario topography guided ablation of laser in situ keratomileusis (LASIK) by EX500 excimer laser for myopia. Totally 145 cases (290 consecutive eyes )with myopia received LASIK with a target of emmetropia. The ablation for 86 cases (172 eyes) was guided manually based on Oculyzer topography (study group), while the ablation for 59 cases (118 eyes) was guided automatically by Topolyzer Vario topography (control group). Measurement of adjustment values included data respectively in horizontal and vertical direction of cornea. Horizontally, synclastic adjustment between manually actual values (dx manu ) and Oculyzer topography guided data (dx ocu ) accounts 35.5% in study group, with mean dx manu /dx ocu of 0.78±0.48; while in control group, synclastic adjustment between automatically actual values (dx auto ) and Oculyzer topography data (dx ocu ) accounts 54.2%, with mean dx auto /dx ocu of 0.79±0.66. Vertically, synclastic adjustment between dy manu and dy ocu accounts 55.2% in study group, with mean dy manu /dy ocu of 0.61±0.42; while in control group, synclastic adjustment between dy auto and dy ocu accounts 66.1%, with mean dy auto /dy ocu of 0.66±0.65. There was no statistically significant difference in ratio of actual values/Oculyzer topography guided data in horizontal and vertical direction between two groups ( P =0.951, 0.621). There is high consistency in angle Kappa adjustment guided manually by Oculyzer and guided automatically by Topolyzer Vario topography during corneal refractive surgery by WaveLight EX500 excimer laser.
Park, Jong-Uk; Lee, Hyo-Ki; Lee, Junghun; Urtnasan, Erdenebayar; Kim, Hojoong; Lee, Kyoung-Joung
2015-09-01
This study proposes a method of automatically classifying sleep apnea/hypopnea events based on sleep states and the severity of sleep-disordered breathing (SDB) using photoplethysmogram (PPG) and oxygen saturation (SpO2) signals acquired from a pulse oximeter. The PPG was used to classify sleep state, while the severity of SDB was estimated by detecting events of SpO2 oxygen desaturation. Furthermore, we classified sleep apnea/hypopnea events by applying different categorisations according to the severity of SDB based on a support vector machine. The classification results showed sensitivity performances and positivity predictive values of 74.2% and 87.5% for apnea, 87.5% and 63.4% for hypopnea, and 92.4% and 92.8% for apnea + hypopnea, respectively. These results represent better or comparable outcomes compared to those of previous studies. In addition, our classification method reliably detected sleep apnea/hypopnea events in all patient groups without bias in particular patient groups when our algorithm was applied to a variety of patient groups. Therefore, this method has the potential to diagnose SDB more reliably and conveniently using a pulse oximeter.
NASA Astrophysics Data System (ADS)
Kang, Won-Seok; Son, Chang-Sik; Lee, Sangho; Choi, Rock-Hyun; Ha, Yeong-Mi
2017-07-01
In this paper, we introduce a wellness software platform, called WellnessHumanCare, is a semi-automatic wellness management software platform which has the functions of complex wellness data acquisition(mental, physical and environmental one) with smart wearable devices, complex wellness condition analysis, private-aware online/offline recommendation, real-time monitoring apps (Smartphone-based, Web-based) and so on and we has demonstrated a wellness management service with 79 participants (experimental group: 39, control group: 40) who has worked at experimental group (H Corp.) and control group (K Corp.), Korea and 3 months in order to show the efficiency of the WellnessHumanCare.
NASA Astrophysics Data System (ADS)
Hwang, Taejin; Kim, Yong Nam; Kim, Soo Kon; Kang, Sei-Kwon; Cheong, Kwang-Ho; Park, Soah; Yoon, Jai-Woong; Han, Taejin; Kim, Haeyoung; Lee, Meyeon; Kim, Kyoung-Joo; Bae, Hoonsik; Suh, Tae-Suk
2015-06-01
The dose constraint during prostate intensity-modulated radiation therapy (IMRT) optimization should be patient-specific for better rectum sparing. The aims of this study are to suggest a novel method for automatically generating a patient-specific dose constraint by using an experience-based dose volume histogram (DVH) of the rectum and to evaluate the potential of such a dose constraint qualitatively. The normal tissue complication probabilities (NTCPs) of the rectum with respect to V %ratio in our study were divided into three groups, where V %ratio was defined as the percent ratio of the rectal volume overlapping the planning target volume (PTV) to the rectal volume: (1) the rectal NTCPs in the previous study (clinical data), (2) those statistically generated by using the standard normal distribution (calculated data), and (3) those generated by combining the calculated data and the clinical data (mixed data). In the calculated data, a random number whose mean value was on the fitted curve described in the clinical data and whose standard deviation was 1% was generated by using the `randn' function in the MATLAB program and was used. For each group, we validated whether the probability density function (PDF) of the rectal NTCP could be automatically generated with the density estimation method by using a Gaussian kernel. The results revealed that the rectal NTCP probability increased in proportion to V %ratio , that the predictive rectal NTCP was patient-specific, and that the starting point of IMRT optimization for the given patient might be different. The PDF of the rectal NTCP was obtained automatically for each group except that the smoothness of the probability distribution increased with increasing number of data and with increasing window width. We showed that during the prostate IMRT optimization, the patient-specific dose constraints could be automatically generated and that our method could reduce the IMRT optimization time as well as maintain the IMRT plan quality.
A Corpus-Based Approach for Automatic Thai Unknown Word Recognition Using Boosting Techniques
NASA Astrophysics Data System (ADS)
Techo, Jakkrit; Nattee, Cholwich; Theeramunkong, Thanaruk
While classification techniques can be applied for automatic unknown word recognition in a language without word boundary, it faces with the problem of unbalanced datasets where the number of positive unknown word candidates is dominantly smaller than that of negative candidates. To solve this problem, this paper presents a corpus-based approach that introduces a so-called group-based ranking evaluation technique into ensemble learning in order to generate a sequence of classification models that later collaborate to select the most probable unknown word from multiple candidates. Given a classification model, the group-based ranking evaluation (GRE) is applied to construct a training dataset for learning the succeeding model, by weighing each of its candidates according to their ranks and correctness when the candidates of an unknown word are considered as one group. A number of experiments have been conducted on a large Thai medical text to evaluate performance of the proposed group-based ranking evaluation approach, namely V-GRE, compared to the conventional naïve Bayes classifier and our vanilla version without ensemble learning. As the result, the proposed method achieves an accuracy of 90.93±0.50% when the first rank is selected while it gains 97.26±0.26% when the top-ten candidates are considered, that is 8.45% and 6.79% improvement over the conventional record-based naïve Bayes classifier and the vanilla version. Another result on applying only best features show 93.93±0.22% and up to 98.85±0.15% accuracy for top-1 and top-10, respectively. They are 3.97% and 9.78% improvement over naive Bayes and the vanilla version. Finally, an error analysis is given.
NASA Astrophysics Data System (ADS)
Ehrentreich, F.; Dietze, U.; Meyer, U.; Abbas, S.; Schulz, H.
1995-04-01
It is a main task within the SpecInfo-Project to develop interpretation tools that can handle a great deal more of the complicated, more specific spectrum-structure-correlations. In the first step the empirical knowledge about the assignment of structural groups and their characteristic IR-bands has been collected from literature and represented in a computer readable well-structured form. Vague, verbal rules are managed by introduction of linguistic variables. The next step was the development of automatic rule generating procedures. We had combined and enlarged the IDIOTS algorithm with the algorithm by Blaffert relying on set theory. The procedures were successfully applied to the SpecInfo database. The realization of the preceding items is a prerequisite for the improvement of the computerized structure elucidation procedure.
Pre-Session Satiation as a Treatment for Stereotypy During Group Activities.
Rispoli, Mandy; Camargo, Síglia Hoher; Neely, Leslie; Gerow, Stephanie; Lang, Russell; Goodwyn, Fara; Ninci, Jennifer
2014-05-01
Individuals with developmental disabilities may engage in automatically reinforced behaviors that may interfere with learning opportunities. Manipulation of motivating operations has been shown to reduce automatically maintained behavior in some individuals. Considering behavioral indicators of satiation may assist in identifying the point at which an abolishing operation has begun to effect behavior. The purpose of this study was to evaluate the effects of pre-session satiation of automatic reinforcement on subsequent levels of stereotypy and activity engagement during group activities for three males ages 5 to 13 years with developmental disabilities. Following functional analyses with analogue conditions, an alternating treatment design compared a pre-session access to stereotypy condition with a no-pre-session access condition prior to group activity sessions. Results indicated that pre-session satiation of the putative reinforcer produced by stereotypy was effective in decreasing stereotypy and increasing activity engagement during subsequent group activities for all participants. These findings add to the literature supporting the effectiveness of abolishing operations to decrease automatically maintained stereotypy. © The Author(s) 2013.
Similarity regularized sparse group lasso for cup to disc ratio computation.
Cheng, Jun; Zhang, Zhuo; Tao, Dacheng; Wong, Damon Wing Kee; Liu, Jiang; Baskaran, Mani; Aung, Tin; Wong, Tien Yin
2017-08-01
Automatic cup to disc ratio (CDR) computation from color fundus images has shown to be promising for glaucoma detection. Over the past decade, many algorithms have been proposed. In this paper, we first review the recent work in the area and then present a novel similarity-regularized sparse group lasso method for automated CDR estimation. The proposed method reconstructs the testing disc image based on a set of reference disc images by integrating the similarity between testing and the reference disc images with the sparse group lasso constraints. The reconstruction coefficients are then used to estimate the CDR of the testing image. The proposed method has been validated using 650 images with manually annotated CDRs. Experimental results show an average CDR error of 0.0616 and a correlation coefficient of 0.7, outperforming other methods. The areas under curve in the diagnostic test reach 0.843 and 0.837 when manual and automatically segmented discs are used respectively, better than other methods as well.
Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone
NASA Astrophysics Data System (ADS)
Xia, G.; Hu, C.
2018-04-01
The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.
Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K
2017-10-01
Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.
[Study on the automatic parameters identification of water pipe network model].
Jia, Hai-Feng; Zhao, Qi-Feng
2010-01-01
Based on the problems analysis on development and application of water pipe network model, the model parameters automatic identification is regarded as a kernel bottleneck of model's application in water supply enterprise. The methodology of water pipe network model parameters automatic identification based on GIS and SCADA database is proposed. Then the kernel algorithm of model parameters automatic identification is studied, RSA (Regionalized Sensitivity Analysis) is used for automatic recognition of sensitive parameters, and MCS (Monte-Carlo Sampling) is used for automatic identification of parameters, the detail technical route based on RSA and MCS is presented. The module of water pipe network model parameters automatic identification is developed. At last, selected a typical water pipe network as a case, the case study on water pipe network model parameters automatic identification is conducted and the satisfied results are achieved.
Brain connectomics imaging in schizophrenia study
NASA Astrophysics Data System (ADS)
Tseng, Wen-Yih Isaac; Chen, Yu-Jen; Hsu, Yung-Chin
2017-04-01
Schizophrenia is a debilitating mental disorder of which the biological underpinning is still unclear. Increasing evidence in neuroscience has indicated that schizophrenia arises from abnormal connections within or between networks, hence called dysconnectvity syndrome. Recently, we established an automatic method to analyze integrity of the white matter tracts over the whole brain based on diffusion MRI data, named tract-based automatic analysis (TBAA), and used this method to study white matter connection in patients with schizophrenia. We found that alteration of tract integrity is hereditary and inherent; it is found in siblings and in patients in the early phase of disease. Moreover, patients with good treatment outcome and those with poor outcome show distinctly different patterns of alterations, suggesting that these two groups of patients might be distinguishable based on the difference in tract alteration. In summary, the altered tracts revealed by TBAA might become potential biomarkers or trait markers for schizophrenia.
Automatic classification of visual evoked potentials based on wavelet decomposition
NASA Astrophysics Data System (ADS)
Stasiakiewicz, Paweł; Dobrowolski, Andrzej P.; Tomczykiewicz, Kazimierz
2017-04-01
Diagnosis of part of the visual system, that is responsible for conducting compound action potential, is generally based on visual evoked potentials generated as a result of stimulation of the eye by external light source. The condition of patient's visual path is assessed by set of parameters that describe the time domain characteristic extremes called waves. The decision process is compound therefore diagnosis significantly depends on experience of a doctor. The authors developed a procedure - based on wavelet decomposition and linear discriminant analysis - that ensures automatic classification of visual evoked potentials. The algorithm enables to assign individual case to normal or pathological class. The proposed classifier has a 96,4% sensitivity at 10,4% probability of false alarm in a group of 220 cases and area under curve ROC equals to 0,96 which, from the medical point of view, is a very good result.
Automatic mine detection based on multiple features
NASA Astrophysics Data System (ADS)
Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.
2000-08-01
Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.
Empirical study of alginate impression materials by customized proportioning system
2016-01-01
PURPOSE Alginate mixers available in the market do not have the automatic proportioning unit. In this study, an automatic proportioning unit for the alginate mixer and controller software were designed and produced for a new automatic proportioning unit. With this device, it was ensured that proportioning operation could arrange weight-based alginate impression materials. MATERIALS AND METHODS The variation of coefficient in the tested groups was compared with the manual proportioning. Compression tension and tear tests were conducted to determine the mechanical properties of alginate impression materials. The experimental data were statistically analyzed using one way ANOVA and Tukey test at the 0.05 level of significance. RESULTS No statistically significant differences in modulus of elastisity (P>0.3), tensional/compresional strength (P>0.3), resilience (P>0.2), strain in failure (P>0.4), and tear energy (P>0.7) of alginate impression materials were seen. However, a decrease in the standard deviation of tested groups was observed when the customized machine was used. To verify the efficiency of the system, powder and powder/water mixing were weighed and significant decrease was observed. CONCLUSION It was possible to obtain more mechanically stable alginate impression materials by using the custom-made proportioning unit. PMID:27826387
Clerkin, Elise M; Fisher, Christopher R; Sherman, Jeffrey W; Teachman, Bethany A
2014-01-01
This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n = 28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n = 31). Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person's ability to use reflective processing to overcome biased automatic processing. Copyright © 2013 Elsevier Ltd. All rights reserved.
Attention and reach-to-grasp movements in Parkinson's disease.
Lu, Cathy; Bharmal, Aamir; Kiss, Zelma H; Suchowersky, Oksana; Haffenden, Angela M
2010-08-01
The role of attention in grasping movements directed at common objects has not been examined in Parkinson's disease (PD), though these movements are critical to activities of daily living. Our primary objective was to determine whether patients with PD demonstrate automaticity in grasping movements directed toward common objects. Automaticity is assumed when tasks can be performed with little or no interference from concurrent tasks. Grasping performance in three patient groups (newly diagnosed, moderate, and advanced/surgically treated PD) on and off of their medication or deep brain stimulation was compared to performance in an age-matched control group. Automaticity was demonstrated by the absence of a decrement in grasping performance when attention was consumed by a concurrent spatial-visualization task. Only the control group and newly diagnosed PD group demonstrated automaticity in their grasping movements. The moderate and advanced PD groups did not demonstrate automaticity. Furthermore, the well-known effects of pharmacotherapy and surgical intervention on movement speed and muscle activation patterns did not appear to reduce the impact of attention-demanding tasks on grasping movements in those with moderate to advanced PD. By the moderate stage of PD, grasping is an attention-demanding process; this change is not ameliorated by dopaminergic or surgical treatments. These findings have important implications for activities of daily living, as devoting attention to the simplest of daily tasks would interfere with complex activities and potentially exacerbate fatigue.
Casaseca-de-la-Higuera, Pablo; Simmross-Wattenberg, Federico; Martín-Fernández, Marcos; Alberola-López, Carlos
2009-07-01
Discontinuation of mechanical ventilation is a challenging task that involves a number of subtle clinical issues. The gradual removal of the respiratory support (referred to as weaning) should be performed as soon as autonomous respiration can be sustained. However, the prediction rate of successful extubation is still below 25% based on previous studies. Construction of an automatic system that provides information on extubation readiness is thus desirable. Recent works have demonstrated that the breathing pattern variability is a useful extubation readiness indicator, with improving performance when multiple respiratory signals are jointly processed. However, the existing methods for predictor extraction present several drawbacks when length-limited time series are to be processed in heterogeneous groups of patients. In this paper, we propose a model-based methodology for automatic readiness prediction. It is intended to deal with multichannel, nonstationary, short records of the breathing pattern. Results on experimental data yield an 87.27% of successful readiness prediction, which is in line with the best figures reported in the literature. A comparative analysis shows that our methodology overcomes the shortcomings of so far proposed methods when applied to length-limited records on heterogeneous groups of patients.
Automatic provisioning, deployment and orchestration for load-balancing THREDDS instances
NASA Astrophysics Data System (ADS)
Cofino, A. S.; Fernández-Tejería, S.; Kershaw, P.; Cimadevilla, E.; Petri, R.; Pryor, M.; Stephens, A.; Herrera, S.
2017-12-01
THREDDS is a widely used web server to provide to different scientific communities with data access and discovery. Due to THREDDS's lack of horizontal scalability and automatic configuration management and deployment, this service usually deals with service downtimes and time consuming configuration tasks, mainly when an intensive use is done as is usual within the scientific community (e.g. climate). Instead of the typical installation and configuration of a single or multiple independent THREDDS servers, manually configured, this work presents an automatic provisioning, deployment and orchestration cluster of THREDDS servers. This solution it's based on Ansible playbooks, used to control automatically the deployment and configuration setup on a infrastructure and to manage the datasets available in THREDDS instances. The playbooks are based on modules (or roles) of different backends and frontends load-balancing setups and solutions. The frontend load-balancing system enables horizontal scalability by delegating requests to backend workers, consisting in a variable number of instances for the THREDDS server. This implementation allows to configure different infrastructure and deployment scenario setups, as more workers are easily added to the cluster by simply declaring them as Ansible variables and executing the playbooks, and also provides fault-tolerance and better reliability since if any of the workers fail another instance of the cluster can take over it. In order to test the solution proposed, two real scenarios are analyzed in this contribution: The JASMIN Group Workspaces at CEDA and the User Data Gateway (UDG) at the Data Climate Service from the University of Cantabria. On the one hand, the proposed configuration has provided CEDA with a higher level and more scalable Group Workspaces (GWS) service than the previous one based on Unix permissions, improving also the data discovery and data access experience. On the other hand, the UDG has improved its scalability by allowing requests to be distributed to the backend workers instead of being served by a unique THREDDS worker. As a conclusion the proposed configuration supposes a significant improvement with respect to configurations based on non-collaborative THREDDS' instances.
NASA Astrophysics Data System (ADS)
Patanè, Domenico; Ferrari, Ferruccio; Giampiccolo, Elisabetta; Gresta, Stefano
Few automated data acquisition and processing systems operate on mainframes, some run on UNIX-based workstations and others on personal computers, equipped with either DOS/WINDOWS or UNIX-derived operating systems. Several large and complex software packages for automatic and interactive analysis of seismic data have been developed in recent years (mainly for UNIX-based systems). Some of these programs use a variety of artificial intelligence techniques. The first operational version of a new software package, named PC-Seism, for analyzing seismic data from a local network is presented in Patanè et al. (1999). This package, composed of three separate modules, provides an example of a new generation of visual object-oriented programs for interactive and automatic seismic data-processing running on a personal computer. In this work, we mainly discuss the automatic procedures implemented in the ASDP (Automatic Seismic Data-Processing) module and real time application to data acquired by a seismic network running in eastern Sicily. This software uses a multi-algorithm approach and a new procedure MSA (multi-station-analysis) for signal detection, phase grouping and event identification and location. It is designed for an efficient and accurate processing of local earthquake records provided by single-site and array stations. Results from ASDP processing of two different data sets recorded at Mt. Etna volcano by a regional network are analyzed to evaluate its performance. By comparing the ASDP pickings with those revised manually, the detection and subsequently the location capabilities of this software are assessed. The first data set is composed of 330 local earthquakes recorded in the Mt. Etna erea during 1997 by the telemetry analog seismic network. The second data set comprises about 970 automatic locations of more than 2600 local events recorded at Mt. Etna during the last eruption (July 2001) at the present network. For the former data set, a comparison of the automatic results with the manual picks indicates that the ASDP module can accurately pick 80% of the P-waves and 65% of S-waves. The on-line application on the latter data set shows that automatic locations are affected by larger errors, due to the preliminary setting of the configuration parameters in the program. However, both automatic ASDP and manual hypocenter locations are comparable within the estimated error bounds. New improvements of the PC-Seism software for on-line analysis are also discussed.
Deeley, M A; Chen, A; Datteri, R; Noble, J; Cmelak, A; Donnelly, E; Malcolm, A; Moretti, L; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Yei, F; Koyama, T; Ding, G X; Dawant, B M
2011-01-01
The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation (STAPLE) algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8–0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4–0.5. Similarly low DSC have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (−4.3, +5.4) mm for the automatic system to (−3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms. PMID:21725140
NASA Astrophysics Data System (ADS)
Deeley, M. A.; Chen, A.; Datteri, R.; Noble, J. H.; Cmelak, A. J.; Donnelly, E. F.; Malcolm, A. W.; Moretti, L.; Jaboin, J.; Niermann, K.; Yang, Eddy S.; Yu, David S.; Yei, F.; Koyama, T.; Ding, G. X.; Dawant, B. M.
2011-07-01
The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice similarity coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8-0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4-0.5. Similarly low DSCs have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (-4.3, +5.4) mm for the automatic system to (-3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms.
NASA Astrophysics Data System (ADS)
Wojenski, Andrzej; Kasprowicz, Grzegorz; Pozniak, Krzysztof T.; Romaniuk, Ryszard
2013-10-01
The paper describes a concept of automatic firmware generation for reconfigurable measurement systems, which uses FPGA devices and measurement cards in FMC standard. Following sections are described in details: automatic HDL code generation for FPGA devices, automatic communication interfaces implementation, HDL drivers for measurement cards, automatic serial connection between multiple measurement backplane boards, automatic build of memory map (address space), automatic generated firmware management. Presented solutions are required in many advanced measurement systems, like Beam Position Monitors or GEM detectors. This work is a part of a wider project for automatic firmware generation and management of reconfigurable systems. Solutions presented in this paper are based on previous publication in SPIE.
Segmentation of stereo terrain images
NASA Astrophysics Data System (ADS)
George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.
2000-06-01
We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.
Zhang, Jing; Lipp, Ottmar V; Hu, Ping
2017-01-01
The current study investigated the interactive effects of individual differences in automatic emotion regulation (AER) and primed emotion regulation strategy on skin conductance level (SCL) and heart rate during provoked anger. The study was a 2 × 2 [AER tendency (expression vs. control) × priming (expression vs. control)] between subject design. Participants were assigned to two groups according to their performance on an emotion regulation-IAT (differentiating automatic emotion control tendency and automatic emotion expression tendency). Then participants of the two groups were randomly assigned to two emotion regulation priming conditions (emotion control priming or emotion expression priming). Anger was provoked by blaming participants for slow performance during a subsequent backward subtraction task. In anger provocation, SCL of individuals with automatic emotion control tendencies in the control priming condition was lower than of those with automatic emotion control tendencies in the expression priming condition. However, SCL of individuals with automatic emotion expression tendencies did no differ in the automatic emotion control priming or the automatic emotion expression priming condition. Heart rate during anger provocation was higher in individuals with automatic emotion expression tendencies than in individuals with automatic emotion control tendencies regardless of priming condition. This pattern indicates an interactive effect of individual differences in AER and emotion regulation priming on SCL, which is an index of emotional arousal. Heart rate was only sensitive to the individual differences in AER, and did not reflect this interaction. This finding has implications for clinical studies of the use of emotion regulation strategy training suggesting that different practices are optimal for individuals who differ in AER tendencies.
Yavuzer, Yasemin; Karataş, Zeynep
2013-01-01
This study aimed to examine the mediating role of anger in the relationship between automatic thoughts and physical aggression in adolescents. The study included 224 adolescents in the 9th grade of 3 different high schools in central Burdur during the 2011-2012 academic year. Participants completed the Aggression Questionnaire and Automatic Thoughts Scale in their classrooms during counseling sessions. Data were analyzed using simple and multiple linear regression analysis. There were positive correlations between the adolescents' automatic thoughts, and physical aggression, and anger. According to regression analysis, automatic thoughts effectively predicted the level of physical aggression (b= 0.233, P < 0.001)) and anger (b= 0.325, P < 0.001). Analysis of the mediating role of anger showed that anger fully mediated the relationship between automatic thoughts and physical aggression (Sobel z = 5.646, P < 0.001). Anger fully mediated the relationship between automatic thoughts and physical aggression. Providing adolescents with anger management skills training is very important for the prevention of physical aggression. Such training programs should include components related to the development of an awareness of dysfunctional and anger-triggering automatic thoughts, and how to change them. As the study group included adolescents from Burdur, the findings can only be generalized to groups with similar characteristics.
Automatic Clustering and Thickness Measurement of Anatomical Variants of the Human Perirhinal Cortex
Xie, Long; Pluta, John; Wang, Hongzhi; Das, Sandhitsu R.; Mancuso, Lauren; Kliot, Dasha; Avants, Brian B.; Ding, Song-Lin; Wolk, David A.; Yushkevich, Paul A.
2015-01-01
The entorhinal cortex (ERC) and the perirhinal cortex (PRC) are subregions of the medial temporal lobe (MTL) that play important roles in episodic memory representations, as well as serving as a conduit between other neocortical areas and the hippocampus. They are also the sites where neuronal damage first occurs in Alzheimer’s disease (AD). The ability to automatically quantify the volume and thickness of the ERC and PRC is desirable because these localized measures can potentially serve as better imaging biomarkers for AD and other neurodegenerative diseases. However, large anatomical variation in the PRC makes it a challenging area for analysis. In order to address this problem, we propose an automatic segmentation, clustering, and thickness measurement approach that explicitly accounts for anatomical variation. The approach is targeted to highly anisotropic (0.4×0.4×2.0mm3) T2-weighted MRI scans that are preferred by many authors for detailed imaging of the MTL, but which pose challenges for segmentation and shape analysis. After automatically labeling MTL substructures using multi-atlas segmentation, our method clusters subjects into groups based on the shape of the PRC, constructs unbiased population templates for each group, and uses the smooth surface representations obtained during template construction to extract regional thickness measurements in the space of each subject. The proposed thickness measures are evaluated in the context of discrimination between patients with Mild Cognitive Impairment (MCI) and normal controls (NC). PMID:25320785
Feature-Based Morphometry: Discovering Group-related Anatomical Patterns
Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal
2015-01-01
This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047
Chatter detection in milling process based on VMD and energy entropy
NASA Astrophysics Data System (ADS)
Liu, Changfu; Zhu, Lida; Ni, Chenbing
2018-05-01
This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.
Kawamoto, Kensaku; Lobach, David F
2003-01-01
Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.
Rule groupings: An approach towards verification of expert systems
NASA Technical Reports Server (NTRS)
Mehrotra, Mala
1991-01-01
Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units.
Identification of forensic samples by using an infrared-based automatic DNA sequencer.
Ricci, Ugo; Sani, Ilaria; Klintschar, Michael; Cerri, Nicoletta; De Ferrari, Francesco; Giovannucci Uzielli, Maria Luisa
2003-06-01
We have recently introduced a new protocol for analyzing all core loci of the Federal Bureau of Investigation's (FBI) Combined DNA Index System (CODIS) with an infrared (IR) automatic DNA sequencer (LI-COR 4200). The amplicons were labeled with forward oligonucleotide primers, covalently linked to a new infrared fluorescent molecule (IRDye 800). The alleles were displayed as familiar autoradiogram-like images with real-time detection. This protocol was employed for paternity testing, population studies, and identification of degraded forensic samples. We extensively analyzed some simulated forensic samples and mixed stains (blood, semen, saliva, bones, and fixed archival embedded tissues), comparing the results with donor samples. Sensitivity studies were also performed for the four multiplex systems. Our results show the efficiency, reliability, and accuracy of the IR system for the analysis of forensic samples. We also compared the efficiency of the multiplex protocol with ultraviolet (UV) technology. Paternity tests, undegraded DNA samples, and real forensic samples were analyzed with this approach based on IR technology and with UV-based automatic sequencers in combination with commercially-available kits. The comparability of the results with the widespread UV methods suggests that it is possible to exchange data between laboratories using the same core group of markers but different primer sets and detection methods.
The Naive Misuse of Power: Nonconscious Sources of Sexual Harassment.
ERIC Educational Resources Information Center
Bargh, John A.; Raymond, Paula
1995-01-01
Considers sexual harassment from the perspective of abuse of power, and discusses the possibility of having power within a situation that automatically and nonconsciously triggers a sexuality schema, just as racial or gender features automatically trigger stereotypes of that group. The possible origins of the automatic power/sex linkage and its…
A statistical parts-based appearance model of inter-subject variability.
Toews, Matthew; Collins, D Louis; Arbel, Tal
2006-01-01
In this article, we present a general statistical parts-based model for representing the appearance of an image set, applied to the problem of inter-subject MR brain image matching. In contrast with global image representations such as active appearance models, the parts-based model consists of a collection of localized image parts whose appearance, geometry and occurrence frequency are quantified statistically. The parts-based approach explicitly addresses the case where one-to-one correspondence does not exist between subjects due to anatomical differences, as parts are not expected to occur in all subjects. The model can be learned automatically, discovering structures that appear with statistical regularity in a large set of subject images, and can be robustly fit to new images, all in the presence of significant inter-subject variability. As parts are derived from generic scale-invariant features, the framework can be applied in a wide variety of image contexts, in order to study the commonality of anatomical parts or to group subjects according to the parts they share. Experimentation shows that a parts-based model can be learned from a large set of MR brain images, and used to determine parts that are common within the group of subjects. Preliminary results indicate that the model can be used to automatically identify distinctive features for inter-subject image registration despite large changes in appearance.
Hsieh, Thomas M; Liu, Yi-Min; Liao, Chun-Chih; Xiao, Furen; Chiang, I-Jen; Wong, Jau-Min
2011-08-26
In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system. The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.
Predictors of Mental Health Symptoms, Automatic Thoughts, and Self-Esteem Among University Students.
Hiçdurmaz, Duygu; İnci, Figen; Karahan, Sevilay
2017-01-01
University youth is a risk group regarding mental health, and many mental health problems are frequent in this group. Sociodemographic factors such as level of income and familial factors such as relationship with father are reported to be associated with mental health symptoms, automatic thoughts, and self-esteem. Also, there are interrelations between mental health problems, automatic thoughts, and self-esteem. The extent of predictive effect of each of these variables on automatic thoughts, self-esteem, and mental health symptoms is not known. We aimed to determine the predictive factors of mental health symptoms, automatic thoughts, and self-esteem in university students. Participants were 530 students enrolled at a university in Turkey, during 2014-2015 academic year. Data were collected using the student information form, the Brief Symptom Inventory, the Automatic Thoughts Questionnaire, and the Rosenberg Self-Esteem Scale. Mental health symptoms, self-esteem, perception of the relationship with the father, and level of income as a student significantly predicted automatic thoughts. Automatic thoughts, mental health symptoms, participation in family decisions, and age had significant predictive effects on self-esteem. Finally, automatic thoughts, self-esteem, age, and perception of the relationship with the father had significant predictive effects on mental health symptoms. The predictive factors revealed in our study provide important information to practitioners and researchers by showing the elements that need to be screened for mental health of university students and issues that need to be included in counseling activities.
Model-Based Reasoning: Using Visual Tools to Reveal Student Learning
ERIC Educational Resources Information Center
Luckie, Douglas; Harrison, Scott H.; Ebert-May, Diane
2011-01-01
Using visual models is common in science and should become more common in classrooms. Our research group has developed and completed studies on the use of a visual modeling tool, the Concept Connector. This modeling tool consists of an online concept mapping Java applet that has automatic scoring functions we refer to as Robograder. The Concept…
Ritter, Philippe; Delnoy, Peter Paul H M; Padeletti, Luigi; Lunati, Maurizio; Naegele, Herbert; Borri-Brunetto, Alberto; Silvestre, Jorge
2012-09-01
Non-response rate to cardiac resynchronization therapy (CRT) might be decreased by optimizing device programming. The Clinical Evaluation on Advanced Resynchronization (CLEAR) study aimed to assess the effects of CRT with automatically optimized atrioventricular (AV) and interventricular (VV) delays, based on a Peak Endocardial Acceleration (PEA) signal system. This multicentre, single-blind study randomized patients in a 1 : 1 ratio to CRT optimized either automatically by the PEA-based system, or according to centres' usual practices, mostly by echocardiography. Patients had heart failure (HF) New York Heart Association (NYHA) functional class III/IV, left ventricular ejection fraction (LVEF) <35%, QRS duration >150 or >120 ms with mechanical dyssynchrony. Follow-up was 1 year. The primary endpoint was the proportion of patients who improved their condition at 1 year, based on a composite of all-cause death, HF hospitalizations, NYHA class, and quality of life. In all, 268 patients in sinus rhythm (63% men; mean age: 73.1 ± 9.9 years; mean NYHA: 3.0 ± 0.3; mean LVEF: 27.1 ± 8.1%; and mean QRS duration: 160.1 ± 22.0 ms) were included and 238 patients were randomized, 123 to PEA and 115 to the control group. At 1 year, 76% of patients assigned to PEA were classified as improved, vs. 62% in the control group (P= 0.0285). The percentage of patients with improved NYHA class was significantly (P= 0.0020) higher in the PEA group than in controls. Fatal and non-fatal adverse events were evenly distributed between the groups. PEA-based optimization of CRT in HF patients significantly increased the proportion of patients who improved with therapy, mainly through improved NYHA class, after 1 year of follow-up.
Method for automatic measurement of second language speaking proficiency
NASA Astrophysics Data System (ADS)
Bernstein, Jared; Balogh, Jennifer
2005-04-01
Spoken language proficiency is intuitively related to effective and efficient communication in spoken interactions. However, it is difficult to derive a reliable estimate of spoken language proficiency by situated elicitation and evaluation of a person's communicative behavior. This paper describes the task structure and scoring logic of a group of fully automatic spoken language proficiency tests (for English, Spanish and Dutch) that are delivered via telephone or Internet. Test items are presented in spoken form and require a spoken response. Each test is automatically-scored and primarily based on short, decontextualized tasks that elicit integrated listening and speaking performances. The tests present several types of tasks to candidates, including sentence repetition, question answering, sentence construction, and story retelling. The spoken responses are scored according to the lexical content of the response and a set of acoustic base measures on segments, words and phrases, which are scaled with IRT methods or parametrically combined to optimize fit to human listener judgments. Most responses are isolated spoken phrases and sentences that are scored according to their linguistic content, their latency, and their fluency and pronunciation. The item development procedures and item norming are described.
Enhancing Collaborative Learning through Group Intelligence Software
NASA Astrophysics Data System (ADS)
Tan, Yin Leng; Macaulay, Linda A.
Employers increasingly demand not only academic excellence from graduates but also excellent interpersonal skills and the ability to work collaboratively in teams. This paper discusses the role of Group Intelligence software in helping to develop these higher order skills in the context of an enquiry based learning (EBL) project. The software supports teams in generating ideas, categorizing, prioritizing, voting and multi-criteria decision making and automatically generates a report of each team session. Students worked in a Group Intelligence lab designed to support both face to face and computer-mediated communication and employers provided feedback at two key points in the year long team project. Evaluation of the effectiveness of Group Intelligence software in collaborative learning was based on five key concepts of creativity, participation, productivity, engagement and understanding.
Kim, Young Jae; Kim, Kwang Gi
2018-01-01
Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image. Finally, we detected the drusen through Renyi's entropy threshold algorithm. We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity. As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98). In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p < 0.01), showing the high reliability of the proposed automatic method. We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.
Roberts, Walter; Fillmore, Mark T.; Milich, Richard
2011-01-01
Researchers in the cognitive sciences recognize a fundamental distinction between automatic and intentional mechanisms of inhibitory control. The use of eye-tracking tasks to assess selective attention has led to a better understanding of this distinction in specific populations such as children with attention-deficit/hyperactivity disorder (ADHD). This study examined automatic and intentional inhibitory control mechanisms in adults with ADHD using a saccadic interference (SI) task and a delayed ocular response (DOR) task. Thirty adults with ADHD were compared to 27 comparison adults on measures of inhibitory control. The DOR task showed that adults with ADHD were less able than comparison adults to inhibit a reflexive saccade towards the sudden appearance of a stimulus in the periphery. However, SI task performance showed that the ADHD group did not differ significantly from the comparison group on a measure of automatic inhibitory control. These findings suggest a dissociation between automatic and intentional inhibitory deficits in adults with ADHD. PMID:21058752
Lv, Peijie; Liu, Jie; Zhang, Rui; Jia, Yan
2015-01-01
Objective To assess the lesion conspicuity and image quality in CT evaluation of small (≤ 3 cm) hepatocellular carcinomas (HCCs) using automatic tube voltage selection (ATVS) and automatic tube current modulation (ATCM) with or without iterative reconstruction. Materials and Methods One hundred and five patients with 123 HCC lesions were included. Fifty-seven patients were scanned using both ATVS and ATCM and images were reconstructed using either filtered back-projection (FBP) (group A1) or sinogram-affirmed iterative reconstruction (SAFIRE) (group A2). Forty-eight patients were imaged using only ATCM, with a fixed tube potential of 120 kVp and FBP reconstruction (group B). Quantitative parameters (image noise in Hounsfield unit and contrast-to-noise ratio of the aorta, the liver, and the hepatic tumors) and qualitative visual parameters (image noise, overall image quality, and lesion conspicuity as graded on a 5-point scale) were compared among the groups. Results Group A2 scanned with the automatically chosen 80 kVp and 100 kVp tube voltages ranked the best in lesion conspicuity and subjective and objective image quality (p values ranging from < 0.001 to 0.004) among the three groups, except for overall image quality between group A2 and group B (p = 0.022). Group A1 showed higher image noise (p = 0.005) but similar lesion conspicuity and overall image quality as compared with group B. The radiation dose in group A was 19% lower than that in group B (p = 0.022). Conclusion CT scanning with combined use of ATVS and ATCM and image reconstruction with SAFIRE algorithm provides higher lesion conspicuity and better image quality for evaluating small hepatic HCCs with radiation dose reduction. PMID:25995682
Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms
NASA Astrophysics Data System (ADS)
Gao, Connie W.; Allen, Joshua W.; Green, William H.; West, Richard H.
2016-06-01
Reaction Mechanism Generator (RMG) constructs kinetic models composed of elementary chemical reaction steps using a general understanding of how molecules react. Species thermochemistry is estimated through Benson group additivity and reaction rate coefficients are estimated using a database of known rate rules and reaction templates. At its core, RMG relies on two fundamental data structures: graphs and trees. Graphs are used to represent chemical structures, and trees are used to represent thermodynamic and kinetic data. Models are generated using a rate-based algorithm which excludes species from the model based on reaction fluxes. RMG can generate reaction mechanisms for species involving carbon, hydrogen, oxygen, sulfur, and nitrogen. It also has capabilities for estimating transport and solvation properties, and it automatically computes pressure-dependent rate coefficients and identifies chemically-activated reaction paths. RMG is an object-oriented program written in Python, which provides a stable, robust programming architecture for developing an extensible and modular code base with a large suite of unit tests. Computationally intensive functions are cythonized for speed improvements.
Gül, A I; Simsek, G; Karaaslan, Ö; Inanir, S
2015-08-01
Automatic thoughts are measurable cognitive markers of the psychopathology and coping styles of individuals. This study measured and compared the automatic thoughts of patients with generalized anxiety disorder (GAD), major depressive disorder (MDD), and generalized social phobia (GSP). Fifty-two patients with GAD, 53 with MDD, and 50 with GSP and 52 healthy controls completed the validated Automatic Thoughts Questionnaire (ATQ) and a structured psychiatric interview. Patients with GAD, MDD, and GSP also completed the validated Generalized Anxiety Disorder-7 questionnaire, the Beck Depression Inventory (BDI), and the Liebowitz Social Anxiety Scale (LSAS) to determine the severity of their illnesses. All scales were completed before treatment and after diagnosis. The ATQ scores of all pairs of groups were compared. The ATQ scores of the GAD, MDD, and GSP groups were significantly higher than were those of the control group. We also found significant correlations among scores on the GAD-7, BDI, and LSAS. The mean age of patients with GSP was lower than was that of the other groups (30.90 ± 8.35). The significantly higher ATQ scores of the MDD, GAD, and GSP groups, compared with the control group, underscore the common cognitive psychopathology characterizing these three disorders. This finding confirms that similar cognitive therapy approaches should be effective for these patients. This study is the first to compare GAD, MDD, and GSP from a cognitive perspective.
Hides, Julie A; Endicott, Timothy; Mendis, M Dilani; Stanton, Warren R
2016-07-01
To investigate whether motor control training alters automatic contraction of abdominal muscles in elite cricketers with low back pain (LBP) during performance of a simulated unilateral weight-bearing task. Clinical trial. 26 male elite-cricketers attended a 13-week cricket training camp. Prior to the camp, participants were allocated to a LBP or asymptomatic group. Real-time ultrasound imaging was used to assess automatic abdominal muscle response to axial loading. During the camp, the LBP group performed a staged motor control training program. Following the camp, the automatic response of the abdominal muscles was re-assessed. At pre-camp assessment, when participants were axially loaded with 25% of their own bodyweight, the LBP group showed a 15.5% thicker internal oblique (IO) muscle compared to the asymptomatic group (p = 0.009). The post-camp assessment showed that participants in the LBP group demonstrated less contraction of the IO muscle in response to axial loading compared with the asymptomatic group. A trend was found in the automatic recruitment pattern of the transversus abdominis (p = 0.08). Motor control training normalized excessive contraction of abdominal muscles in response to a low load task. This may be a useful strategy for rehabilitation of cricketers with LBP. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Robust Automatic Ionospheric O/X Mode Separation Technique for Vertical Incidence Sounders
NASA Astrophysics Data System (ADS)
Harris, T. J.; Pederick, L. H.
2017-12-01
The sounding of the ionosphere by a vertical incidence sounder (VIS) is the oldest and most common technique for determining the state of the ionosphere. The automatic extraction of relevant ionospheric parameters from the ionogram image, referred to as scaling, is important for the effective utilization of data from large ionospheric sounder networks. Due to the Earth's magnetic field, the ionosphere is birefringent at radio frequencies, so a VIS will typically see two distinct returns for each frequency. For the automatic scaling of ionograms, it is highly desirable to be able to separate the two modes. Defence Science and Technology Group has developed a new VIS solution which is based on direct digital receiver technology and includes an algorithm to separate the O and X modes. This algorithm can provide high-quality separation even in difficult ionospheric conditions. In this paper we describe the algorithm and demonstrate its consistency and reliability in successfully separating 99.4% of the ionograms during a 27 day experimental campaign under sometimes demanding ionospheric conditions.
Automatically producing tailored web materials for public administration
NASA Astrophysics Data System (ADS)
Colineau, Nathalie; Paris, Cécile; Vander Linden, Keith
2013-06-01
Public administration organizations commonly produce citizen-focused, informational materials describing public programs and the conditions under which citizens or citizen groups are eligible for these programs. The organizations write these materials for generic audiences because of the excessive human resource costs that would be required to produce personalized materials for everyone. Unfortunately, generic materials tend to be longer and harder to understand than materials tailored for particular citizens. Our work explores the feasibility and effectiveness of automatically producing tailored materials. We have developed an adaptive hypermedia application system that automatically produces tailored informational materials and have evaluated it in a series of studies. The studies demonstrate that: (1) subjects prefer tailored materials over generic materials, even if the tailoring requires answering a set of demographic questions first; (2) tailored materials are more effective at supporting subjects in their task of learning about public programs; and (3) the time required to specify the demographic information on which the tailoring is based does not significantly slow down the subjects in their information seeking task.
Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource
Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa
2003-01-01
Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355
In situ control of cardiotomy suction reduces blood trauma.
Tevaearai, H T; Mueller, X M; Horisberger, J; Augstburger, M; Bock, H; Knorr, A; von Segesser, L K
1998-01-01
Cardiotomy suction is known for its deleterious effects on formed and unformed blood elements. The authors investigated an "intelligent" remote controlled automatic suction system. A suction cannula with an optic sensor at its tip was connected to a special closed cardiotomy reservoir. Contact with blood immediately generated a reservoir vacuum from 0 to -100 mmHg, permitting aspiration until the blood was no longer detected (automatic shut off). Blood trauma was evaluated in a bovine model, comparing the automatic suction system vs standard continuous aspiration (control) adjusted to -100 mmHg. After full systemic heparinization, five calves (weight, 62.5 +/- 4.4 kg) for the automatic suction system group, and four (weight, 62.8 +/- 5.1 kg) for the control group, were equipped with a jugular cannula connected via a roller pump to the cardiotomy reservoir. Through a small thoracotomy, a standardized hole was created in the right atrium, allowing for a blood loss of approximately 400 ml/min. The suction cannula was placed into the chest cavity in a fixed position. Blood samples were drawn at regular intervals for cell count and chemistry. Lactate dehydrogenase values, for the automatic suction system and the control groups, respectively, expressed as percent of baseline value, were 88 +/- 14 vs 116 +/- 22 after 1 hr; 94 +/- 16 vs 123 +/- 23 after 2 hr; and 97 +/- 19 vs 140 +/- 48 after 3 hr (p < 0.05). Values for free hemoglobin in plasma (percent of baseline value), for the automatic suction system and the control groups, respectively, were 102 +/- 18 vs 200 +/- 69 after 1 hr; 98 +/- 29 vs 163 +/- 37 after 2 hr; and 94 +/- 37 vs 179 +/- 42 after 3 hr (p < 0.05). Compared with a standard continuous aspiration system, in situ regulation of suction significantly reduces blood trauma.
Additivity of Feature-Based and Symmetry-Based Grouping Effects in Multiple Object Tracking
Wang, Chundi; Zhang, Xuemin; Li, Yongna; Lyu, Chuang
2016-01-01
Multiple object tracking (MOT) is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the “laws of perceptual organization” proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape) among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. “Additive effect” refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The “where” and “what” pathways might have played an important role in the additive grouping effect. PMID:27199875
The chordate proteome history database.
Levasseur, Anthony; Paganini, Julien; Dainat, Jacques; Thompson, Julie D; Poch, Olivier; Pontarotti, Pierre; Gouret, Philippe
2012-01-01
The chordate proteome history database (http://ioda.univ-provence.fr) comprises some 20,000 evolutionary analyses of proteins from chordate species. Our main objective was to characterize and study the evolutionary histories of the chordate proteome, and in particular to detect genomic events and automatic functional searches. Firstly, phylogenetic analyses based on high quality multiple sequence alignments and a robust phylogenetic pipeline were performed for the whole protein and for each individual domain. Novel approaches were developed to identify orthologs/paralogs, and predict gene duplication/gain/loss events and the occurrence of new protein architectures (domain gains, losses and shuffling). These important genetic events were localized on the phylogenetic trees and on the genomic sequence. Secondly, the phylogenetic trees were enhanced by the creation of phylogroups, whereby groups of orthologous sequences created using OrthoMCL were corrected based on the phylogenetic trees; gene family size and gene gain/loss in a given lineage could be deduced from the phylogroups. For each ortholog group obtained from the phylogenetic or the phylogroup analysis, functional information and expression data can be retrieved. Database searches can be performed easily using biological objects: protein identifier, keyword or domain, but can also be based on events, eg, domain exchange events can be retrieved. To our knowledge, this is the first database that links group clustering, phylogeny and automatic functional searches along with the detection of important events occurring during genome evolution, such as the appearance of a new domain architecture.
NASA Astrophysics Data System (ADS)
Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin
2017-03-01
Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.
[Research on automatic external defibrillator based on DSP].
Jing, Jun; Ding, Jingyan; Zhang, Wei; Hong, Wenxue
2012-10-01
Electrical defibrillation is the most effective way to treat the ventricular tachycardia (VT) and ventricular fibrillation (VF). An automatic external defibrillator based on DSP is introduced in this paper. The whole design consists of the signal collection module, the microprocessor controlingl module, the display module, the defibrillation module and the automatic recognition algorithm for VF and non VF, etc. This automatic external defibrillator has achieved goals such as ECG signal real-time acquisition, ECG wave synchronous display, data delivering to U disk and automatic defibrillate when shockable rhythm appears, etc.
2013-01-01
Objective: Long-term memory functioning in autism spectrum disorders (ASDs) is marked by a characteristic pattern of impairments and strengths. Individuals with ASD show impairment in memory tasks that require the processing of relational and contextual information, but spared performance on tasks requiring more item-based, acontextual processing. Two experiments investigated the cognitive mechanisms underlying this memory profile. Method: A sample of 14 children with a diagnosis of high-functioning ASD (age: M = 12.2 years), and a matched control group of 14 typically developing (TD) children (age: M = 12.1 years), participated in a range of behavioral memory tasks in which we measured both relational and item-based memory abilities. They also completed a battery of executive function measures. Results: The ASD group showed specific deficits in relational memory, but spared or superior performance in item-based memory, across all tasks. Importantly, for ASD children, executive ability was significantly correlated with relational memory but not with item-based memory. No such relationship was present in the control group. This suggests that children with ASD atypically employed effortful, executive strategies to retrieve relational (but not item-specific) information, whereas TD children appeared to use more automatic processes. Conclusions: The relational memory impairment in ASD may result from a specific impairment in automatic associative retrieval processes with an increased reliance on effortful and strategic retrieval processes. Our findings allow specific neural predictions to be made regarding the interactive functioning of the hippocampus, prefrontal cortex, and posterior parietal cortex in ASD as a neural network supporting relational memory processing. PMID:24245930
Soto, Fabian A.; Waldschmidt, Jennifer G.; Helie, Sebastien; Ashby, F. Gregory
2013-01-01
Previous evidence suggests that relatively separate neural networks underlie initial learning of rule-based and information-integration categorization tasks. With the development of automaticity, categorization behavior in both tasks becomes increasingly similar and exclusively related to activity in cortical regions. The present study uses multi-voxel pattern analysis to directly compare the development of automaticity in different categorization tasks. Each of three groups of participants received extensive training in a different categorization task: either an information-integration task, or one of two rule-based tasks. Four training sessions were performed inside an MRI scanner. Three different analyses were performed on the imaging data from a number of regions of interest (ROIs). The common patterns analysis had the goal of revealing ROIs with similar patterns of activation across tasks. The unique patterns analysis had the goal of revealing ROIs with dissimilar patterns of activation across tasks. The representational similarity analysis aimed at exploring (1) the similarity of category representations across ROIs and (2) how those patterns of similarities compared across tasks. The results showed that common patterns of activation were present in motor areas and basal ganglia early in training, but only in the former later on. Unique patterns were found in a variety of cortical and subcortical areas early in training, but they were dramatically reduced with training. Finally, patterns of representational similarity between brain regions became increasingly similar across tasks with the development of automaticity. PMID:23333700
Vaginismus and dyspareunia: automatic vs. deliberate disgust responsivity.
Borg, Charmaine; de Jong, Peter J; Schultz, Willibrord Weijmar
2010-06-01
The difficulty of penetration experienced in vaginismus and dyspareunia may at least partly be due to a disgust-induced defensive response. To examine if sex stimuli specifically elicit: (i) automatic disgust-related memory associations; (ii) physiological disgust responsivity; and/or (iii) deliberate expression of disgust/threat. Two single target Implicit Association Task (st-IAT) and electromyography (EMG) were conducted on three groups: vaginismus (N = 24), dyspareunia (N = 24), and control (N = 31) group. st-IAT, to index their initial disgust-related associations and facial EMG for the m. levator labii and m. corrugator supercilii regions. Both clinical groups showed enhanced automatic sex-disgust associations. As a unique physiological expression of disgust, the levator activity was specifically enhanced for the vaginismus group, when exposed to a women-friendly SEX video clip. Also at the deliberate level, specifically the vaginismus group showed enhanced subjective disgust toward SEX pictures and the SEX clip, along with higher threat responses. Supporting the view that disgust is involved in vaginismus and dyspareunia, for both, clinical groups' sex stimuli automatically elicited associations with disgust. Particularly for the vaginismus group, these initial disgust associations persisted during subsequent validation processes and were also evident at the level of facial expression and self-report data. Findings are consistent with the notion that uncontrollable activated associations are involved in eliciting defensive reactions at the prospect of penetration seen in both conditions. Whereas deliberate attitudes, usually linked with the desire for having intercourse, possibly generate the distinction (e.g., severity) between these two conditions.
Low implicit self-esteem and dysfunctional automatic associations in social anxiety disorder.
Glashouwer, Klaske A; Vroling, Maartje S; de Jong, Peter J; Lange, Wolf-Gero; de Keijser, Jos
2013-06-01
Negative automatic associations towards the self and social cues are assumed to play an important role in social anxiety disorder. We tested whether social anxiety disorder patients (n = 45) showed stronger dysfunctional automatic associations than non-clinical controls (n = 45) and panic disorder patients (n = 24) and whether there existed gender differences in this respect. We used a single-target Implicit Association Test and an Implicit Association Test to measure dysfunctional automatic associations with social cues and implicit self-esteem, respectively. Results showed that automatic associations with social cues were more dysfunctional in socially anxious patients than in both control groups, suggesting this might be a specific characteristic of social anxiety disorder. Socially anxious patients showed relatively low implicit self-esteem compared to non-clinical controls, whereas panic disorder patients scored in between both groups. Unexpectedly, we found that lower implicit self-esteem was related to higher severity of social anxiety symptoms in men, whereas no such relationship was found in women. These findings support the view that automatic negative associations with social cues and lowered implicit self-esteem may both help to enhance our understanding of the cognitive processes that underlie social anxiety disorder. Copyright © 2012 Elsevier Ltd. All rights reserved.
Masked Priming Effects in Aphasia: Evidence for Altered Automatic Spreading Activation
Silkes, JoAnn P.; Rogers, Margaret A.
2015-01-01
Purpose Previous research has suggested that impairments of automatic spreading activation may underlie some aphasic language deficits. This study further investigated the status of automatic spreading activation in individuals with aphasia as compared with typical adults. Method Participants were 21 individuals with aphasia (12 fluent, 9 non-fluent) and 31 typical adults. Reaction time data were collected on a lexical decision task with masked repetition primes, assessed at 11 different interstimulus intervals (ISIs). Masked primes were used to assess automatic spreading activation without the confound of conscious processing. The various ISIs were used to assess the time to onset, and duration, of priming effects. Results The control group showed maximal priming in the 200 ms ISI condition, with significant priming at a range of ISIs surrounding that peak. Participants with both fluent and non-fluent aphasia showed maximal priming effects in the 250 ms ISI condition, and primed across a smaller range of ISIs than the control group. Conclusions Results suggest that individuals with aphasia have slowed automatic spreading activation, and impaired maintenance of activation over time, regardless of fluency classification. These findings have implications for understanding aphasic language impairment and for development of aphasia treatments designed directly address automatic language processes. PMID:22411281
Masked priming effects in aphasia: evidence of altered automatic spreading activation.
Silkes, JoAnn P; Rogers, Margaret A
2012-12-01
Previous research has suggested that impairments of automatic spreading activation may underlie some aphasic language deficits. The current study further investigated the status of automatic spreading activation in individuals with aphasia as compared with typical adults. Participants were 21 individuals with aphasia (12 fluent, 9 nonfluent) and 31 typical adults. Reaction time data were collected on a lexical decision task with masked repetition primes, assessed at 11 different interstimulus intervals (ISIs). Masked primes were used to assess automatic spreading activation without the confound of conscious processing. The various ISIs were used to assess the time to onset and duration of priming effects. The control group showed maximal priming in the 200-ms ISI condition, with significant priming at a range of ISIs surrounding that peak. Participants with both fluent and nonfluent aphasia showed maximal priming effects in the 250-ms ISI condition and primed across a smaller range of ISIs than did the control group. Results suggest that individuals with aphasia have slowed automatic spreading activation and impaired maintenance of activation over time, regardless of fluency classification. These findings have implications for understanding aphasic language impairment and for development of aphasia treatments designed to directly address automatic language processes.
A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.
Madan, Hennadii; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga
2017-02-01
Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework. The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images. The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm. The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.
The precursors of double dissociation between reading and spelling in a transparent orthography.
Torppa, Minna; Georgiou, George K; Niemi, Pekka; Lerkkanen, Marja-Kristiina; Poikkeus, Anna-Maija
2017-04-01
Research and clinical practitioners have mixed views whether reading and spelling difficulties should be combined or seen as separate. This study examined the following: (a) if double dissociation between reading and spelling can be identified in a transparent orthography (Finnish) and (b) the cognitive and noncognitive precursors of this phenomenon. Finnish-speaking children (n = 1963) were assessed on reading fluency and spelling in grades 1, 2, 3, and 4. Dissociation groups in reading and spelling were formed based on stable difficulties in grades 1-4. The groups were compared in kindergarten phonological awareness, rapid automatized naming, letter knowledge, home literacy environment, and task-avoidant behavior. The results indicated that the double dissociation groups could be identified even in the context of a highly transparent orthography: 41 children were unexpected poor spellers (SD), 36 were unexpected poor readers (RD), and 59 were poor in both reading and spelling (RSD). The RSD group performed poorest on all cognitive skills and showed the most task-avoidant behavior, the RD group performed poorly particularly on rapid automatized naming and letter knowledge, and the SD group had difficulties on phonological awareness and letter knowledge. Fathers' shared book reading was less frequent in the RD and RSD groups than in the other groups. The findings suggest that there are discernible double dissociation groups with distinct cognitive profiles. This further suggests that the identification of difficulties in Finnish and the planning of teaching and remediation practices should include both reading and spelling assessments.
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
2002-01-01
In this paper we describe the extension of the CAPO parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report first results for several benchmark codes and one full application that have been parallelized using our system.
NASA Astrophysics Data System (ADS)
Yang, Z.; Burn, D. H.
2017-12-01
Extreme rainfall events can have devastating impacts on society. To quantify the associated risk, the IDF curve has been used to provide the essential rainfall-related information for urban planning. However, the recent changes in the rainfall climatology caused by climate change and urbanization have made the estimates provided by the traditional regional IDF approach increasingly inaccurate. This inaccuracy is mainly caused by two problems: 1) The ineffective choice of similarity indicators for the formation of a homogeneous group at different regions; and 2) An inadequate number of stations in the pooling group that does not adequately reflect the optimal balance between group size and group homogeneity or achieve the lowest uncertainty in the rainfall quantiles estimates. For the first issue, to consider the temporal difference among different meteorological and topographic indicators, a three-layer design is proposed based on three stages in the extreme rainfall formation: cloud formation, rainfall generation and change of rainfall intensity above urban surface. During the process, the impacts from climate change and urbanization are considered through the inclusion of potential relevant features at each layer. Then to consider spatial difference of similarity indicators for the homogeneous group formation at various regions, an automatic feature selection and weighting algorithm, specifically the hybrid searching algorithm of Tabu search, Lagrange Multiplier and Fuzzy C-means Clustering, is used to select the optimal combination of features for the potential optimal homogenous groups formation at a specific region. For the second issue, to compare the uncertainty of rainfall quantile estimates among potential groups, the two sample Kolmogorov-Smirnov test-based sample ranking process is used. During the process, linear programming is used to rank these groups based on the confidence intervals of the quantile estimates. The proposed methodology fills the gap of including the urbanization impacts during the pooling group formation, and challenges the traditional assumption that the same set of similarity indicators can be equally effective in generating the optimal homogeneous group for regions with different geographic and meteorological characteristics.
An algorithm to identify functional groups in organic molecules.
Ertl, Peter
2017-06-07
The concept of functional groups forms a basis of organic chemistry, medicinal chemistry, toxicity assessment, spectroscopy and also chemical nomenclature. All current software systems to identify functional groups are based on a predefined list of substructures. We are not aware of any program that can identify all functional groups in a molecule automatically. The algorithm presented in this article is an attempt to solve this scientific challenge. An algorithm to identify functional groups in a molecule based on iterative marching through its atoms is described. The procedure is illustrated by extracting functional groups from the bioactive portion of the ChEMBL database, resulting in identification of 3080 unique functional groups. A new algorithm to identify all functional groups in organic molecules is presented. The algorithm is relatively simple and full details with examples are provided, therefore implementation in any cheminformatics toolkit should be relatively easy. The new method allows the analysis of functional groups in large chemical databases in a way that was not possible using previous approaches. Graphical abstract .
Automatized Assessment of Protective Group Reactivity: A Step Toward Big Reaction Data Analysis.
Lin, Arkadii I; Madzhidov, Timur I; Klimchuk, Olga; Nugmanov, Ramil I; Antipin, Igor S; Varnek, Alexandre
2016-11-28
We report a new method to assess protective groups (PGs) reactivity as a function of reaction conditions (catalyst, solvent) using raw reaction data. It is based on an intuitive similarity principle for chemical reactions: similar reactions proceed under similar conditions. Technically, reaction similarity can be assessed using the Condensed Graph of Reaction (CGR) approach representing an ensemble of reactants and products as a single molecular graph, i.e., as a pseudomolecule for which molecular descriptors or fingerprints can be calculated. CGR-based in-house tools were used to process data for 142,111 catalytic hydrogenation reactions extracted from the Reaxys database. Our results reveal some contradictions with famous Greene's Reactivity Charts based on manual expert analysis. Models developed in this study show high accuracy (ca. 90%) for predicting optimal experimental conditions of protective group deprotection.
On the context dependency of implicit self-esteem in social anxiety disorder.
Hiller, Thomas S; Steffens, Melanie C; Ritter, Viktoria; Stangier, Ulrich
2017-12-01
Cognitive models assume that negative self-evaluations are automatically activated in individuals with Social Anxiety Disorder (SAD) during social situations, increasing their individual level of anxiety. This study examined automatic self-evaluations (i.e., implicit self-esteem) and state anxiety in a group of individuals with SAD (n = 45) and a non-clinical comparison group (NC; n = 46). Participants were randomly assigned to either a speech condition with social threat induction (giving an impromptu speech) or to a no-speech condition without social threat induction. We measured implicit self-esteem with an Implicit Association Test (IAT). Implicit self-esteem differed significantly between SAD and NC groups under the speech condition but not under the no-speech condition. The SAD group showed lower implicit self-esteem than the NC group under the speech-condition. State anxiety was significantly higher under the speech condition than under the no-speech condition in the SAD group but not in the NC group. Mediation analyses supported the idea that for the SAD group, the effect of experimental condition on state anxiety was mediated by implicit self-esteem. The causal relation between implicit self-esteem and state anxiety could not be determined. The findings corroborate hypotheses derived from cognitive models of SAD: Automatic self-evaluations were negatively biased in individuals with SAD facing social threat and showed an inverse relationship to levels of state anxiety. However, automatic self-evaluations in individuals with SAD can be unbiased (similar to NC) in situations without social threat. Copyright © 2017 Elsevier Ltd. All rights reserved.
Direct volume estimation without segmentation
NASA Astrophysics Data System (ADS)
Zhen, X.; Wang, Z.; Islam, A.; Bhaduri, M.; Chan, I.; Li, S.
2015-03-01
Volume estimation plays an important role in clinical diagnosis. For example, cardiac ventricular volumes including left ventricle (LV) and right ventricle (RV) are important clinical indicators of cardiac functions. Accurate and automatic estimation of the ventricular volumes is essential to the assessment of cardiac functions and diagnosis of heart diseases. Conventional methods are dependent on an intermediate segmentation step which is obtained either manually or automatically. However, manual segmentation is extremely time-consuming, subjective and highly non-reproducible; automatic segmentation is still challenging, computationally expensive, and completely unsolved for the RV. Towards accurate and efficient direct volume estimation, our group has been researching on learning based methods without segmentation by leveraging state-of-the-art machine learning techniques. Our direct estimation methods remove the accessional step of segmentation and can naturally deal with various volume estimation tasks. Moreover, they are extremely flexible to be used for volume estimation of either joint bi-ventricles (LV and RV) or individual LV/RV. We comparatively study the performance of direct methods on cardiac ventricular volume estimation by comparing with segmentation based methods. Experimental results show that direct estimation methods provide more accurate estimation of cardiac ventricular volumes than segmentation based methods. This indicates that direct estimation methods not only provide a convenient and mature clinical tool for cardiac volume estimation but also enables diagnosis of cardiac diseases to be conducted in a more efficient and reliable way.
2014-01-01
Background Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs’ adherence to the rules. Design We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules. Discussion We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP’s workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated. Trial registration Controlled Trials NTR3566 PMID:24642339
Group Dynamics in Automatic Imitation
Wilson, Neil; Reddy, Geetha; Catmur, Caroline
2016-01-01
Imitation–matching the configural body movements of another individual–plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach. PMID:27657926
Group Dynamics in Automatic Imitation.
Gleibs, Ilka H; Wilson, Neil; Reddy, Geetha; Catmur, Caroline
Imitation-matching the configural body movements of another individual-plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach.
ERIC Educational Resources Information Center
Khribi, Mohamed Koutheair; Jemni, Mohamed; Nasraoui, Olfa
2009-01-01
In this paper, we describe an automatic personalization approach aiming to provide online automatic recommendations for active learners without requiring their explicit feedback. Recommended learning resources are computed based on the current learner's recent navigation history, as well as exploiting similarities and dissimilarities among…
Automatic Syllabification in English: A Comparison of Different Algorithms
ERIC Educational Resources Information Center
Marchand, Yannick; Adsett, Connie R.; Damper, Robert I.
2009-01-01
Automatic syllabification of words is challenging, not least because the syllable is not easy to define precisely. Consequently, no accepted standard algorithm for automatic syllabification exists. There are two broad approaches: rule-based and data-driven. The rule-based method effectively embodies some theoretical position regarding the…
1989-08-01
Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17
NASA Technical Reports Server (NTRS)
Coggeshall, M. E.; Hoffer, R. M.
1973-01-01
Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.
Wong, Daniel Fu Keung; Chau, Phyllis; Kwok, Anna; Kwan, Jackie
2007-07-01
This study describes and evaluates a cognitive-behavioral treatment group for people with chronic physical illness in Hong Kong. We developed a group protocol based on the understanding that Chinese people generally prefer a structured group format, expect group leaders to be active and directive, and are not used to expressing opinions and emotions in groups. The experimental and waitlist control groups had 38 and 35 participants, respectively. A standardized questionnaire was administered to all participants before and after the group treatment. Results suggest that members of the experimental group showed improvements in mental health, negative automatic thoughts, and negative emotions when compared to those in the waitlist control groups, and at the end of group treatment. Implications for designing and running a culturally attuned CBT group for Chinese people are discussed.
a Method for the Seamlines Network Automatic Selection Based on Building Vector
NASA Astrophysics Data System (ADS)
Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.
2018-04-01
In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.
Chomiak, Taylor; Watts, Alexander; Meyer, Nicole; Pereira, Fernando V; Hu, Bin
2017-02-01
Deficits in motor movement automaticity in Parkinson's disease (PD), especially during multitasking, are early and consistent hallmarks of cognitive function decline, which increases fall risk and reduces quality of life. This study aimed to test the feasibility and potential efficacy of a wearable sensor-enabled technological platform designed for an in-home music-contingent stepping-in-place (SIP) training program to improve step automaticity during dual-tasking (DT). This was a 4-week prospective intervention pilot study. The intervention uses a sensor system and algorithm that runs off the iPod Touch which calculates step height (SH) in real-time. These measurements were then used to trigger auditory (treatment group, music; control group, radio podcast) playback in real-time through wireless headphones upon maintenance of repeated large amplitude stepping. With small steps or shuffling, auditory playback stops, thus allowing participants to use anticipatory motor control to regain positive feedback. Eleven participants were recruited from an ongoing trial (Trial Number: ISRCTN06023392). Fear of falling (FES-I), general cognitive functioning (MoCA), self-reported freezing of gait (FOG-Q), and DT step automaticity were evaluated. While we found no significant effect of training on FES-I, MoCA, or FOG-Q, we did observe a significant group (music vs podcast) by training interaction in DT step automaticity (P<0.01). Wearable device technology can be used to enable musically-contingent SIP training to increase motor automaticity for people living with PD. The training approach described here can be implemented at home to meet the growing demand for self-management of symptoms by patients.
Park, Seong-Cheol; Chung, Chun Kee
2018-06-01
The objective of this study was to introduce a new machine learning guided by outcome of resective epilepsy surgery defined as the presence/absence of seizures to improve data mining for interictal pathological activities in neocortical epilepsy. Electrocorticographies for 39 patients with medically intractable neocortical epilepsy were analyzed. We separately analyzed 38 frequencies from 0.9 to 800 Hz including both high-frequency activities and low-frequency activities to select bands related to seizure outcome. An automatic detector using amplitude-duration-number thresholds was used. Interictal electrocorticography data sets of 8 min for each patient were selected. In the first training data set of 20 patients, the automatic detector was optimized to best differentiate the seizure-free group from not-seizure-free-group based on ranks of resection percentages of activities detected using a genetic algorithm. The optimization was validated in a different data set of 19 patients. There were 16 (41%) seizure-free patients. The mean follow-up duration was 21 ± 11 mo (range, 13-44 mo). After validation, frequencies significantly related to seizure outcome were 5.8, 8.4-25, 30, 36, 52, and 75 among low-frequency activities and 108 and 800 Hz among high-frequency activities. Resection for 5.8, 8.4-25, 108, and 800 Hz activities consistently improved seizure outcome. Resection effects of 17-36, 52, and 75 Hz activities on seizure outcome were variable according to thresholds. We developed and validated an automated detector for monitoring interictal pathological and inhibitory/physiological activities in neocortical epilepsy using a data-driven approach through outcome-guided machine learning. NEW & NOTEWORTHY Outcome-guided machine learning based on seizure outcome was used to improve detections for interictal electrocorticographic low- and high-frequency activities. This method resulted in better separation of seizure outcome groups than others reported in the literature. The automatic detector can be trained without human intervention and no prior information. It is based only on objective seizure outcome data without relying on an expert's manual annotations. Using the method, we could find and characterize pathological and inhibitory activities.
Rocuronium: automatic infusion versus manual administration with TOF monitorisation.
Ozturk Arikan, Fatma Gulcin; Turan, Guldem; Ozgultekin, Asu; Sivrikaya, Zubeyir; Cosar, Bekir Cem; Onder, Dondu Nisa
2016-10-01
TOF (train-of-four) monitoring provides objective data in application of neuromuscular blocking agent. Thus, applicator-based differences are eliminated and optimum muscle relaxation is maintained during operation. In the present study, we aimed to compare the effects of target-controlled infusion system and standard TOF monitoring, on use of rocuronium. ASA I-II patients, who were aged between 18 and 75 years and scheduled for elective abdominal surgery at Haydarpaşa Numune Training and Research Hospital, were enrolled in the study. In order to evaluate neuromuscular blockade, the patients in Group 1 were connected to the acceleromyography device of the target-controlled infusion pump (Veryark-CLMRIS-I-China) while the ones in Group 2 were connected to the routinely used acceleromyography device (TOF Watch SX). There was no significant difference between groups regarding patient characteristics, the durations of anaesthesia and surgery, quality of intubation, time to extubation and time to recovery (TOF ratio of 0.9). Intubation time was significantly longer in Group 1 (Automated group) as compared to Group 2 (Control group) (p < 0.05). The total rocuronium amount used in Group 1 was found to be significantly higher than the amount used in Group 2 (p < 0.05). There was no clinical evidence of residual neuromuscular blockage or reoccurrence of neuromuscular blockage in any patient in either group. Both methods can be used for administration of neuromuscular blocker agent during moderate time anesthesia. No advantage was noted when rocuronium was administered via automatical infusion pump during anaesthesia.
Data mining for average images in a digital hand atlas
NASA Astrophysics Data System (ADS)
Zhang, Aifeng; Cao, Fei; Pietka, Ewa; Liu, Brent J.; Huang, H. K.
2004-04-01
Bone age assessment is a procedure performed in pediatric patients to quickly evaluate parameters of maturation and growth from a left hand and wrist radiograph. Pietka and Cao have developed a Computer-aided diagnosis (CAD) method of bone age assessment based on a digital hand atlas. The aim of this paper is to extend their work by automatically select the best representative image from a group of normal children based on specific bony features that reflect skeletal maturity. The group can be of any ethnic origin and gender from one year to 18 year old in the digital atlas. This best representative image is defined as the "average" image of the group that can be augmented to Piekta and Cao's method to facilitate in the bone age assessment process.
Method for automatic detection of wheezing in lung sounds.
Riella, R J; Nohama, P; Maia, J M
2009-07-01
The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.
ERIC Educational Resources Information Center
Arendasy, Martin; Sommer, Markus
2007-01-01
This article deals with the investigation of the psychometric quality and constructs validity of algebra word problems generated by means of a schema-based version of the automatic min-max approach. Based on review of the research literature in algebra word problem solving and automatic item generation this new approach is introduced as a…
Martin, Elizabeth A.; Karcher, Nicole R.; Bartholow, Bruce D.; Siegle, Greg J.; Kerns, John G.
2017-01-01
Both extreme levels of social anhedonia (SocAnh) and perceptual aberration/magical ideation (PerMag) are associated with risk for schizophrenia-spectrum disorders and with emotional abnormalities. Yet, the nature of any psychophysiological-measured affective abnormality, including the role of automatic/controlled processes, is unclear. We examined the late positive potential (LPP) during passive viewing (to assess automatic processing) and during cognitive reappraisal (to assess controlled processing) in three groups: SocAnh, PerMag, and controls. The SocAnh group exhibited an increased LPP when viewing negative images. Further, SocAnh exhibited greater reductions in the LPP for negative images when told to use strategies to alter negative emotion. Similar to SocAnh, PerMag exhibited an increased LPP when viewing negative images. However, PerMag also exhibited an increased LPP when viewing positive images as well as an atypical decreased LPP when increasing positive emotion. Overall, these results suggest that at-risk groups are associated with shared and unique automatic and controlled abnormalities. PMID:28174121
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Morita, Syoichi; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi
2015-03-01
This paper describes an automatic approach for anatomy partitioning on three-dimensional (3D) computedtomography (CT) images that divide the human torso into several volume-of-interesting (VOI) images based on anatomical definition. The proposed approach combines several individual detections of organ-location with a groupwise organ-location calibration and correction to achieve an automatic and robust multiple-organ localization task. The essence of the proposed method is to jointly detect the 3D minimum bounding box for each type of organ shown on CT images based on intra-organ-image-textures and inter-organ-spatial-relationship in the anatomy. Machine-learning-based template matching and generalized Hough transform-based point-distribution estimation are used in the detection and calibration processes. We apply this approach to the automatic partitioning of a torso region on CT images, which are divided into 35 VOIs presenting major organ regions and tissues required by routine diagnosis in clinical medicine. A database containing 4,300 patient cases of high-resolution 3D torso CT images is used for training and performance evaluations. We confirmed that the proposed method was successful in target organ localization on more than 95% of CT cases. Only two organs (gallbladder and pancreas) showed a lower success rate: 71 and 78% respectively. In addition, we applied this approach to another database that included 287 patient cases of whole-body CT images scanned for positron emission tomography (PET) studies and used for additional performance evaluation. The experimental results showed that no significant difference between the anatomy partitioning results from those two databases except regarding the spleen. All experimental results showed that the proposed approach was efficient and useful in accomplishing localization tasks for major organs and tissues on CT images scanned using different protocols.
NASA Astrophysics Data System (ADS)
Pena-Verdeal, Hugo; Garcia-Resua, Carlos; Yebra-Pimentel, Eva; Giraldez, Maria J.
2017-08-01
Purpose: Different lower tear meniscus parameters can be clinical assessed on dry eye diagnosis. The aim of this study was to propose and analyse the variability of a semi-automatic method for measuring lower tear meniscus central area (TMCA) by using open source software. Material and methods: On a group of 105 subjects, one video of the lower tear meniscus after fluorescein instillation was generated by a digital camera attached to a slit-lamp. A short light beam (3x5 mm) with moderate illumination in the central portion of the meniscus (6 o'clock) was used. Images were extracted from each video by a masked observer. By using an open source software based on Java (NIH ImageJ), a further observer measured in a masked and randomized order the TMCA in the short light beam illuminated area by two methods: (1) manual method, where TMCA images was "manually" measured; (2) semi-automatic method, where TMCA images were transformed in an 8-bit-binary image, then holes inside this shape were filled and on the isolated shape, the area size was obtained. Finally, both measurements, manual and semi-automatic, were compared. Results: Paired t-test showed no statistical difference between both techniques results (p = 0.102). Pearson correlation between techniques show a significant positive near to perfect correlation (r = 0.99; p < 0.001). Conclusions: This study showed a useful tool to objectively measure the frontal central area of the meniscus in photography by free open source software.
Automatic localization of the da Vinci surgical instrument tips in 3-D transrectal ultrasound.
Mohareri, Omid; Ramezani, Mahdi; Adebar, Troy K; Abolmaesumi, Purang; Salcudean, Septimiu E
2013-09-01
Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical system is the current state-of-the-art treatment option for clinically confined prostate cancer. Given the limited field of view of the surgical site in RALRP, several groups have proposed the integration of transrectal ultrasound (TRUS) imaging in the surgical workflow to assist with accurate resection of the prostate and the sparing of the neurovascular bundles (NVBs). We previously introduced a robotic TRUS manipulator and a method for automatically tracking da Vinci surgical instruments with the TRUS imaging plane, in order to facilitate the integration of intraoperative TRUS in RALRP. Rapid and automatic registration of the kinematic frames of the da Vinci surgical system and the robotic TRUS probe manipulator is a critical component of the instrument tracking system. In this paper, we propose a fully automatic registration technique based on automatic 3-D TRUS localization of robot instrument tips pressed against the air-tissue boundary anterior to the prostate. The detection approach uses a multiscale filtering technique to identify and localize surgical instrument tips in the TRUS volume, and could also be used to detect other surface fiducials in 3-D ultrasound. Experiments have been performed using a tissue phantom and two ex vivo tissue samples to show the feasibility of the proposed methods. Also, an initial in vivo evaluation of the system has been carried out on a live anaesthetized dog with a da Vinci Si surgical system and a target registration error (defined as the root mean square distance of corresponding points after registration) of 2.68 mm has been achieved. Results show this method's accuracy and consistency for automatic registration of TRUS images to the da Vinci surgical system.
General Automatic Components of Motion Sickness
NASA Technical Reports Server (NTRS)
Suter, S.; Toscano, W. B.; Kamiya, J.; Naifeh, K.
1985-01-01
A body of investigations performed in support of experiments aboard the space shuttle, and designed to counteract the symptoms of Space Adaptation Syndrome, which resemble those of motion sickness on Earth is reviewed. For these supporting studies, the automatic manifestations of earth-based motion sickness was examined. Heart rate, respiration rate, finger pulse volume and basal skin resistance were measured on 127 men and women before, during and after exposure to nauseogenic rotating chair tests. Significant changes in all autonomic responses were observed across the tests. Significant differences in autonomic responses among groups divided according to motion sickness susceptibility were also observed. Results suggest that the examination of autonomic responses as an objective indicator of motion sickness malaise is warranted and may contribute to the overall understanding of the syndrome on Earth and in Space.
Predictors of Reading in Urdu: Does Deep Orthography Have an Impact?
Farukh, Ammara; Vulchanova, Mila
2014-01-01
The aim of this study was to establish the extent to which rapid automatized naming (RAN) and non-word repetition (NWR) tasks predict reading fluency and reading accuracy in Urdu. One hundred sixty (8–9 years) children attending two types of schools (Urdu and English medium schools) were distributed into two groups, a control and a reading disability group on the basis of teacher’s report. The results confirmed the role of RAN in predicting reading fluency in both groups. The role of NWR as a predictor of accuracy was also confirmed, although the strength of the relationship was modulated by RAN in the reading disability group. There are no tests available to identify children with reading problems in Urdu. Our study supports the validity of NWR and RAN tasks for the purposes of screening for reading deficits. The performance results also confirm the original grouping based on teacher reports. The study further highlights the importance of medium of instruction and increased oral language input in learning to read. © 2014 The Authors. Dyslexia published by John Wiley & Sons Ltd. Key Messages Reliability of teacher reports in screening for reading difficulties in the classroom. Appropriateness of non-word repetition and rapid automatized naming tasks for establishing reading problems in Urdu. School type and exposure to instruction influences reading skills. PMID:24664499
Resisting chocolate temptation using a brief mindfulness strategy.
Jenkins, Kim T; Tapper, Katy
2014-09-01
We examined the effects of two mindfulness-based strategies on chocolate consumption amongst individuals who were trying to reduce the amount of chocolate they consumed. Participants (n = 137) were allocated to one of three conditions and employed either cognitive defusion, acceptance, or relaxation (control) techniques to help them resist chocolate over 5 days. During this period, they carried a bag of chocolates with them and recorded any chocolate or chocolate-related products they consumed. They also completed a questionnaire measure of the extent to which chocolate consumption was automatic, both before and after the 5-day period. Results showed that compared to controls, those in the cognitive defusion group ate significantly less chocolate from the bag (p = .046) and less chocolate according to the diary measure (p = .053). There was evidence that these changes were brought about by reductions in the extent to which chocolate consumption was automatic. There were no differences in chocolate consumption between the acceptance and control groups. Our results point to a promising brief intervention strategy and highlight the importance of disentangling the effects of different mindfulness-based techniques. What is already known on this subject? Multicomponent mindfulness interventions have been successfully applied to a range of health behaviours. Low levels of self-control are associated with weight gain and a higher BMI. What does this study add? The results show that a brief mindfulness strategy (defusion) helps individuals resist chocolate over 5 days. The results suggest this may be brought about by reductions in the extent to which eating chocolate is automatic. A second brief mindfulness strategy (acceptance) failed to help individuals resist chocolate. © 2013 The British Psychological Society.
The Use of Automatic Indexing for Authority Control.
ERIC Educational Resources Information Center
Dillon, Martin; And Others
1981-01-01
Uses an experimental system for authority control on a collection of bibliographic records to demonstrate the resemblance between thesaurus-based automatic indexing and automatic authority control. Details of the automatic indexing system are given, results discussed, and the benefits of the resemblance examined. Included are a rules appendix and…
A dye-assisted paper-based point-of-care assay for fast and reliable blood grouping.
Zhang, Hong; Qiu, Xiaopei; Zou, Yurui; Ye, Yanyao; Qi, Chao; Zou, Lingyun; Yang, Xiang; Yang, Ke; Zhu, Yuanfeng; Yang, Yongjun; Zhou, Yang; Luo, Yang
2017-03-15
Fast and simultaneous forward and reverse blood grouping has long remained elusive. Forward blood grouping detects antigens on red blood cells, whereas reverse grouping identifies specific antibodies present in plasma. We developed a paper-based assay using immobilized antibodies and bromocresol green dye for rapid and reliable blood grouping, where dye-assisted color changes corresponding to distinct blood components provide a visual readout. ABO antigens and five major Rhesus antigens could be detected within 30 s, and simultaneous forward and reverse ABO blood grouping using small volumes (100 μl) of whole blood was achieved within 2 min through on-chip plasma separation without centrifugation. A machine-learning method was developed to classify the spectral plots corresponding to dye-based color changes, which enabled reproducible automatic grouping. Using optimized operating parameters, the dye-assisted paper assay exhibited comparable accuracy and reproducibility to the classical gel-card assays in grouping 3550 human blood samples. When translated to the assembly line and low-cost manufacturing, the proposed approach may be developed into a cost-effective and robust universal blood-grouping platform. Copyright © 2017, American Association for the Advancement of Science.
The role of sensorimotor processes in social group contagion.
Cracco, Emiel; Brass, Marcel
2018-06-01
Although it is well known that action observation triggers an imitative response, not much is known about how these responses develop as a function of group size. Research on social contagion suggests that imitative tendencies initially increase but then stabilize as groups become larger. However, these findings have mainly been explained in terms of interpretative processes. Across seven experiments (N = 322), the current study investigated the contribution of sensorimotor processes to social group contagion by looking at the relation between group size and automatic imitation in a task that involved minimal interpretation. The results of Experiments 1-2 revealed that automatic imitation increased with group size according to an asymptotic curve on congruent trials but a linear curve on incongruent trials. The results of Experiments 3-7 showed that the asymptote on congruent trials disappeared when no control was needed, namely in the absence of incongruent trials. This suggests that the asymptote in the relation between group size and automatic imitation can be explained in terms of strategic control mechanisms that aim to prevent unintended imitative responses. The findings of the current study are in close correspondence with previous research in the social domain and as such support the hypothesis that sensorimotor processes contribute to the relation between group size and social contagion. Copyright © 2018 Elsevier Inc. All rights reserved.
Advances in segmentation modeling for health communication and social marketing campaigns.
Albrecht, T L; Bryant, C
1996-01-01
Large-scale communication campaigns for health promotion and disease prevention involve analysis of audience demographic and psychographic factors for effective message targeting. A variety of segmentation modeling techniques, including tree-based methods such as Chi-squared Automatic Interaction Detection and logistic regression, are used to identify meaningful target groups within a large sample or population (N = 750-1,000+). Such groups are based on statistically significant combinations of factors (e.g., gender, marital status, and personality predispositions). The identification of groups or clusters facilitates message design in order to address the particular needs, attention patterns, and concerns of audience members within each group. We review current segmentation techniques, their contributions to conceptual development, and cost-effective decision making. Examples from a major study in which these strategies were used are provided from the Texas Women, Infants and Children Program's Comprehensive Social Marketing Program.
Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giancardo, Luca; Meriaudeau, Fabrice; Karnowski, Thomas Paul
2011-01-01
Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publiclymore » available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing. Our algorithm is robust to segmentation uncertainties, does not need ground truth at lesion level, and is very fast, generating a diagnosis on an average of 4.4 seconds per image on an 2.6 GHz platform with an unoptimised Matlab implementation.« less
[Dispositional mindfulness modulates automatic transference of disgust into moral judgment].
Sato, Atsushi; Sugiura, Yoshinori
2014-02-01
Previous studies showed that incidental feelings of disgust could make moral judgments more severe. In the present study, we investigated whether individual differences in mindfulness modulated automatic transference of disgust into moral judgment. Undergraduates were divided into high- and low-mindfulness groups based on the mean score on each subscale of the Five Facet Mindfulness Questionnaire (FFMQ). Participants were asked to write about a disgusting experience or an emotionally neutral experience, and then to evaluate moral (impersonal vs. high-conflict personal) and non-moral scenarios. The results showed that the disgust induction made moral judgments more severe for the low "acting with awareness" participants, whereas it did not influence the moral judgments of the high "acting with awareness" participants irrespective of type of moral dilemma. The other facets of the FFMQ did not modulate the effect of disgust on moral judgment. These findings suggest that being present prevents automatic transference of disgust into moral judgment even when prepotent emotions elicited by the thought of killing one person to save several others and utilitarian reasoning conflict.
McGillivray, Jane A; Kershaw, Mavis M
2013-02-01
It has been estimated that people with ID experience the same and possibly higher levels of depression than the general population. Referral to a General Medical Practitioner (GP) for primary care is recommended practice for people with depression and cognitive behavioural (CB) therapy is now an accepted evidence based intervention. A growing body of literature indicates that people with ID and depression may benefit from CB strategies. The aim of the current study was to compare (i) CB group intervention strategies with referral to a GP; (ii) CB group intervention strategies only; and (iii) referral to a GP only on symptoms of depression among people with mild ID. Staff from six participating agencies received training in (a) how to identify and screen individuals with mild ID for depressive symptoms and risk factors for depression, and (b) supportive referral of identified individuals to GPs for mental health services. In addition, staff from four of the agencies undertook (c) training on how to deliver group CB intervention strategies. Eighty-two participants were allocated to one of the three intervention groups. Depressive symptoms and negative automatic thoughts were assessed prior to the intervention, at the conclusion of the intervention, and at eight months follow-up. Compared to GP referral alone, those participants who received CB strategies both with and without GP referral displayed significant reductions in depressive symptoms. The use of CB strategies only also resulted in a significant reduction in frequency of negative automatic thoughts. The findings of this study support routine screening of individuals with mild ID for depression and the delivery of group CB intervention programmes by trained staff within community-based disability agencies. Copyright © 2012 Elsevier Ltd. All rights reserved.
Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms
Gao, Connie W.; Allen, Joshua W.; Green, William H.; ...
2016-02-24
Reaction Mechanism Generator (RMG) constructs kinetic models composed of elementary chemical reaction steps using a general understanding of how molecules react. Species thermochemistry is estimated through Benson group additivity and reaction rate coefficients are estimated using a database of known rate rules and reaction templates. At its core, RMG relies on two fundamental data structures: graphs and trees. Graphs are used to represent chemical structures, and trees are used to represent thermodynamic and kinetic data. Models are generated using a rate-based algorithm which excludes species from the model based on reaction fluxes. RMG can generate reaction mechanisms for species involvingmore » carbon, hydrogen, oxygen, sulfur, and nitrogen. It also has capabilities for estimating transport and solvation properties, and it automatically computes pressure-dependent rate coefficients and identifies chemically-activated reaction paths. RMG is an object-oriented program written in Python, which provides a stable, robust programming architecture for developing an extensible and modular code base with a large suite of unit tests. Computationally intensive functions are cythonized for speed improvements.« less
Group size and social conflict in complex societies.
Shen, Sheng-Feng; Akçay, Erol; Rubenstein, Dustin R
2014-02-01
Conflicts of interest over resources or reproduction among individuals in a social group have long been considered to result in automatic and universal costs to group living. However, exploring how social conflict varies with group size has produced mixed empirical results. Here we develop a model that generates alternative predictions for how social conflict should vary with group size depending on the type of benefits gained from being in a social group. We show that a positive relationship between social conflict and group size is favored when groups form primarily for the benefits of sociality but not when groups form mainly for accessing group-defended resources. Thus, increased social conflict in animal societies should not be viewed as an automatic cost of larger social groups. Instead, studying the relationship between social conflict and the types of grouping benefits will be crucial for understanding the evolution of complex societies.
Fuzzy forecasting based on fuzzy-trend logical relationship groups.
Chen, Shyi-Ming; Wang, Nai-Yi
2010-10-01
In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.
Valencia, Mauricio; Ferrer, Miquel; Farre, Ramon; Navajas, Daniel; Badia, Joan Ramon; Nicolas, Josep Maria; Torres, Antoni
2007-06-01
The aspiration of subglottic secretions colonized by bacteria pooled around the tracheal tube cuff due to inadvertent deflation (<20 cm H2O) of the cuff plays a relevant role in the pathogenesis of ventilator-associated pneumonia. We assessed the efficacy of an automatic, validated device for the continuous regulation of tracheal tube cuff pressure in preventing ventilator-associated pneumonia. Prospective randomized controlled trial. Respiratory intensive care unit and general medical intensive care unit. One hundred and forty-two mechanically ventilated patients (age, 64 +/- 17 yrs; Acute Physiology and Chronic Health Evaluation II score, 18 +/- 6) without pneumonia or aspiration at admission. Within 24 hrs of intubation, patients were randomly allocated to undergo continuous regulation of the cuff pressure with the automatic device (n = 73) or routine care of the cuff pressure (control group, n = 69). Patients remained in a semirecumbent position in bed. The primary end point variable was the incidence of ventilator-associated pneumonia. Main causes for intubation were decreased consciousness (43, 30%) and exacerbation of chronic respiratory diseases (38, 27%). Cuff pressure <20 cm H2O was more frequently observed in the control than the automatic group (45.3 vs. 0.7% determinations, p < .001). However, the rate of ventilator-associated pneumonia with clinical criteria (16, 22% vs. 20, 29%) and microbiological confirmation (11, 15% vs. 10, 15%), the distribution of early and late onset, the causative microorganisms, and intensive care unit (20, 27% vs. 16, 23%) and hospital mortality (30, 41% vs. 23, 33%) were similar for the automatic and control groups, respectively. Cuff pressure is better controlled with the automatic device. However, it did not result in additional benefits to the semirecumbent position in preventing ventilator-associated pneumonia.
A training approach to improve stepping automaticity while dual-tasking in Parkinson's disease
Chomiak, Taylor; Watts, Alexander; Meyer, Nicole; Pereira, Fernando V.; Hu, Bin
2017-01-01
Abstract Background: Deficits in motor movement automaticity in Parkinson's disease (PD), especially during multitasking, are early and consistent hallmarks of cognitive function decline, which increases fall risk and reduces quality of life. This study aimed to test the feasibility and potential efficacy of a wearable sensor-enabled technological platform designed for an in-home music-contingent stepping-in-place (SIP) training program to improve step automaticity during dual-tasking (DT). Methods: This was a 4-week prospective intervention pilot study. The intervention uses a sensor system and algorithm that runs off the iPod Touch which calculates step height (SH) in real-time. These measurements were then used to trigger auditory (treatment group, music; control group, radio podcast) playback in real-time through wireless headphones upon maintenance of repeated large amplitude stepping. With small steps or shuffling, auditory playback stops, thus allowing participants to use anticipatory motor control to regain positive feedback. Eleven participants were recruited from an ongoing trial (Trial Number: ISRCTN06023392). Fear of falling (FES-I), general cognitive functioning (MoCA), self-reported freezing of gait (FOG-Q), and DT step automaticity were evaluated. Results: While we found no significant effect of training on FES-I, MoCA, or FOG-Q, we did observe a significant group (music vs podcast) by training interaction in DT step automaticity (P<0.01). Conclusion: Wearable device technology can be used to enable musically-contingent SIP training to increase motor automaticity for people living with PD. The training approach described here can be implemented at home to meet the growing demand for self-management of symptoms by patients. PMID:28151878
Herold, Volker; Herz, Stefan; Winter, Patrick; Gutjahr, Fabian Tobias; Andelovic, Kristina; Bauer, Wolfgang Rudolf; Jakob, Peter Michael
2017-10-16
Local aortic pulse wave velocity (PWV) is a measure for vascular stiffness and has a predictive value for cardiovascular events. Ultra high field CMR scanners allow the quantification of local PWV in mice, however these systems are yet unable to monitor the distribution of local elasticities. In the present study we provide a new accelerated method to quantify local aortic PWV in mice with phase-contrast cardiovascular magnetic resonance imaging (PC-CMR) at 17.6 T. Based on a k-t BLAST (Broad-use Linear Acquisition Speed-up Technique) undersampling scheme, total measurement time could be reduced by a factor of 6. The fast data acquisition enables to quantify the local PWV at several locations along the aortic blood vessel based on the evaluation of local temporal changes in blood flow and vessel cross sectional area. To speed up post processing and to eliminate operator bias, we introduce a new semi-automatic segmentation algorithm to quantify cross-sectional areas of the aortic vessel. The new methods were applied in 10 eight-month-old mice (4 C57BL/6J-mice and 6 ApoE (-/-) -mice) at 12 adjacent locations along the abdominal aorta. Accelerated data acquisition and semi-automatic post-processing delivered reliable measures for the local PWV, similiar to those obtained with full data sampling and manual segmentation. No statistically significant differences of the mean values could be detected for the different measurement approaches. Mean PWV values were elevated for the ApoE (-/-) -group compared to the C57BL/6J-group (3.5 ± 0.7 m/s vs. 2.2 ± 0.4 m/s, p < 0.01). A more heterogeneous PWV-distribution in the ApoE (-/-) -animals could be observed compared to the C57BL/6J-mice, representing the local character of lesion development in atherosclerosis. In the present work, we showed that k-t BLAST PC-MRI enables the measurement of the local PWV distribution in the mouse aorta. The semi-automatic segmentation method based on PC-CMR data allowed rapid determination of local PWV. The findings of this study demonstrate the ability of the proposed methods to non-invasively quantify the spatial variations in local PWV along the aorta of ApoE (-/-) -mice as a relevant model of atherosclerosis.
Changes in default mode network as automaticity develops in a categorization task.
Shamloo, Farzin; Helie, Sebastien
2016-10-15
The default mode network (DMN) is a set of brain regions in which blood oxygen level dependent signal is suppressed during attentional focus on the external environment. Because automatic task processing requires less attention, development of automaticity in a rule-based categorization task may result in less deactivation and altered functional connectivity of the DMN when compared to the initial learning stage. We tested this hypothesis by re-analyzing functional magnetic resonance imaging data of participants trained in rule-based categorization for over 10,000 trials (Helie et al., 2010) [12,13]. The results show that some DMN regions are deactivated in initial training but not after automaticity has developed. There is also a significant decrease in DMN deactivation after extensive practice. Seed-based functional connectivity analyses with the precuneus, medial prefrontal cortex (two important DMN regions) and Brodmann area 6 (an important region in automatic categorization) were also performed. The results show increased functional connectivity with both DMN and non-DMN regions after the development of automaticity, and a decrease in functional connectivity between the medial prefrontal cortex and ventromedial orbitofrontal cortex. Together, these results further support the hypothesis of a strategy shift in automatic categorization and bridge the cognitive and neuroscientific conceptions of automaticity in showing that the reduced need for cognitive resources in automatic processing is accompanied by a disinhibition of the DMN and stronger functional connectivity between DMN and task-related brain regions. Copyright © 2016 Elsevier B.V. All rights reserved.
Research on Application of Automatic Weather Station Based on Internet of Things
NASA Astrophysics Data System (ADS)
Jianyun, Chen; Yunfan, Sun; Chunyan, Lin
2017-12-01
In this paper, the Internet of Things is briefly introduced, and then its application in the weather station is studied. A method of data acquisition and transmission based on NB-iot communication mode is proposed, Introduction of Internet of things technology, Sensor digital and independent power supply as the technical basis, In the construction of Automatic To realize the intelligent interconnection of the automatic weather station, and then to form an automatic weather station based on the Internet of things. A network structure of automatic weather station based on Internet of things technology is constructed to realize the independent operation of intelligent sensors and wireless data transmission. Research on networking data collection and dissemination of meteorological data, through the data platform for data analysis, the preliminary work of meteorological information publishing standards, networking of meteorological information receiving terminal provides the data interface, to the wisdom of the city, the wisdom of the purpose of the meteorological service.
Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection
Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe
2012-01-01
This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461
Melles, Reinhilde J; Dewitte, Marieke D; Ter Kuile, Moniek M; Peters, Madelon M L; de Jong, Peter J
2016-08-01
Current information processing models propose that heightened attention bias for sex-related threats (eg, pain) and lowered automatic incentive processes ("wanting") may play an important role in the impairment of sexual arousal and the development of sexual dysfunctions such as genitopelvic pain/penetration disorder (GPPPD). Differential threat and incentive processing may also help explain the stronger persistence of coital avoidance in women with vaginismus compared to women with dyspareunia. As the first aim, we tested if women with GPPPD show (1) heightened attention for pain and sex, and (2) heightened threat and lower incentive associations with sexual penetration. Second, we examined whether the stronger persistence of coital avoidance in vaginismus vs dyspareunia might be explained by a stronger attentional bias or more dysfunctional automatic threat/incentive associations. Women with lifelong vaginismus (n = 37), dyspareunia (n = 29), and a no-symptoms comparison group (n = 51) completed a visual search task to assess attentional bias, and single target implicit-association tests to measure automatic sex-threat and sex-wanting associations. There were no group differences in attentional bias or automatic associations. Correlational analysis showed that slowed detection of sex stimuli and stronger automatic threat associations were related to lowered sexual arousal. The findings do not corroborate the view that attentional bias for pain or sex contributes to coital pain, or that differences in coital avoidance may be explained by differences in attentional bias or automatic threat/incentive associations. However, the correlational findings are consistent with the view that automatic threat associations and impaired attention for sex stimuli may interfere with the generation of sexual arousal. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric
2011-03-01
Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.
PyEmir: Data Reduction Pipeline for EMIR, the GTC Near-IR Multi-Object Spectrograph
NASA Astrophysics Data System (ADS)
Pascual, S.; Gallego, J.; Cardiel, N.; Eliche-Moral, M. C.
2010-12-01
EMIR is the near-infrared wide-field camera and multi-slit spectrograph being built for Gran Telescopio Canarias. We present here the work being done on its data processing pipeline. PyEmir is based on Python and it will process automatically data taken in both imaging and spectroscopy mode. PyEmir is begin developed by the UCM Group of Extragalactic Astrophysics and Astronomical Instrumentation.
Project MAC Progress Report 11
1974-12-01
whether a subroutine would be useful as a part of some larger program , and, if so, how to use it [8]. The programming methodology employed by CALICO...7. Seriff, Marc, How to Write Programs for the CALICO Environment. SYS. 14.04 (unpublished). 8. Reeve, Chris, Marty Draper, D. E. Burmaster, and J...Introduction Automatic Programming Group A. Introduction B. Understanding How a User Might Interact with a Knowledge-Based Application System C
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
2002-01-01
In this paper we describe the extension of the CAPO (CAPtools (Computer Aided Parallelization Toolkit) OpenMP) parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report some results for several benchmark codes and one full application that have been parallelized using our system.
An Example-Based Multi-Atlas Approach to Automatic Labeling of White Matter Tracts
Yoo, Sang Wook; Guevara, Pamela; Jeong, Yong; Yoo, Kwangsun; Shin, Joseph S.; Mangin, Jean-Francois; Seong, Joon-Kyung
2015-01-01
We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our approach exploits expert-provided example data to automatically classify the WM tracts of a subject. Multiple atlases are constructed to model the example data from multiple subjects in order to reflect the individual variability of bundle shapes and trajectories over subjects. For each example subject, an atlas is maintained to allow the example data of a subject to be added or deleted flexibly. A voting scheme is proposed to facilitate the multi-atlas exploitation of example data. For conceptual simplicity, we adopt the same metrics in both example data construction and WM tract labeling. Due to the huge number of WM tracts in a subject, it is time-consuming to label each WM tract individually. Thus, the WM tracts are grouped according to their shape similarity, and WM tracts within each group are labeled simultaneously. To further enhance the computational efficiency, we implemented our approach on the graphics processing unit (GPU). Through nested cross-validation we demonstrated that our approach yielded high classification performance. The average sensitivities for bundles in the left and right hemispheres were 89.5% and 91.0%, respectively, and their average false discovery rates were 14.9% and 14.2%, respectively. PMID:26225419
An Example-Based Multi-Atlas Approach to Automatic Labeling of White Matter Tracts.
Yoo, Sang Wook; Guevara, Pamela; Jeong, Yong; Yoo, Kwangsun; Shin, Joseph S; Mangin, Jean-Francois; Seong, Joon-Kyung
2015-01-01
We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our approach exploits expert-provided example data to automatically classify the WM tracts of a subject. Multiple atlases are constructed to model the example data from multiple subjects in order to reflect the individual variability of bundle shapes and trajectories over subjects. For each example subject, an atlas is maintained to allow the example data of a subject to be added or deleted flexibly. A voting scheme is proposed to facilitate the multi-atlas exploitation of example data. For conceptual simplicity, we adopt the same metrics in both example data construction and WM tract labeling. Due to the huge number of WM tracts in a subject, it is time-consuming to label each WM tract individually. Thus, the WM tracts are grouped according to their shape similarity, and WM tracts within each group are labeled simultaneously. To further enhance the computational efficiency, we implemented our approach on the graphics processing unit (GPU). Through nested cross-validation we demonstrated that our approach yielded high classification performance. The average sensitivities for bundles in the left and right hemispheres were 89.5% and 91.0%, respectively, and their average false discovery rates were 14.9% and 14.2%, respectively.
Keleş Altun, İlkay; Uysal, Emel; Özkorumak Karagüzel, Evrim
2017-01-01
Obsessive compulsive disorder (OCD) is characterized by obsessions and compulsions. Obsessions have been classified as autogenous obsessions and reactive obsessions on the basis of the cognitive theory of Lee and Kwon. The aim of this study was to investigate the differences between autogenous groups (AG) and reactive groups (RG) in terms of metacognition and automatic thoughts, for the purpose of investigating the differences of cognitive appraisals. One hundred and thirty-three patients diagnosed with OCD were included in the study as the patient group. A control group was formed of 133 age, gender and education-matched healthy individuals. The OCD group patients were separated into subgroups according to the primary obsessions. The sociodemographic data, and the Yale-Brown Obsessive Compulsive Scale, Metacognition Questionnaire-30 (MCQ-30), Automatic Thoughts Questionnaire (ATQ), Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) scores of the AG, RG, and control groups were compared. The MCQ-30 (total) and the subscales of MCQ-30 and ATQ scale points were seen to be significantly higher in the AG than in the RG and significantly higher in the RG than in the control group. In the reactive obsession group, the predictive variables of the ATQ points were determined to be MCQ-30 (total), BDI and BAI. In the autogenous obsession group, the predictive variables of the ATQ points were determined to be BDI and BAI. In the current study, differences were determined between the AG and the RG in respect of metacognitions and automatic thoughts. In light of these results, the recommended grouping can be considered useful in the identification of OCD sub-types. There is a need for further studies to identify more homogenous sub-types of OCD. Future multi-centered studies of sub-typing with larger samples using more specific instruments to sub-type and dimensional evaluation will be useful for detailed evaluation and better understanding of the subject.
Construction and testing of a simple and economical soil greenhouse gas automatic sampler
Ginting, D.; Arnold, S.L.; Arnold, N.S.; Tubbs, R.S.
2007-01-01
Quantification of soil greenhouse gas emissions requires considerable sampling to account for spatial and/or temporal variation. With manual sampling, additional personnel are often not available to sample multiple sites within a narrow time interval. The objectives were to construct an automatic gas sampler and to compare the accuracy and precision of automatic versus manual sampling. The automatic sampler was tested with carbon dioxide (CO2) fluxes that mimicked the range of CO2 fluxes during a typical corn-growing season in eastern Nebraska. Gas samples were drawn from the chamber at 0, 5, and 10 min manually and with the automatic sampler. The three samples drawn with the automatic sampler were transferred to pre-vacuumed vials after 1 h; thus the samples in syringe barrels stayed connected with the increasing CO2 concentration in the chamber. The automatic sampler sustains accuracy and precision in greenhouse gas sampling while improving time efficiency and reducing labor stress. Copyright ?? Taylor & Francis Group, LLC.
Patrick, Regan E; Rastogi, Anuj; Christensen, Bruce K
2015-01-01
Adaptive emotional responding relies on dual automatic and effortful processing streams. Dual-stream models of schizophrenia (SCZ) posit a selective deficit in neural circuits that govern goal-directed, effortful processes versus reactive, automatic processes. This imbalance suggests that when patients are confronted with competing automatic and effortful emotional response cues, they will exhibit diminished effortful responding and intact, possibly elevated, automatic responding compared to controls. This prediction was evaluated using a modified version of the face-vignette task (FVT). Participants viewed emotional faces (automatic response cue) paired with vignettes (effortful response cue) that signalled a different emotion category and were instructed to discriminate the manifest emotion. Patients made less vignette and more face responses than controls. However, the relationship between group and FVT responding was moderated by IQ and reading comprehension ability. These results replicate and extend previous research and provide tentative support for abnormal conflict resolution between automatic and effortful emotional processing predicted by dual-stream models of SCZ.
Handfield, Louis-François; Chong, Yolanda T.; Simmons, Jibril; Andrews, Brenda J.; Moses, Alan M.
2013-01-01
Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images. PMID:23785265
A VxD-based automatic blending system using multithreaded programming.
Wang, L; Jiang, X; Chen, Y; Tan, K C
2004-01-01
This paper discusses the object-oriented software design for an automatic blending system. By combining the advantages of a programmable logic controller (PLC) and an industrial control PC (ICPC), an automatic blending control system is developed for a chemical plant. The system structure and multithread-based communication approach are first presented in this paper. The overall software design issues, such as system requirements and functionalities, are then discussed in detail. Furthermore, by replacing the conventional dynamic link library (DLL) with virtual X device drivers (VxD's), a practical and cost-effective solution is provided to improve the robustness of the Windows platform-based automatic blending system in small- and medium-sized plants.
Automatic detection of sweep-meshable volumes
Tautges,; Timothy J. , White; David, R [Pittsburgh, PA
2006-05-23
A method of and software for automatically determining whether a mesh can be generated by sweeping for a representation of a geometric solid comprising: classifying surface mesh schemes for surfaces of the representation locally using surface vertex types; grouping mappable and submappable surfaces of the representation into chains; computing volume edge types for the representation; recursively traversing surfaces of the representation and grouping the surfaces into source, target, and linking surface lists; and checking traversal direction when traversing onto linking surfaces.
The automatic component of habit in health behavior: habit as cue-contingent automaticity.
Orbell, Sheina; Verplanken, Bas
2010-07-01
Habit might be usefully characterized as a form of automaticity that involves the association of a cue and a response. Three studies examined habitual automaticity in regard to different aspects of the cue-response relationship characteristic of unhealthy and healthy habits. In each study, habitual automaticity was assessed by the Self-Report Habit Index (SRHI). In Study 1 SRHI scores correlated with attentional bias to smoking cues in a Stroop task. Study 2 examined the ability of a habit cue to elicit an unwanted habit response. In a prospective field study, habitual automaticity in relation to smoking when drinking alcohol in a licensed public house (pub) predicted the likelihood of cigarette-related action slips 2 months later after smoking in pubs had become illegal. In Study 3 experimental group participants formed an implementation intention to floss in response to a specified situational cue. Habitual automaticity of dental flossing was rapidly enhanced compared to controls. The studies provided three different demonstrations of the importance of cues in the automatic operation of habits. Habitual automaticity assessed by the SRHI captured aspects of a habit that go beyond mere frequency or consistency of the behavior. PsycINFO Database Record (c) 2010 APA, all rights reserved.
Cho, Jae-Hyoung; Lee, Hye-Chung; Lim, Dong-Jun; Kwon, Hyuk-Sang; Yoon, Kun-Ho
2009-01-01
A mobile phone with a glucometer integrated into the battery pack (the 'Diabetes Phone') was launched in Korea in 2003. We compared its effect on management of type 2 diabetes to the Internet-based glucose monitoring system (IBGMS), which had been studied previously. We conducted a randomized trial involving 69 patients for three months. Participants were assigned to an Internet group or a phone group. The phone group communicated with medical staff through the mobile phone only. Their glucose-monitoring data were automatically transferred to individual, web-based charts and they received medical recommendations by short message service. The Internet group used the IBGMS. There were no significant differences between the groups at baseline. After three months' intervention, HbA(1c) levels of both groups had decreased significantly, from 7.6% to 6.9% for the Internet group and from 8.3% to 7.1% for the phone group (P < 0.01). Levels of patient satisfaction and adherence to medical advice were similar. Mobile, bidirectional communication between doctors and patients using the diabetes phone was as effective for glucose control as the previously-studied Internet-based monitoring system and it was good for patient satisfaction and adherence.
Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method
NASA Astrophysics Data System (ADS)
Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi
In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.
Eidlin-Levy, Hili; Rubinsten, Orly
2017-01-01
The relationship between numbers and other magnitudes has been extensively investigated in the scientific literature. Here, the objectives were to examine whether two continuous magnitudes, area and perimeter, are automatically processed and whether adults with developmental dyscalculia (DD) are deficient in their ability to automatically process one or both of these magnitudes. Fifty-seven students (30 with DD and 27 with typical development) performed a novel Stroop-like task requiring estimation of one aspect (area or perimeter) while ignoring the other. In order to track possible changes in automaticity due to practice, we measured performance after initial and continuous exposure to stimuli. Similar to previous findings, current results show a significant group × congruency interaction, evident beyond exposure level or magnitude type. That is, the DD group systematically showed larger Stroop effects. However, analysis of each exposure period showed that during initial exposure to stimuli the DD group showed larger Stroop effects in the perimeter and not in the area task. In contrast, during continuous exposure to stimuli no triple interaction was evident. It is concluded that both magnitudes are automatically processed. Nevertheless, individuals with DD are deficient in inhibiting irrelevant magnitude information in general and, specifically, struggle to inhibit salient area information after initial exposure to a perimeter comparison task. Accordingly, the findings support the assumption that DD involves a deficiency in multiple cognitive components, which include domain-specific and domain-general cognitive functions.
Eidlin-Levy, Hili; Rubinsten, Orly
2017-01-01
The relationship between numbers and other magnitudes has been extensively investigated in the scientific literature. Here, the objectives were to examine whether two continuous magnitudes, area and perimeter, are automatically processed and whether adults with developmental dyscalculia (DD) are deficient in their ability to automatically process one or both of these magnitudes. Fifty-seven students (30 with DD and 27 with typical development) performed a novel Stroop-like task requiring estimation of one aspect (area or perimeter) while ignoring the other. In order to track possible changes in automaticity due to practice, we measured performance after initial and continuous exposure to stimuli. Similar to previous findings, current results show a significant group × congruency interaction, evident beyond exposure level or magnitude type. That is, the DD group systematically showed larger Stroop effects. However, analysis of each exposure period showed that during initial exposure to stimuli the DD group showed larger Stroop effects in the perimeter and not in the area task. In contrast, during continuous exposure to stimuli no triple interaction was evident. It is concluded that both magnitudes are automatically processed. Nevertheless, individuals with DD are deficient in inhibiting irrelevant magnitude information in general and, specifically, struggle to inhibit salient area information after initial exposure to a perimeter comparison task. Accordingly, the findings support the assumption that DD involves a deficiency in multiple cognitive components, which include domain-specific and domain-general cognitive functions. PMID:29312066
Sowden, Sophie; Koehne, Svenja; Catmur, Caroline; Dziobek, Isabel; Bird, Geoffrey
2016-02-01
A lack of imitative behavior is frequently described as a core feature of Autism Spectrum Disorder (ASD), and is consistent with claims of mirror neuron system dysfunction in these individuals. Previous research has questioned this characterization of ASD however, arguing that when tests of automatic imitation are used--which do not require higher-level cognitive processing--imitative behavior is intact or even enhanced in individuals with ASD. In Experiment 1, 60 adult individuals with ASD and a matched Control group completed an automatic imitation task in which they were required to perform an index or a middle finger lift while observing a hand making either the same, or the alternate, finger movement. Both groups demonstrated a significant imitation effect whereby actions were executed faster when preceded by observation of the same action, than when preceded by the alternate action. The magnitude of this "imitation effect" was statistically indistinguishable in the ASD and Control groups. Experiment 2 utilized an improved automatic imitation paradigm to demonstrate that, when automatic imitation effects are isolated from those due to spatial compatibility, increasing autism symptom severity is associated with an increased tendency to imitate. Notably, there was no association between autism symptom severity and spatial compatibility, demonstrating the specificity of the link between ASD symptoms and increased imitation. These results provide evidence against claims of a lack of imitative behavior in ASD, and challenge the "Broken Mirror Theory of Autism." © 2015 International Society for Autism Research, Wiley Periodicals, Inc.
Group-wise feature-based registration of CT and ultrasound images of spine
NASA Astrophysics Data System (ADS)
Rasoulian, Abtin; Mousavi, Parvin; Hedjazi Moghari, Mehdi; Foroughi, Pezhman; Abolmaesumi, Purang
2010-02-01
Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm.
Comparison of landmark-based and automatic methods for cortical surface registration
Pantazis, Dimitrios; Joshi, Anand; Jiang, Jintao; Shattuck, David; Bernstein, Lynne E.; Damasio, Hanna; Leahy, Richard M.
2009-01-01
Group analysis of structure or function in cerebral cortex typically involves as a first step the alignment of the cortices. A surface based approach to this problem treats the cortex as a convoluted surface and coregisters across subjects so that cortical landmarks or features are aligned. This registration can be performed using curves representing sulcal fundi and gyral crowns to constrain the mapping. Alternatively, registration can be based on the alignment of curvature metrics computed over the entire cortical surface. The former approach typically involves some degree of user interaction in defining the sulcal and gyral landmarks while the latter methods can be completely automated. Here we introduce a cortical delineation protocol consisting of 26 consistent landmarks spanning the entire cortical surface. We then compare the performance of a landmark-based registration method that uses this protocol with that of two automatic methods implemented in the software packages FreeSurfer and BrainVoyager. We compare performance in terms of discrepancy maps between the different methods, the accuracy with which regions of interest are aligned, and the ability of the automated methods to correctly align standard cortical landmarks. Our results show similar performance for ROIs in the perisylvian region for the landmark based method and FreeSurfer. However, the discrepancy maps showed larger variability between methods in occipital and frontal cortex and also that automated methods often produce misalignment of standard cortical landmarks. Consequently, selection of the registration approach should consider the importance of accurate sulcal alignment for the specific task for which coregistration is being performed. When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis. PMID:19796696
Buller, G; Lutman, M E
1998-08-01
The increasing use of transiently evoked otoacoustic emissions (TEOAE) in large neonatal hearing screening programmes makes a standardized method of response classification desirable. Until now methods have been either subjective or based on arbitrary response characteristics. This study takes an expert system approach to standardize the subjective judgements of an experienced scorer. The method that is developed comprises three stages. First, it transforms TEOAEs from waveforms in the time domain into a simplified parameter set. Second, the parameter set is classified by an artificial neural network that has been taught on a large database TEOAE waveforms and corresponding expert scores. Third, additional fuzzy logic rules automatically detect probable artefacts in the waveforms and synchronized spontaneous emission components. In this way, the knowledge of the experienced scorer is encapsulated in the expert system software and thereafter can be accessed by non-experts. Teaching and evaluation of the neural network was based on TEOAEs from a database totalling 2190 neonatal hearing screening tests. The database was divided into learning and test groups with 820 and 1370 waveforms respectively. From each recorded waveform a set of 12 parameters was calculated, representing signal static and dynamic properties. The artifical network was taught with parameter sets of only the learning groups. Reproduction of the human scorer classification by the neural net in the learning group showed a sensitivity for detecting screen fails of 99.3% (299 from 301 failed results on subjective scoring) and a specificity for detecting screen passes of 81.1% (421 of 519 pass results). To quantify the post hoc performance of the net (generalization), the test group was then presented to the network input. Sensitivity was 99.4% (474 from 477) and specificity was 87.3% (780 from 893). To check the efficiency of the classification method, a second learning group was selected out of the previous test group, and the previous learning group was used as the test group. Repeating learning and test procedures yielded 99.3% sensitivity and 80.7% specificity for reproduction, and 99.4% sensitivity and 86.7% specificity for generalization. In all respects, performance was better than for a previously optimized method based simply on cross-correlation between replicate non-linear waveforms. It is concluded that classification methods based on neural networks show promise for application to large neonatal screening programmes utilizing TEOAEs.
[Wearable Automatic External Defibrillators].
Luo, Huajie; Luo, Zhangyuan; Jin, Xun; Zhang, Leilei; Wang, Changjin; Zhang, Wenzan; Tu, Quan
2015-11-01
Defibrillation is the most effective method of treating ventricular fibrillation(VF), this paper introduces wearable automatic external defibrillators based on embedded system which includes EGG measurements, bioelectrical impedance measurement, discharge defibrillation module, which can automatic identify VF signal, biphasic exponential waveform defibrillation discharge. After verified by animal tests, the device can realize EGG acquisition and automatic identification. After identifying the ventricular fibrillation signal, it can automatic defibrillate to abort ventricular fibrillation and to realize the cardiac electrical cardioversion.
NASA Astrophysics Data System (ADS)
Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin
2014-05-01
Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.
Makeyev, Oleksandr; Ding, Quan; Martínez-Juárez, Iris E; Gaitanis, John; Kay, Steven M; Besio, Walter G
2013-01-01
As epilepsy affects approximately one percent of the world population, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. Closed-loop systems that apply electrical stimulation when seizure onset is automatically detected require high accuracy of automatic seizure detection based on electrographic brain activity. To improve this accuracy we propose to use noninvasive tripolar concentric ring electrodes that have been shown to have significantly better signal-to-noise ratio, spatial selectivity, and mutual information compared to conventional disc electrodes. The proposed detection methodology is based on integration of multiple sensors using exponentially embedded family (EEF). In this preliminary study it is validated on over 26.3 hours of data collected using both tripolar concentric ring and conventional disc electrodes concurrently each from 7 human patients with epilepsy including five seizures. For a cross-validation based group model EEF correctly detected 100% and 80% of seizures respectively with <0.76 and <1.56 false positive detections per hour respectively for the two electrode modalities. These results clearly suggest the potential of seizure onset detection based on data from tripolar concentric ring electrodes.
Application of image recognition-based automatic hyphae detection in fungal keratitis.
Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi
2018-03-01
The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.
Automatic detection of confusion in elderly users of a web-based health instruction video.
Postma-Nilsenová, Marie; Postma, Eric; Tates, Kiek
2015-06-01
Because of cognitive limitations and lower health literacy, many elderly patients have difficulty understanding verbal medical instructions. Automatic detection of facial movements provides a nonintrusive basis for building technological tools supporting confusion detection in healthcare delivery applications on the Internet. Twenty-four elderly participants (70-90 years old) were recorded while watching Web-based health instruction videos involving easy and complex medical terminology. Relevant fragments of the participants' facial expressions were rated by 40 medical students for perceived level of confusion and analyzed with automatic software for facial movement recognition. A computer classification of the automatically detected facial features performed more accurately and with a higher sensitivity than the human observers (automatic detection and classification, 64% accuracy, 0.64 sensitivity; human observers, 41% accuracy, 0.43 sensitivity). A drill-down analysis of cues to confusion indicated the importance of the eye and eyebrow region. Confusion caused by misunderstanding of medical terminology is signaled by facial cues that can be automatically detected with currently available facial expression detection technology. The findings are relevant for the development of Web-based services for healthcare consumers.
Automatic and user-centric approaches to video summary evaluation
NASA Astrophysics Data System (ADS)
Taskiran, Cuneyt M.; Bentley, Frank
2007-01-01
Automatic video summarization has become an active research topic in content-based video processing. However, not much emphasis has been placed on developing rigorous summary evaluation methods and developing summarization systems based on a clear understanding of user needs, obtained through user centered design. In this paper we address these two topics and propose an automatic video summary evaluation algorithm adapted from teh text summarization domain.
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
Koch, Saskia B J; Klumpers, Floris; Zhang, Wei; Hashemi, Mahur M; Kaldewaij, Reinoud; van Ast, Vanessa A; Smit, Annika S; Roelofs, Karin
2017-01-01
Background : Control over automatic tendencies is often compromised in challenging situations when people fall back on automatic defensive reactions, such as freeze - fight - flight responses. Stress-induced lack of control over automatic defensive responses constitutes a problem endemic to high-risk professions, such as the police. Difficulties controlling automatic defensive responses may not only impair split-second decisions under threat, but also increase the risk for and persistence of posttraumatic stress disorder (PTSD) symptoms. However, the significance of these automatic defensive responses in the development and maintenance of trauma-related symptoms remains unclear due to a shortage of large-scale prospective studies. Objective : The 'Police-in-Action' study is conducted to investigate the role of automatic defensive responses in the development and maintenance of PTSD symptomatology after trauma exposure. Methods : In this prospective study, 340 police recruits from the Dutch Police Academy are tested before (wave 1; pre-exposure) and after (wave 2; post-exposure) their first emergency aid experiences as police officers. The two waves of data assessment are separated by approximately 15 months. To control for unspecific time effects, a well-matched control group of civilians ( n = 85) is also tested twice, approximately 15 months apart, but without being frequently exposed to potentially traumatic events. Main outcomes are associations between (changes in) behavioural, psychophysiological, endocrine and neural markers of automatic defensive responses and development of trauma-related symptoms after trauma exposure in police recruits. Discussion : This prospective study in a large group of primary responders enables us to distinguish predisposing from acquired neurobiological abnormalities in automatic defensive responses, associated with the development of trauma-related symptoms. Identifying neurobiological correlates of (vulnerability for) trauma-related psychopathology may greatly improve screening for individuals at risk for developing PTSD symptomatology and offer valuable targets for (early preventive) interventions for PTSD.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sikora, R.; Chady, T.; Baniukiewicz, P.
2010-02-22
Nondestructive testing and evaluation are under continuous development. Currently researches are concentrated on three main topics: advancement of existing methods, introduction of novel methods and development of artificial intelligent systems for automatic defect recognition (ADR). Automatic defect classification algorithm comprises of two main tasks: creating a defect database and preparing a defect classifier. Here, the database was built using defect features that describe all geometrical and texture properties of the defect. Almost twenty carefully selected features calculated for flaws extracted from real radiograms were used. The radiograms were obtained from shipbuilding industry and they were verified by qualified operator. Twomore » weld defect's classifiers based on artificial neural networks were proposed and compared. First model consisted of one neural network model, where each output neuron corresponded to different defect group. The second model contained five neural networks. Each neural network had one neuron on output and was responsible for detection of defects from one group. In order to evaluate the effectiveness of the neural networks classifiers, the mean square errors were calculated for test radiograms and compared.« less
NASA Astrophysics Data System (ADS)
Sikora, R.; Chady, T.; Baniukiewicz, P.; Caryk, M.; Piekarczyk, B.
2010-02-01
Nondestructive testing and evaluation are under continuous development. Currently researches are concentrated on three main topics: advancement of existing methods, introduction of novel methods and development of artificial intelligent systems for automatic defect recognition (ADR). Automatic defect classification algorithm comprises of two main tasks: creating a defect database and preparing a defect classifier. Here, the database was built using defect features that describe all geometrical and texture properties of the defect. Almost twenty carefully selected features calculated for flaws extracted from real radiograms were used. The radiograms were obtained from shipbuilding industry and they were verified by qualified operator. Two weld defect's classifiers based on artificial neural networks were proposed and compared. First model consisted of one neural network model, where each output neuron corresponded to different defect group. The second model contained five neural networks. Each neural network had one neuron on output and was responsible for detection of defects from one group. In order to evaluate the effectiveness of the neural networks classifiers, the mean square errors were calculated for test radiograms and compared.
Aging Influences the Neural Correlates of Lexical Decision but Not Automatic Semantic Priming
Andersen, Anders H.; Jicha, Greg A.; Smith, Charles D.
2009-01-01
Human behavioral data indicate that older adults are slower to perform lexical decisions (LDs) than young adults but show similar reaction time gains when these decisions are primed semantically. The present study explored the functional neuroanatomic bases of these frequently observed behavioral findings. Young and older groups completed unprimed and primed LD tasks while functional magnetic resonance imaging (fMRI) was recorded, using a fully randomized trial design paralleling those used in behavioral research. Results from the unprimed task found that age-related slowing of LD was associated with decreased activation in perceptual extrastriate regions and increased activation in regions associated with higher level linguistic processes, including prefrontal cortex. In contrast to these age-related changes in brain activation, the older group showed a preserved pattern of fMRI decreases in inferior temporal cortex when LD was primed semantically. These findings provide evidence that older adults’ LD abilities benefit from contexts that reduce the need for frontally mediated strategic processes and capitalize on the continued sensitivity of inferior temporal cortex to automatic semantic processes in aging. PMID:19273460
An approach for automatic classification of grouper vocalizations with passive acoustic monitoring.
Ibrahim, Ali K; Chérubin, Laurent M; Zhuang, Hanqi; Schärer Umpierre, Michelle T; Dalgleish, Fraser; Erdol, Nurgun; Ouyang, B; Dalgleish, A
2018-02-01
Grouper, a family of marine fishes, produce distinct vocalizations associated with their reproductive behavior during spawning aggregation. These low frequencies sounds (50-350 Hz) consist of a series of pulses repeated at a variable rate. In this paper, an approach is presented for automatic classification of grouper vocalizations from ambient sounds recorded in situ with fixed hydrophones based on weighted features and sparse classifier. Group sounds were labeled initially by humans for training and testing various feature extraction and classification methods. In the feature extraction phase, four types of features were used to extract features of sounds produced by groupers. Once the sound features were extracted, three types of representative classifiers were applied to categorize the species that produced these sounds. Experimental results showed that the overall percentage of identification using the best combination of the selected feature extractor weighted mel frequency cepstral coefficients and sparse classifier achieved 82.7% accuracy. The proposed algorithm has been implemented in an autonomous platform (wave glider) for real-time detection and classification of group vocalizations.
Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.
Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng
2018-04-20
Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.
Höink, Anna Janina; Schülke, Christoph; Koch, Raphael; Löhnert, Annika; Kammerer, Sara; Fortkamp, Rasmus; Heindel, Walter; Buerke, Boris
2017-11-01
Purpose To compare measurement precision and interobserver variability in the evaluation of hepatocellular carcinoma (HCC) and liver metastases in MSCT before and after transarterial local ablative therapies. Materials and Methods Retrospective study of 72 patients with malignant liver lesions (42 metastases; 30 HCCs) before and after therapy (43 SIRT procedures; 29 TACE procedures). Established (LAD; SAD; WHO) and vitality-based parameters (mRECIST; mLAD; mSAD; EASL) were assessed manually and semi-automatically by two readers. The relative interobserver difference (RID) and intraclass correlation coefficient (ICC) were calculated. Results The median RID for vitality-based parameters was lower from semi-automatic than from manual measurement of mLAD (manual 12.5 %; semi-automatic 3.4 %), mSAD (manual 12.7 %; semi-automatic 5.7 %) and EASL (manual 10.4 %; semi-automatic 1.8 %). The difference in established parameters was not statistically noticeable (p > 0.05). The ICCs of LAD (manual 0.984; semi-automatic 0.982), SAD (manual 0.975; semi-automatic 0.958) and WHO (manual 0.984; semi-automatic 0.978) are high, both in manual and semi-automatic measurements. The ICCs of manual measurements of mLAD (0.897), mSAD (0.844) and EASL (0.875) are lower. This decrease cannot be found in semi-automatic measurements of mLAD (0.997), mSAD (0.992) and EASL (0.998). Conclusion Vitality-based tumor measurements of HCC and metastases after transarterial local therapies should be performed semi-automatically due to greater measurement precision, thus increasing the reproducibility and in turn the reliability of therapeutic decisions. Key points · Liver lesion measurements according to EASL and mRECIST are more precise when performed semi-automatically.. · The higher reproducibility may facilitate a more reliable classification of therapy response.. · Measurements according to RECIST and WHO offer equivalent precision semi-automatically and manually.. Citation Format · Höink AJ, Schülke C, Koch R et al. Response Evaluation of Malignant Liver Lesions After TACE/SIRT: Comparison of Manual and Semi-Automatic Measurement of Different Response Criteria in Multislice CT. Fortschr Röntgenstr 2017; 189: 1067 - 1075. © Georg Thieme Verlag KG Stuttgart · New York.
MatchGUI: A Graphical MATLAB-Based Tool for Automatic Image Co-Registration
NASA Technical Reports Server (NTRS)
Ansar, Adnan I.
2011-01-01
MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically
Martin, Elizabeth A; Karcher, Nicole R; Bartholow, Bruce D; Siegle, Greg J; Kerns, John G
2017-03-01
Both extreme levels of social anhedonia (SocAnh) and perceptual aberration/magical ideation (PerMag) are associated with risk for schizophrenia-spectrum disorders and with emotional abnormalities. Yet, the nature of any psychophysiological-measured affective abnormality, including the role of automatic/controlled processes, is unclear. We examined the late positive potential (LPP) during passive viewing (to assess automatic processing) and during cognitive reappraisal (to assess controlled processing) in three groups: SocAnh, PerMag, and controls. The SocAnh group exhibited an increased LPP when viewing negative images. Further, SocAnh exhibited greater reductions in the LPP for negative images when told to use strategies to alter negative emotion. Similar to SocAnh, PerMag exhibited an increased LPP when viewing negative images. However, PerMag also exhibited an increased LPP when viewing positive images as well as an atypical decreased LPP when increasing positive emotion. Overall, these results suggest that at-risk groups are associated with shared and unique automatic and controlled abnormalities. Copyright © 2017 Elsevier B.V. All rights reserved.
High Performance Automatic Character Skinning Based on Projection Distance
NASA Astrophysics Data System (ADS)
Li, Jun; Lin, Feng; Liu, Xiuling; Wang, Hongrui
2018-03-01
Skeleton-driven-deformation methods have been commonly used in the character deformations. The process of painting skin weights for character deformation is a long-winded task requiring manual tweaking. We present a novel method to calculate skinning weights automatically from 3D human geometric model and corresponding skeleton. The method first, groups each mesh vertex of 3D human model to a skeleton bone by the minimum distance from a mesh vertex to each bone. Secondly, calculates each vertex's weights to the adjacent bones by the vertex's projection point distance to the bone joints. Our method's output can not only be applied to any kind of skeleton-driven deformation, but also to motion capture driven (mocap-driven) deformation. Experiments results show that our method not only has strong generality and robustness, but also has high performance.
Knowledge discovery with classification rules in a cardiovascular dataset.
Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan
2005-12-01
In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.
Automatic control of solar power plants
NASA Astrophysics Data System (ADS)
Ermakov, V. S.; Dubilovich, V. M.
1982-02-01
The automatic control of the heliostat field of a 200-MW solar power plant is discussed. The advantages of the decentralized control principle with the solution of a number of individual problems in a single control center are emphasized. The basic requirements on heliostat construction are examined, and possible functional schemes for the automatic control of a heliostat field are described. It is proposed that groups of heliostats can be controlled from a single center and on the basis of a single algorithm.
Oudman, Erik; Van der Stigchel, Stefan; Nijboer, Tanja C W; Wijnia, Jan W; Seekles, Maaike L; Postma, Albert
2016-03-01
Korsakoff's syndrome (KS) is characterized by explicit amnesia, but relatively spared implicit memory. The aim of this study was to assess to what extent KS patients can acquire spatial information while performing a spatial navigation task. Furthermore, we examined whether residual spatial acquisition in KS was based on automatic or effortful coding processes. Therefore, 20 KS patients and 20 matched healthy controls performed six tasks on spatial navigation after they navigated through a residential area. Ten participants per group were instructed to pay close attention (intentional condition), while 10 received mock instructions (incidental condition). KS patients showed hampered performance on a majority of tasks, yet their performance was superior to chance level on a route time and distance estimation tasks, a map drawing task and a route walking task. Performance was relatively spared on the route distance estimation task, but there were large variations between participants. Acquisition in KS was automatic rather than effortful, since no significant differences were obtained between the intentional and incidental condition on any task, whereas for the healthy controls, the intention to learn was beneficial for the map drawing task and the route walking task. The results of this study suggest that KS patients are still able to acquire spatial information during navigation on multiple domains despite the presence of the explicit amnesia. Residual acquisition is most likely based on automatic coding processes. © 2014 The British Psychological Society.
Bernardo, Danilo; Nariai, Hiroki; Hussain, Shaun A; Sankar, Raman; Salamon, Noriko; Krueger, Darcy A; Sahin, Mustafa; Northrup, Hope; Bebin, E Martina; Wu, Joyce Y
2018-04-03
We aim to establish that interictal fast ripples (FR; 250-500 Hz) are detectable on scalp EEG, and to investigate their association to epilepsy. Scalp EEG recordings of a subset of children with tuberous sclerosis complex (TSC)-associated epilepsy from two large multicenter observational TSC studies were analyzed and compared to control children without epilepsy or any other brain-based diagnoses. FR were identified both by human visual review and compared with semi-automated review utilizing a deep learning-based FR detector. Seven out of 7 children with TSC-associated epilepsy had scalp FR compared to 0 out of 4 children in the control group (p = 0.003). The automatic detector has a sensitivity of 98% and false positive rate with average of 11.2 false positives per minute. Non-invasive detection of interictal scalp FR was feasible, by both visual and semi-automatic detection. Interictal scalp FR occurred exclusively in children with TSC-associated epilepsy and were absent in controls without epilepsy. The proposed detector achieves high sensitivity of FR detection; however, expert review of the results to reduce false positives is advised. Interictal FR are detectable on scalp EEG and may potentially serve as a biomarker of epilepsy in children with TSC. Copyright © 2018 International Federation of Clinical Neurophysiology. All rights reserved.
Assessing Walking Strategies Using Insole Pressure Sensors for Stroke Survivors.
Munoz-Organero, Mario; Parker, Jack; Powell, Lauren; Mawson, Susan
2016-10-01
Insole pressure sensors capture the different forces exercised over the different parts of the sole when performing tasks standing up such as walking. Using data analysis and machine learning techniques, common patterns and strategies from different users to achieve different tasks can be automatically extracted. In this paper, we present the results obtained for the automatic detection of different strategies used by stroke survivors when walking as integrated into an Information Communication Technology (ICT) enhanced Personalised Self-Management Rehabilitation System (PSMrS) for stroke rehabilitation. Fourteen stroke survivors and 10 healthy controls have participated in the experiment by walking six times a distance from chair to chair of approximately 10 m long. The Rivermead Mobility Index was used to assess the functional ability of each individual in the stroke survivor group. Several walking strategies are studied based on data gathered from insole pressure sensors and patterns found in stroke survivor patients are compared with average patterns found in healthy control users. A mechanism to automatically estimate a mobility index based on the similarity of the pressure patterns to a stereotyped stride is also used. Both data gathered from stroke survivors and healthy controls are used to evaluate the proposed mechanisms. The output of trained algorithms is applied to the PSMrS system to provide feedback on gait quality enabling stroke survivors to self-manage their rehabilitation.
Shaheen, E; Mowafy, B; Politis, C; Jacobs, R
2017-12-01
Previous research proposed the use of the mandibular midline neurovascular canal structures as a forensic finger print. In their observer study, an average correct identification of 95% was reached which triggered this study. To present a semi-automatic computer recognition approach to replace the observers and to validate the accuracy of this newly proposed method. Imaging data from Computer Tomography (CT) and Cone Beam Computer Tomography (CBCT) of mandibles scanned at two different moments were collected to simulate an AM and PM situation where the first scan presented AM and the second scan was used to simulate PM. Ten cases with 20 scans were used to build a classifier which relies on voxel based matching and results with classification into one of two groups: "Unmatched" and "Matched". This protocol was then tested using five other scans out of the database. Unpaired t-testing was applied and accuracy of the computerized approach was determined. A significant difference was found between the "Unmatched" and "Matched" classes with means of 0.41 and 0.86 respectively. Furthermore, the testing phase showed an accuracy of 100%. The validation of this method pushes this protocol further to a fully automatic identification procedure for victim identification based on the mandibular midline canals structures only in cases with available AM and PM CBCT/CT data.
NASA Astrophysics Data System (ADS)
Gao, M.; Li, J.
2018-04-01
Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.
Synonym set extraction from the biomedical literature by lexical pattern discovery.
McCrae, John; Collier, Nigel
2008-03-24
Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction based on patterns was first suggested by Hearst 1, but it is still not clear how to automatically construct such patterns for different semantic relations and domains. In particular it is not certain which patterns are useful for capturing synonymy. The assumption of extant resources such as parsers is also a limiting factor for many languages, so it is desirable to find patterns that do not use syntactical analysis. Finally to give a more consistent and applicable result it is desirable to use these patterns to form synonym sets in a sound way. We present a method that automatically generates regular expression patterns by expanding seed patterns in a heuristic search and then develops a feature vector based on the occurrence of term pairs in each developed pattern. This allows for a binary classifications of term pairs as synonymous or non-synonymous. We then model this result as a probability graph to find synonym sets, which is equivalent to the well-studied problem of finding an optimal set cover. We achieved 73.2% precision and 29.7% recall by our method, out-performing hand-made resources such as MeSH and Wikipedia. We conclude that automatic methods can play a practical role in developing new thesauri or expanding on existing ones, and this can be done with only a small amount of training data and no need for resources such as parsers. We also concluded that the accuracy can be improved by grouping into synonym sets.
Jones, Travis M; Drew, Richard H; Wilson, Dustin T; Sarubbi, Christina; Anderson, Deverick J
2017-12-01
The impact of automatic infectious diseases (ID) consultation for inpatients with fungemia at a large academic medical center was studied. In this single-center, retrospective study, the time to appropriate antifungal therapy before and after implementing a policy requiring automatic ID consultation for the management of fungemia for all patients with an inpatient positive blood culture for fungus was examined. The rates of ID consultation; the likelihood of receiving appropriate antifungal therapy; central venous catheter (CVC) removal rates; performance of ophthalmologic examinations; infection-related length of stay (LOS); rates of all-cause inhospital mortality, death, or transfer to an intensive care unit within 7 days of first culture; and inpatient cost of antifungals were also evaluated. A total of 173 unique episodes (94 and 79 in the control and intervention groups, respectively) were included. Candida species were the most frequently cultured organisms, isolated from over 90% of patients in both groups. No differences were observed between the control and intervention groups in time to appropriate therapy, infection-related LOS, or time to CVC removal. However, patients in the intervention group were more likely than those in the control group to receive appropriate antifungal therapy ( p = 0.0392), undergo ophthalmologic examination ( p = 0.003), have their CVC removed ( p = 0.0038), and receive ID consultation ( p = 0.0123). Inpatient antifungal costs were significantly higher in the intervention group ( p = 0.0177). While automatic ID consultation for inpatients with fungemia did not affect the time to administration of appropriate therapy, improvement was observed for several process indicators, including rates of appropriate antifungal therapy selection, time to removal of CVCs, and performance of ophthalmologic examinations. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.
Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra
2014-01-01
Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. The aims were to describe how to:(i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and(ii) automatically identify the features that best distinguish the groups. The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo 18 were used,which included 200 healthy Brazilians of both genders. A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods.
Ruiz-Peña, Juan Luís; Duque, Pablo; Izquierdo, Guillermo
2008-01-01
Background A software based tool has been developed (Optem) to allow automatize the recommendations of the Canadian Multiple Sclerosis Working Group for optimizing MS treatment in order to avoid subjective interpretation. Methods Treatment Optimization Recommendations (TORs) were applied to our database of patients treated with IFN β1a IM. Patient data were assessed during year 1 for disease activity, and patients were assigned to 2 groups according to TOR: "change treatment" (CH) and "no change treatment" (NCH). These assessments were then compared to observed clinical outcomes for disease activity over the following years. Results We have data on 55 patients. The "change treatment" status was assigned to 22 patients, and "no change treatment" to 33 patients. The estimated sensitivity and specificity according to last visit status were 73.9% and 84.4%. During the following years, the Relapse Rate was always higher in the "change treatment" group than in the "no change treatment" group (5 y; CH: 0.7, NCH: 0.07; p < 0.001, 12 m – last visit; CH: 0.536, NCH: 0.34). We obtained the same results with the EDSS (4 y; CH: 3.53, NCH: 2.55, annual progression rate in 12 m – last visit; CH: 0.29, NCH: 0.13). Conclusion Applying TOR at the first year of therapy allowed accurate prediction of continued disease activity in relapses and disability progression. PMID:18325088
Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.
Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin
2015-01-01
Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.
Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information
Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin
2015-01-01
Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294
Iancu, I; Bodner, E; Joubran, S; Ben Zion, I; Ram, E
2015-05-01
Social Anxiety Disorder (SAD) has been repeatedly shown to be very prevalent in the Western society and is characterized by low self-esteem, pessimism, procrastination and also perfectionism. Very few studies on SAD have been done in the Middle East or in Arab countries, and no study tackled the relationship between social anxiety symptoms and perfectionism in non-Western samples. We examined social anxiety symptoms and perfectionism in a group of 132 Israeli Jewish (IJ) and Israeli Arab (IA) students. Subjects completed the Liebowitz Social Anxiety Scale (LSAS), the Multidimensional Perfectionism Scale (MPS), the Negative Automatic Thoughts Questionnaire (ATQ-N), the Positive Automatic Thoughts Questionnaire (ATQ-P) and a socio-demographic questionnaire. The rate of SAD in our sample according to a LSAS score of 60 or more was 17.2% (IJ=13.8%, IA=19%, ns). The correlation between perfectionism and the LSAS was high in both groups, and in particular in the IJ group. The IA group had higher scores of social avoidance, of ATQ-P and of two of the MPS subscales: parental expectations and parental criticism. Concern over mistakes and negative automatic thoughts positively predicted social fear in the IJ group, whereas in the IA group being female, religious and less educated positively predicted social fear. Negative automatic thoughts and age positively predicted social avoidance in the IJ group. In general, the IJ and IA subjects showed higher social anxiety, higher ATQ-N scores and lower parental expectations as compared with non-clinical US samples. Social anxiety symptoms and perfectionism are prevalent in Arab and Jewish students in Israel and seem to be closely related. Further studies among non-western minority groups may detect cultural influences on social anxiety and might add to the growing body of knowledge on this intriguing condition. Copyright © 2014 Elsevier Inc. All rights reserved.
Boriani, Giuseppe; Da Costa, Antoine; Ricci, Renato Pietro; Quesada, Aurelio; Favale, Stefano; Iacopino, Saverio; Romeo, Francesco; Risi, Arnaldo; Mangoni di S Stefano, Lorenza; Navarro, Xavier; Biffi, Mauro; Santini, Massimo; Burri, Haran
2013-08-21
Remote monitoring (RM) in patients with advanced heart failure and cardiac resynchronization therapy defibrillators (CRT-D) may reduce delays in clinical decisions by transmitting automatic alerts. However, this strategy has never been tested specifically in this patient population, with alerts for lung fluid overload, and in a European setting. The main objective of Phase 1 (presented here) is to evaluate if RM strategy is able to reduce time from device-detected events to clinical decisions. In this multicenter randomized controlled trial, patients with moderate to severe heart failure implanted with CRT-D devices were randomized to a Remote group (with remote follow-up and wireless automatic alerts) or to a Control group (with standard follow-up without alerts). The primary endpoint of Phase 1 was the delay between an alert event and clinical decisions related to the event in the first 154 enrolled patients followed for 1 year. The median delay from device-detected events to clinical decisions was considerably shorter in the Remote group compared to the Control group: 2 (25(th)-75(th) percentile, 1-4) days vs 29 (25(th)-75(th) percentile, 3-51) days respectively, P=.004. In-hospital visits were reduced in the Remote group (2.0 visits/patient/year vs 3.2 visits/patient/year in the Control group, 37.5% relative reduction, P<.001). Automatic alerts were successfully transmitted in 93% of events occurring outside the hospital in the Remote group. The annual rate of all-cause hospitalizations per patient did not differ between the two groups (P=.65). RM in CRT-D patients with advanced heart failure allows physicians to promptly react to clinically relevant automatic alerts and significantly reduces the burden of in-hospital visits. Clinicaltrials.gov NCT00885677; http://clinicaltrials.gov/show/NCT00885677 (Archived by WebCite at http://www.webcitation.org/6IkcCJ7NF).
Da Costa, Antoine; Ricci, Renato Pietro; Quesada, Aurelio; Favale, Stefano; Iacopino, Saverio; Romeo, Francesco; Risi, Arnaldo; Mangoni di S Stefano, Lorenza; Navarro, Xavier; Biffi, Mauro; Santini, Massimo; Burri, Haran
2013-01-01
Background Remote monitoring (RM) in patients with advanced heart failure and cardiac resynchronization therapy defibrillators (CRT-D) may reduce delays in clinical decisions by transmitting automatic alerts. However, this strategy has never been tested specifically in this patient population, with alerts for lung fluid overload, and in a European setting. Objective The main objective of Phase 1 (presented here) is to evaluate if RM strategy is able to reduce time from device-detected events to clinical decisions. Methods In this multicenter randomized controlled trial, patients with moderate to severe heart failure implanted with CRT-D devices were randomized to a Remote group (with remote follow-up and wireless automatic alerts) or to a Control group (with standard follow-up without alerts). The primary endpoint of Phase 1 was the delay between an alert event and clinical decisions related to the event in the first 154 enrolled patients followed for 1 year. Results The median delay from device-detected events to clinical decisions was considerably shorter in the Remote group compared to the Control group: 2 (25th-75th percentile, 1-4) days vs 29 (25th-75th percentile, 3-51) days respectively, P=.004. In-hospital visits were reduced in the Remote group (2.0 visits/patient/year vs 3.2 visits/patient/year in the Control group, 37.5% relative reduction, P<.001). Automatic alerts were successfully transmitted in 93% of events occurring outside the hospital in the Remote group. The annual rate of all-cause hospitalizations per patient did not differ between the two groups (P=.65). Conclusions RM in CRT-D patients with advanced heart failure allows physicians to promptly react to clinically relevant automatic alerts and significantly reduces the burden of in-hospital visits. Trial Registration Clinicaltrials.gov NCT00885677; http://clinicaltrials.gov/show/NCT00885677 (Archived by WebCite at http://www.webcitation.org/6IkcCJ7NF). PMID:23965236
NASA Astrophysics Data System (ADS)
Pujayanto, Pujayanto; Budiharti, Rini; Adhitama, Egy; Nuraini, Niken Rizky Amalia; Vernanda Putri, Hanung
2018-07-01
This research proposes the development of a web-based assessment system to identify students’ misconception. The system, named WAS (web-based assessment system), can identify students’ misconception profile on linear kinematics automatically after the student has finished the test. The test instrument was developed and validated. Items were constructed and arranged from the result of a focus group discussion (FGD), related to previous research. Fifty eight students (female = 37, male = 21) were used as samples. They were from different classes with 18 students from the gifted class and another 40 students from the normal class. WAS was designed specifically to support the teacher as an efficient replacement for a paper-based test system. In addition, WAS offers flexible timing functionally, stand-alone subject module, robustness and scalability. The entire WAS program and interface was developed with open source-based technologies such as the XAMP server, MySQL database, Javascript and PHP. It provides results immediately and provides diagrammatic questions as well as scientific symbols. It is feasible to apply this system to many students at once. Thus, it could be integrated in many schools as part of physics courses.
Trust, control strategies and allocation of function in human-machine systems.
Lee, J; Moray, N
1992-10-01
As automated controllers supplant human intervention in controlling complex systems, the operators' role often changes from that of an active controller to that of a supervisory controller. Acting as supervisors, operators can choose between automatic and manual control. Improperly allocating function between automatic and manual control can have negative consequences for the performance of a system. Previous research suggests that the decision to perform the job manually or automatically depends, in part, upon the trust the operators invest in the automatic controllers. This paper reports an experiment to characterize the changes in operators' trust during an interaction with a semi-automatic pasteurization plant, and investigates the relationship between changes in operators' control strategies and trust. A regression model identifies the causes of changes in trust, and a 'trust transfer function' is developed using time series analysis to describe the dynamics of trust. Based on a detailed analysis of operators' strategies in response to system faults we suggest a model for the choice between manual and automatic control, based on trust in automatic controllers and self-confidence in the ability to control the system manually.
Model-Based Reasoning in Humans Becomes Automatic with Training.
Economides, Marcos; Kurth-Nelson, Zeb; Lübbert, Annika; Guitart-Masip, Marc; Dolan, Raymond J
2015-09-01
Model-based and model-free reinforcement learning (RL) have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.
Conceptual size in developmental dyscalculia and dyslexia.
Gliksman, Yarden; Henik, Avishai
2018-02-01
People suffering from developmental dyscalculia (DD) are known to have impairment in numerical abilities and have been found to have weaker processing of countable magnitudes. However, not much research was done on their abilities to process noncountable magnitudes. An example of noncountable magnitude is conceptual size (e.g., mouse is small and elephant is big). Recently, we found that adults process conceptual size automatically. The current study examined automatic processing of conceptual size in students with DD and developmental dyslexia. Conceptual and physical sizes were manipulated orthogonally to create congruent (e.g., a physically small apple compared to a physically large violin) and incongruent (e.g., a physically large apple compared to a physically small violin) conditions. Participants were presented with 2 objects and had to choose the larger one. Each trial began with an instruction to respond to the physical or to the conceptual dimension. Control and the dyslexic groups presented automatic processing of both conceptual and physical sizes. The dyscalculic group presented automatic processing of physical size but not automaticity of processing conceptual size. Our results fit with previous findings of weaker magnitude representation in those with DD, specifically regarding noncountable magnitudes, and support theories of a shared neurocognitive substrate for different types of magnitudes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Imitation inhibition in children with Tourette syndrome.
Brandt, Valerie Cathérine; Moczydlowski, Agnes; Jonas, Melanie; Boelmans, Kai; Bäumer, Tobias; Brass, Marcel; Münchau, Alexander
2017-08-12
Echopraxia, that is, the open and automatic imitation of other peoples' actions, is common in patients with Gilles de la Tourette syndrome, autism spectrum disorder, and also those with frontal lobe lesions. While systematic reaction time tasks have confirmed increased automatic imitation in the latter two groups, adult patients with Tourette syndrome appear to compensate for automatic imitation tendencies by an overall slowing in response times. However, whether children with Tourette syndrome are already able to inhibit automatic imitation tendencies has not been investigated. Fifteen children with Tourette syndrome and 15 healthy children (aged 7-12 years) performed an imitation inhibition paradigm. Participants were asked to respond to an auditory cue by lifting their index finger or their little finger. Participants were simultaneously presented with either compatible or incompatible visual stimuli. Overall responses in children with Tourette syndrome were slower than in healthy children. Although responses were faster in compatible than in incompatible trials in both groups, this 'interference effect' was smaller in children with Tourette syndrome. Children with Tourette syndrome have a smaller interference effect than healthy children, indicating an enhanced ability to behaviourally control automatic imitation tendencies at the cost of reacting slower. The results suggest that children with Tourette syndrome already employ different or additional inhibition strategies compared to healthy children. © 2017 The British Psychological Society.
Grazing Soybean to Increase Voluntary Cow Traffic in a Pasture-based Automatic Milking System
Clark, C. E. F.; Horadagoda, A.; Kerrisk, K. L.; Scott, V.; Islam, M. R.; Kaur, R.; Garcia, S. C.
2014-01-01
Pasture-based automatic milking systems (AMS) require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max) with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group) with a 2×2 Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov.) pasture (pasture) or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ≈18 L/cow/d) in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner) exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation) relative to pasture (4.7 kg/cow/d/allocation). Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages. PMID:25049970
Gerth, Sabrina; Klassert, Annegret; Dolk, Thomas; Fliesser, Michael; Fischer, Martin H; Nottbusch, Guido; Festman, Julia
2016-01-01
Due to their multifunctionality, tablets offer tremendous advantages for research on handwriting dynamics or for interactive use of learning apps in schools. Further, the widespread use of tablet computers has had a great impact on handwriting in the current generation. But, is it advisable to teach how to write and to assess handwriting in pre- and primary schoolchildren on tablets rather than on paper? Since handwriting is not automatized before the age of 10 years, children's handwriting movements require graphomotor and visual feedback as well as permanent control of movement execution during handwriting. Modifications in writing conditions, for instance the smoother writing surface of a tablet, might influence handwriting performance in general and in particular those of non-automatized beginning writers. In order to investigate how handwriting performance is affected by a difference in friction of the writing surface, we recruited three groups with varying levels of handwriting automaticity: 25 preschoolers, 27 second graders, and 25 adults. We administered three tasks measuring graphomotor abilities, visuomotor abilities, and handwriting performance (only second graders and adults). We evaluated two aspects of handwriting performance: the handwriting quality with a visual score and the handwriting dynamics using online handwriting measures [e.g., writing duration, writing velocity, strokes and number of inversions in velocity (NIV)]. In particular, NIVs which describe the number of velocity peaks during handwriting are directly related to the level of handwriting automaticity. In general, we found differences between writing on paper compared to the tablet. These differences were partly task-dependent. The comparison between tablet and paper revealed a faster writing velocity for all groups and all tasks on the tablet which indicates that all participants-even the experienced writers-were influenced by the lower friction of the tablet surface. Our results for the group-comparison show advancing levels in handwriting automaticity from preschoolers to second graders to adults, which confirms that our method depicts handwriting performance in groups with varying degrees of handwriting automaticity. We conclude that the smoother tablet surface requires additional control of handwriting movements and therefore might present an additional challenge for learners of handwriting.
Gerth, Sabrina; Klassert, Annegret; Dolk, Thomas; Fliesser, Michael; Fischer, Martin H.; Nottbusch, Guido; Festman, Julia
2016-01-01
Due to their multifunctionality, tablets offer tremendous advantages for research on handwriting dynamics or for interactive use of learning apps in schools. Further, the widespread use of tablet computers has had a great impact on handwriting in the current generation. But, is it advisable to teach how to write and to assess handwriting in pre- and primary schoolchildren on tablets rather than on paper? Since handwriting is not automatized before the age of 10 years, children's handwriting movements require graphomotor and visual feedback as well as permanent control of movement execution during handwriting. Modifications in writing conditions, for instance the smoother writing surface of a tablet, might influence handwriting performance in general and in particular those of non-automatized beginning writers. In order to investigate how handwriting performance is affected by a difference in friction of the writing surface, we recruited three groups with varying levels of handwriting automaticity: 25 preschoolers, 27 second graders, and 25 adults. We administered three tasks measuring graphomotor abilities, visuomotor abilities, and handwriting performance (only second graders and adults). We evaluated two aspects of handwriting performance: the handwriting quality with a visual score and the handwriting dynamics using online handwriting measures [e.g., writing duration, writing velocity, strokes and number of inversions in velocity (NIV)]. In particular, NIVs which describe the number of velocity peaks during handwriting are directly related to the level of handwriting automaticity. In general, we found differences between writing on paper compared to the tablet. These differences were partly task-dependent. The comparison between tablet and paper revealed a faster writing velocity for all groups and all tasks on the tablet which indicates that all participants—even the experienced writers—were influenced by the lower friction of the tablet surface. Our results for the group-comparison show advancing levels in handwriting automaticity from preschoolers to second graders to adults, which confirms that our method depicts handwriting performance in groups with varying degrees of handwriting automaticity. We conclude that the smoother tablet surface requires additional control of handwriting movements and therefore might present an additional challenge for learners of handwriting. PMID:27672372
Automatic spatiotemporal matching of detected pleural thickenings
NASA Astrophysics Data System (ADS)
Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas
2014-01-01
Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).
Expert system for generating initial layouts of zoom systems with multiple moving lens groups
NASA Astrophysics Data System (ADS)
Cheng, Xuemin; Wang, Yongtian; Hao, Qun; Sasián, José M.
2005-01-01
An expert system is developed for the automatic generation of initial layouts for the design of zoom systems with multiple moving lens groups. The Gaussian parameters of the zoom system are optimized using the damped-least-squares method to achieve smooth zoom cam curves, with the f-number of each lens group in the zoom system constrained to a rational value. Then each lens group is selected automatically from a database according to its range of f-number, field of view, and magnification ratio as it is used in the zoom system. The lens group database is established from the results of analyzing thousands of zoom lens patents. Design examples are given, which show that the scheme is a practical approach to generate starting points for zoom lens design.
Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte
2016-07-01
Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Controlled cooling of an electronic system based on projected conditions
David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.
2016-05-17
Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.
Controlled cooling of an electronic system based on projected conditions
David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.
2015-08-18
Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.
An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization
NASA Astrophysics Data System (ADS)
Chen, Li; Weng, Zhiqiang; Goh, LaiYoong; Garland, Marc
2002-09-01
A new algorithm for automatic phase correction of NMR spectra based on entropy minimization is proposed. The optimal zero-order and first-order phase corrections for a NMR spectrum are determined by minimizing entropy. The objective function is constructed using a Shannon-type information entropy measure. Entropy is defined as the normalized derivative of the NMR spectral data. The algorithm has been successfully applied to experimental 1H NMR spectra. The results of automatic phase correction are found to be comparable to, or perhaps better than, manual phase correction. The advantages of this automatic phase correction algorithm include its simple mathematical basis and the straightforward, reproducible, and efficient optimization procedure. The algorithm is implemented in the Matlab program ACME—Automated phase Correction based on Minimization of Entropy.
IntegratedMap: a Web interface for integrating genetic map data.
Yang, Hongyu; Wang, Hongyu; Gingle, Alan R
2005-05-01
IntegratedMap is a Web application and database schema for storing and interactively displaying genetic map data. Its Web interface includes a menu for direct chromosome/linkage group selection, a search form for selection based on mapped object location and linkage group displays. An overview display provides convenient access to the full range of mapped and anchored object types with genetic locus details, such as numbers, types and names of mapped/anchored objects displayed in a compact scrollable list box that automatically updates based on selected map location and object type. Also, multilinkage group and localized map views are available along with links that can be configured for integration with other Web resources. IntegratedMap is implemented in C#/ASP.NET and the package, including a MySQL schema creation script, is available from http://cggc.agtec.uga.edu/Data/download.asp
DeRobertis, Christopher V.; Lu, Yantian T.
2010-02-23
A method, system, and program storage device for creating a new user account or user group with a unique identification number in a computing environment having multiple user registries is provided. In response to receiving a command to create a new user account or user group, an operating system of a clustered computing environment automatically checks multiple registries configured for the operating system to determine whether a candidate identification number for the new user account or user group has been assigned already to one or more existing user accounts or groups, respectively. The operating system automatically assigns the candidate identification number to the new user account or user group created in a target user registry if the checking indicates that the candidate identification number has not been assigned already to any of the existing user accounts or user groups, respectively.
Automatic cataloguing and characterization of Earth science data using SE-trees
NASA Technical Reports Server (NTRS)
Rymon, Ron; Short, Nicholas M., Jr.
1994-01-01
In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.
Iakovidis, Dimitris K; Koulaouzidis, Anastasios
2014-11-01
The advent of wireless capsule endoscopy (WCE) has revolutionized the diagnostic approach to small-bowel disease. However, the task of reviewing WCE video sequences is laborious and time-consuming; software tools offering automated video analysis would enable a timelier and potentially a more accurate diagnosis. To assess the validity of innovative, automatic lesion-detection software in WCE. A color feature-based pattern recognition methodology was devised and applied to the aforementioned image group. This study was performed at the Royal Infirmary of Edinburgh, United Kingdom, and the Technological Educational Institute of Central Greece, Lamia, Greece. A total of 137 deidentified WCE single images, 77 showing pathology and 60 normal images. The proposed methodology, unlike state-of-the-art approaches, is capable of detecting several different types of lesions. The average performance, in terms of the area under the receiver-operating characteristic curve, reached 89.2 ± 0.9%. The best average performance was obtained for angiectasias (97.5 ± 2.4%) and nodular lymphangiectasias (96.3 ± 3.6%). Single expert for annotation of pathologies, single type of WCE model, use of single images instead of entire WCE videos. A simple, yet effective, approach allowing automatic detection of all types of abnormalities in capsule endoscopy is presented. Based on color pattern recognition, it outperforms previous state-of-the-art approaches. Moreover, it is robust in the presence of luminal contents and is capable of detecting even very small lesions. Crown Copyright © 2014. Published by Elsevier Inc. All rights reserved.
Component Processes Subserving Rapid Automatized Naming in Dyslexic and Non-Dyslexic Readers
ERIC Educational Resources Information Center
Araujo, Susana; Inacio, Filomena; Francisco, Ana; Faisca, Luis; Petersson, Karl Magnus; Reis, Alexandra
2011-01-01
The current study investigated which time components of rapid automatized naming (RAN) predict group differences between dyslexic and non-dyslexic readers (matched for age and reading level), and how these components relate to different reading measures. Subjects performed two RAN tasks (letters and objects), and data were analyzed through a…
Automatic Speech Recognition Technology as an Effective Means for Teaching Pronunciation
ERIC Educational Resources Information Center
Elimat, Amal Khalil; AbuSeileek, Ali Farhan
2014-01-01
This study aimed to explore the effect of using automatic speech recognition technology (ASR) on the third grade EFL students' performance in pronunciation, whether teaching pronunciation through ASR is better than regular instruction, and the most effective teaching technique (individual work, pair work, or group work) in teaching pronunciation…
Learner Attention to Form in ACCESS Task-Based Interaction
ERIC Educational Resources Information Center
Dao, Phung; Iwashita, Noriko; Gatbonton, Elizabeth
2017-01-01
This study explored the potential effects of communicative tasks developed using a reformulation of a task-based language teaching called Automatization in Communicative Contexts of Essential Speech Sequences (ACCESS) that includes automatization of language elements as one of its goals on learner attention to form in task-based interaction. The…
Automatic mental associations predict future choices of undecided decision-makers.
Galdi, Silvia; Arcuri, Luciano; Gawronski, Bertram
2008-08-22
Common wisdom holds that choice decisions are based on conscious deliberations of the available information about choice options. On the basis of recent insights about unconscious influences on information processing, we tested whether automatic mental associations of undecided individuals bias future choices in a manner such that these choices reflect the evaluations implied by earlier automatic associations. With the use of a computer-based, speeded categorization task to assess automatic mental associations (i.e., associations that are activated unintentionally, difficult to control, and not necessarily endorsed at a conscious level) and self-report measures to assess consciously endorsed beliefs and choice preferences, automatic associations of undecided participants predicted changes in consciously reported beliefs and future choices over a period of 1 week. Conversely, for decided participants, consciously reported beliefs predicted changes in automatic associations and future choices over the same period. These results indicate that decision-makers sometimes have already made up their mind at an unconscious level, even when they consciously indicate that they are still undecided.
NASA Astrophysics Data System (ADS)
Maspero, Matteo; van den Berg, Cornelis A. T.; Zijlstra, Frank; Sikkes, Gonda G.; de Boer, Hans C. J.; Meijer, Gert J.; Kerkmeijer, Linda G. W.; Viergever, Max A.; Lagendijk, Jan J. W.; Seevinck, Peter R.
2017-10-01
An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of 1.1 × 1.1 × 1.2 mm3 and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.
Marjanovic, Nicolas; Le Floch, Soizig; Jaffrelot, Morgan; L'Her, Erwan
2014-05-01
In the absence of endotracheal intubation, the manual bag-valve-mask (BVM) is the most frequently used ventilation technique during resuscitation. The efficiency of other devices has been poorly studied. The bench-test study described here was designed to evaluate the effectiveness of an automatic, manually triggered system, and to compare it with manual BVM ventilation. A respiratory system bench model was assembled using a lung simulator connected to a manikin to simulate a patient with unprotected airways. Fifty health-care providers from different professional groups (emergency physicians, residents, advanced paramedics, nurses, and paramedics; n = 10 per group) evaluated manual BVM ventilation, and compared it with an automatic manually triggered device (EasyCPR). Three pathological situations were simulated (restrictive, obstructive, normal). Standard ventilation parameters were recorded; the ergonomics of the system were assessed by the health-care professionals using a standard numerical scale once the recordings were completed. The tidal volume fell within the standard range (400-600 mL) for 25.6% of breaths (0.6-45 breaths) using manual BVM ventilation, and for 28.6% of breaths (0.3-80 breaths) using the automatic manually triggered device (EasyCPR) (P < .0002). Peak inspiratory airway pressure was lower using the automatic manually triggered device (EasyCPR) (10.6 ± 5 vs 15.9 ± 10 cm H2O, P < .001). The ventilation rate fell consistently within the guidelines, in the case of the automatic manually triggered device (EasyCPR) only (10.3 ± 2 vs 17.6 ± 6, P < .001). Significant pulmonary overdistention was observed when using the manual BVM device during the normal and obstructive sequences. The nurses and paramedics considered the ergonomics of the automatic manually triggered device (EasyCPR) to be better than those of the manual device. The use of an automatic manually triggered device may improve ventilation efficiency and decrease the risk of pulmonary overdistention, while decreasing the ventilation rate.
NASA Astrophysics Data System (ADS)
Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng
2007-11-01
As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.
Wilkins, Nicolas J; Rawson, Katherine A
2013-10-01
In Rickard, Lau, and Pashler's (2008) investigation of the lag effect on memory-based automaticity, response times were faster and proportion of trials retrieved was higher at the end of practice for short lag items than for long lag items. However, during testing after a delay, response times were slower and proportion of trials retrieved was lower for short lag items than for long lag items. The current study investigated the extent to which the lag effect on the durability of memory-based automaticity is due to interference or to the loss of memory strength with time. Participants repeatedly practiced alphabet subtraction items in short lag and long lag conditions. After practice, half of the participants were immediately tested and the other half were tested after a 7-day delay. Results indicate that the lag effect on the durability of memory-based automaticity is primarily due to interference. We discuss potential modification of current memory-based processing theories to account for these effects. © 2013.
Terminal Sliding Mode Tracking Controller Design for Automatic Guided Vehicle
NASA Astrophysics Data System (ADS)
Chen, Hongbin
2018-03-01
Based on sliding mode variable structure control theory, the path tracking problem of automatic guided vehicle is studied, proposed a controller design method based on the terminal sliding mode. First of all, through analyzing the characteristics of the automatic guided vehicle movement, the kinematics model is presented. Then to improve the traditional expression of terminal sliding mode, design a nonlinear sliding mode which the convergence speed is faster than the former, verified by theoretical analysis, the design of sliding mode is steady and fast convergence in the limited time. Finally combining Lyapunov method to design the tracking control law of automatic guided vehicle, the controller can make the automatic guided vehicle track the desired trajectory in the global sense as well as in finite time. The simulation results verify the correctness and effectiveness of the control law.
Design of cylindrical pipe automatic welding control system based on STM32
NASA Astrophysics Data System (ADS)
Chen, Shuaishuai; Shen, Weicong
2018-04-01
The development of modern economy makes the demand for pipeline construction and construction rapidly increasing, and the pipeline welding has become an important link in pipeline construction. At present, there are still a large number of using of manual welding methods at home and abroad, and field pipe welding especially lacks miniature and portable automatic welding equipment. An automated welding system consists of a control system, which consisting of a lower computer control panel and a host computer operating interface, as well as automatic welding machine mechanisms and welding power systems in coordination with the control system. In this paper, a new control system of automatic pipe welding based on the control panel of the lower computer and the interface of the host computer is proposed, which has many advantages over the traditional automatic welding machine.
a Two-Step Classification Approach to Distinguishing Similar Objects in Mobile LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
He, H.; Khoshelham, K.; Fraser, C.
2017-09-01
Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.
SAR image segmentation using skeleton-based fuzzy clustering
NASA Astrophysics Data System (ADS)
Cao, Yun Yi; Chen, Yan Qiu
2003-06-01
SAR image segmentation can be converted to a clustering problem in which pixels or small patches are grouped together based on local feature information. In this paper, we present a novel framework for segmentation. The segmentation goal is achieved by unsupervised clustering upon characteristic descriptors extracted from local patches. The mixture model of characteristic descriptor, which combines intensity and texture feature, is investigated. The unsupervised algorithm is derived from the recently proposed Skeleton-Based Data Labeling method. Skeletons are constructed as prototypes of clusters to represent arbitrary latent structures in image data. Segmentation using Skeleton-Based Fuzzy Clustering is able to detect the types of surfaces appeared in SAR images automatically without any user input.
Content-based analysis of Ki-67 stained meningioma specimens for automatic hot-spot selection.
Swiderska-Chadaj, Zaneta; Markiewicz, Tomasz; Grala, Bartlomiej; Lorent, Malgorzata
2016-10-07
Hot-spot based examination of immunohistochemically stained histological specimens is one of the most important procedures in pathomorphological practice. The development of image acquisition equipment and computational units allows for the automation of this process. Moreover, a lot of possible technical problems occur in everyday histological material, which increases the complexity of the problem. Thus, a full context-based analysis of histological specimens is also needed in the quantification of immunohistochemically stained specimens. One of the most important reactions is the Ki-67 proliferation marker in meningiomas, the most frequent intracranial tumour. The aim of our study is to propose a context-based analysis of Ki-67 stained specimens of meningiomas for automatic selection of hot-spots. The proposed solution is based on textural analysis, mathematical morphology, feature ranking and classification, as well as on the proposed hot-spot gradual extinction algorithm to allow for the proper detection of a set of hot-spot fields. The designed whole slide image processing scheme eliminates such artifacts as hemorrhages, folds or stained vessels from the region of interest. To validate automatic results, a set of 104 meningioma specimens were selected and twenty hot-spots inside them were identified independently by two experts. The Spearman rho correlation coefficient was used to compare the results which were also analyzed with the help of a Bland-Altman plot. The results show that most of the cases (84) were automatically examined properly with two fields of view with a technical problem at the very most. Next, 13 had three such fields, and only seven specimens did not meet the requirement for the automatic examination. Generally, the Automatic System identifies hot-spot areas, especially their maximum points, better. Analysis of the results confirms the very high concordance between an automatic Ki-67 examination and the expert's results, with a Spearman rho higher than 0.95. The proposed hot-spot selection algorithm with an extended context-based analysis of whole slide images and hot-spot gradual extinction algorithm provides an efficient tool for simulation of a manual examination. The presented results have confirmed that the automatic examination of Ki-67 in meningiomas could be introduced in the near future.
Department of Defense Chemical and Biological Defense Program. Volume I: Annual Report to Congress
2002-04-01
The M21 RSCAAL is an automatic scanning, passive infrared sensor that detects nerve ( GA , GB, and GD) and blister (H and L) agent vapor clouds based on...Point Detection GA - tabun, a nerve agent System GAO - General Accounting Office IPE - Individual Protective Equipment GAS - Group A Streptococcus...IPR - In-Process Review GB - sarin , a nerve agent IPT - Integrated Product Team GC - gas chromatography IR&D - Independent Research & Development GD
Automatic 3d Building Model Generations with Airborne LiDAR Data
NASA Astrophysics Data System (ADS)
Yastikli, N.; Cetin, Z.
2017-11-01
LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D building models can be generated successfully using raw LiDAR point cloud data.
NASA Astrophysics Data System (ADS)
Schlupp, A.; Sira, C.; Schmitt, K.; Schaming, M.
2013-12-01
In charge of intensity estimations in France, BCSF has collected and manually analyzed more than 47000 online individual macroseismic questionnaires since 2000 up to intensity VI. These macroseismic data allow us to estimate one SQI value (Single Questionnaire Intensity) for each form following the EMS98 scale. The reliability of the automatic intensity estimation is important as they are today used for automatic shakemaps communications and crisis management. Today, the automatic intensity estimation at BCSF is based on the direct use of thumbnails selected on a menu by the witnesses. Each thumbnail corresponds to an EMS-98 intensity value, allowing us to quickly issue an intensity map of the communal intensity by averaging the SQIs at each city. Afterwards an expert, to determine a definitive SQI, manually analyzes each form. This work is time consuming and not anymore suitable considering the increasing number of testimonies at BCSF. Nevertheless, it can take into account incoherent answers. We tested several automatic methods (USGS algorithm, Correlation coefficient, Thumbnails) (Sira et al. 2013, IASPEI) and compared them with 'expert' SQIs. These methods gave us medium score (between 50 to 60% of well SQI determined and 35 to 40% with plus one or minus one intensity degree). The best fit was observed with the thumbnails. Here, we present new approaches based on 3 statistical ranking methods as 1) Multinomial logistic regression model, 2) Discriminant analysis DISQUAL and 3) Support vector machines (SVMs). The two first methods are standard methods, while the third one is more recent. Theses methods could be applied because the BCSF has already in his database more then 47000 forms and because their questions and answers are well adapted for a statistical analysis. The ranking models could then be used as automatic method constrained on expert analysis. The performance of the automatic methods and the reliability of the estimated SQI can be evaluated thanks to the fact that each definitive BCSF SQIs is determined by an expert analysis. We compare the SQIs obtained by these methods from our database and discuss the coherency and variations between automatic and manual processes. These methods lead to high scores with up to 85% of the forms well classified and most of the remaining forms classified with only a shift of one intensity degree. This allows us to use the ranking methods as the best automatic methods to fast SQIs estimation and to produce fast shakemaps. The next step, to improve the use of these methods, will be to identify explanations for the forms not classified at the correct value and a way to select the few remaining forms that should be analyzed by the expert. Note that beyond intensity VI, on-line questionnaires are insufficient and a field survey is indispensable to estimate intensity. For such survey, in France, BCSF leads a macroseismic intervention group (GIM).
ERIC Educational Resources Information Center
Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.
2018-01-01
Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…
NASA Astrophysics Data System (ADS)
Chen, Kewei; Ge, Xiaolin; Yao, Li; Bandy, Dan; Alexander, Gene E.; Prouty, Anita; Burns, Christine; Zhao, Xiaojie; Wen, Xiaotong; Korn, Ronald; Lawson, Michael; Reiman, Eric M.
2006-03-01
Having approved fluorodeoxyglucose positron emission tomography (FDG PET) for the diagnosis of Alzheimer's disease (AD) in some patients, the Centers for Medicare and Medicaid Services suggested the need to develop and test analysis techniques to optimize diagnostic accuracy. We developed an automated computer package comparing an individual's FDG PET image to those of a group of normal volunteers. The normal control group includes FDG-PET images from 82 cognitively normal subjects, 61.89+/-5.67 years of age, who were characterized demographically, clinically, neuropsychologically, and by their apolipoprotein E genotype (known to be associated with a differential risk for AD). In addition, AD-affected brain regions functionally defined as based on a previous study (Alexander, et al, Am J Psychiatr, 2002) were also incorporated. Our computer package permits the user to optionally select control subjects, matching the individual patient for gender, age, and educational level. It is fully streamlined to require minimal user intervention. With one mouse click, the program runs automatically, normalizing the individual patient image, setting up a design matrix for comparing the single subject to a group of normal controls, performing the statistics, calculating the glucose reduction overlap index of the patient with the AD-affected brain regions, and displaying the findings in reference to the AD regions. In conclusion, the package automatically contrasts a single patient to a normal subject database using sound statistical procedures. With further validation, this computer package could be a valuable tool to assist physicians in decision making and communicating findings with patients and patient families.
Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina
2012-01-01
Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803
Attention-spreading based on hierarchical spatial representations for connected objects.
Kasai, Tetsuko
2010-01-01
Attention selects objects or groups as the most fundamental unit, and this may be achieved through a process in which attention automatically spreads throughout their entire region. Previously, we found that a lateralized potential relative to an attended hemifield at occipito-temporal electrode sites reflects attention-spreading in response to connected bilateral stimuli [Kasai, T., & Kondo, M. Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93-98, 2007]. The present study examined the nature of object representations by manipulating the extent of grouping through connectedness, while controlling the symmetrical structure of bilateral stimuli. The electrophysiological results of two experiments consistently indicated that attention was guided twice in association with perceptual grouping in the early phase (N1, 150-200 msec poststimulus) and with the unity of an object in the later phase (N2pc, 310/330-390 msec). This suggests that there are two processes in object-based spatial selection, and these are discussed with regard to their cognitive mechanisms and object representations.
Analyzing Activity Behavior and Movement in a Naturalistic Environment using Smart Home Techniques
Cook, Diane J.; Schmitter-Edgecombe, Maureen; Dawadi, Prafulla
2015-01-01
One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study we use smart home and wearable sensors to collect data while (n=84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an AUC value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant. PMID:26259225
Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques.
Cook, Diane J; Schmitter-Edgecombe, Maureen; Dawadi, Prafulla
2015-11-01
One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while ( n = 84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an area under the ROC curve value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant.
Investigation of possible causes for human-performance degradation during microgravity flight
NASA Technical Reports Server (NTRS)
Schroeder, James E.; Tuttle, Megan L.
1992-01-01
The results of the first year of a three year study of the effects of microgravity on human performance are given. Test results show support for the hypothesis that the effects of microgravity can be studied indirectly on Earth by measuring performance in an altered gravitational field. The hypothesis was that an altered gravitational field could disrupt performance on previously automated behaviors if gravity was a critical part of the stimulus complex controlling those behaviors. In addition, it was proposed that performance on secondary cognitive tasks would also degrade, especially if the subject was provided feedback about degradation on the previously automated task. In the initial experimental test of these hypotheses, there was little statistical support. However, when subjects were categorized as high or low in automated behavior, results for the former group supported the hypotheses. The predicted interaction between body orientation and level of workload in their joint effect on performance in the secondary cognitive task was significant for the group high in automatized behavior and receiving feedback, but no such interventions were found for the group high in automatized behavior but not receiving feedback, or the group low in automatized behavior.
The research of automatic speed control algorithm based on Green CBTC
NASA Astrophysics Data System (ADS)
Lin, Ying; Xiong, Hui; Wang, Xiaoliang; Wu, Youyou; Zhang, Chuanqi
2017-06-01
Automatic speed control algorithm is one of the core technologies of train operation control system. It’s a typical multi-objective optimization control algorithm, which achieve the train speed control for timing, comfort, energy-saving and precise parking. At present, the train speed automatic control technology is widely used in metro and inter-city railways. It has been found that the automatic speed control technology can effectively reduce the driver’s intensity, and improve the operation quality. However, the current used algorithm is poor at energy-saving, even not as good as manual driving. In order to solve the problem of energy-saving, this paper proposes an automatic speed control algorithm based on Green CBTC system. Based on the Green CBTC system, the algorithm can adjust the operation status of the train to improve the efficient using rate of regenerative braking feedback energy while ensuring the timing, comfort and precise parking targets. Due to the reason, the energy-using of Green CBTC system is lower than traditional CBTC system. The simulation results show that the algorithm based on Green CBTC system can effectively reduce the energy-using due to the improvement of the using rate of regenerative braking feedback energy.
Automatic liver contouring for radiotherapy treatment planning
NASA Astrophysics Data System (ADS)
Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei
2015-09-01
To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems. The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours. The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group are on an average 2.15-2.57%, 2.96-3.23%, and 91.01-97.21% for the CT images with normal appearing livers, 2.28-3.62%, 3.15-4.33%, and 86.14-93.53% for the CT images with hepatocellular carcinoma or liver metastases, and 2.37-3.96%, 3.25-4.57%, and 82.23-89.44% for the 4D-CT images also with hepatocellular carcinoma or liver metastases, respectively. The proposed three-step method can achieve efficient automatic liver contouring for planning CT and 4D-CT images with follow-up treatment planning and should find widespread applications in future treatment planning systems.
Resource depletion promotes automatic processing: implications for distribution of practice.
Scheel, Matthew H
2010-12-01
Recent models of cognition include two processing systems: an automatic system that relies on associative learning, intuition, and heuristics, and a controlled system that relies on deliberate consideration. Automatic processing requires fewer resources and is more likely when resources are depleted. This study showed that prolonged practice on a resource-depleting mental arithmetic task promoted automatic processing on a subsequent problem-solving task, as evidenced by faster responding and more errors. Distribution of practice effects (0, 60, 120, or 180 sec. between problems) on rigidity also disappeared when groups had equal time on resource-depleting tasks. These results suggest that distribution of practice effects is reducible to resource availability. The discussion includes implications for interpreting discrepancies in the traditional distribution of practice effect.
ERIC Educational Resources Information Center
Hevel, David; Tannehill, Dana, Ed.
This module is the eighth of nine modules in the competency-based Missouri Auto Mechanics Curriculum Guide. Six units cover: introduction to automatic transmission/transaxle; hydraulic control systems; transmission/transaxle diagnosis; automatic transmission/transaxle maintenance and adjustment; in-vehicle transmission repair; and off-car…
Automatic Item Generation of Probability Word Problems
ERIC Educational Resources Information Center
Holling, Heinz; Bertling, Jonas P.; Zeuch, Nina
2009-01-01
Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…
Reading between the Lines: Accessing Information via "Youtube's" Automatic Captioning
ERIC Educational Resources Information Center
Smith, Chad; Allman, Tamby; Crocker, Samantha
2017-01-01
This study and discussion center upon the use of "YouTube's" automatic captioning feature with college-age adult readers. The study required 75 participants with college experience to view brief middle school science videos with automatic captioning on "YouTube" and answer comprehension questions based on material presented…
Enhancing Automaticity through Task-Based Language Learning
ERIC Educational Resources Information Center
De Ridder, Isabelle; Vangehuchten, Lieve; Gomez, Marta Sesena
2007-01-01
In general terms automaticity could be defined as the subconscious condition wherein "we perform a complex series of tasks very quickly and efficiently, without having to think about the various components and subcomponents of action involved" (DeKeyser 2001: 125). For language learning, Segalowitz (2003) characterised automaticity as a…
Autonomous self-organizing resource manager for multiple networked platforms
NASA Astrophysics Data System (ADS)
Smith, James F., III
2002-08-01
A fuzzy logic based expert system for resource management has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar autonomous naval platforms defending their group against attackers. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. This paper provides an overview of the resource manager including the four fuzzy decision trees that make up the resource manager; the fuzzy EA model; genetic algorithm based optimization; co-evolutionary data mining through gaming; and mathematical, computational and hardware based validation. Methods of automatically designing new multi-platform EA techniques are considered. The expert system runs on each defending platform rendering it an autonomous system requiring no human intervention. There is no commanding platform. Instead the platforms work cooperatively as a function of battlespace geometry; sensor data such as range, bearing, ID, uncertainty measures for sensor output; intelligence reports; etc. Computational experiments will show the defending networked platform's ability to self- organize. The platforms' ability to self-organize is illustrated through the output of the scenario generator, a software package that automates the underlying data mining problem and creates a computer movie of the platforms' interaction for evaluation.
Automatically identifying health outcome information in MEDLINE records.
Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George
2006-01-01
Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.
ERIC Educational Resources Information Center
Shih, Ching-Hsiang; Cheng, Hsiao-Fen; Li, Chia-Chun; Shih, Ching-Tien; Chiang, Ming-Shan
2010-01-01
This study evaluated whether four persons (two groups) with developmental disabilities would be able to improve their collaborative pointing performance through a Multiple Cursor Automatic Pointing Assistive Program (MCAPAP) with a newly developed mouse driver (i.e., a new mouse driver replaces standard mouse driver, and is able to…
Automatic Evaluation of Practices in Moodle for Self Learning in Engineering
ERIC Educational Resources Information Center
Sánchez, Carles; Ramos, Oriol; Márquez, Patricia; Marti, Enric; Rocarias, Jaume; Gil, Debora
2015-01-01
The first years in engineering degree courses are usually made of large groups with a low teacher-student ratio. Overcrowding in classrooms hinders continuous assessment much needed to promote independent learning. Therefore, there is a need to apply some kind of automatic evaluation to facilitate the correction of exercises outside the classroom.…
TERMTrial--terminology-based documentation systems for cooperative clinical trials.
Merzweiler, A; Weber, R; Garde, S; Haux, R; Knaup-Gregori, P
2005-04-01
Within cooperative groups of multi-center clinical trials a standardized documentation is a prerequisite for communication and sharing of data. Standardizing documentation systems means standardizing the underlying terminology. The management and consistent application of terminology systems is a difficult and fault-prone task, which should be supported by appropriate software tools. Today, documentation systems for clinical trials are often implemented as so-called Remote-Data-Entry-Systems (RDE-systems). Although there are many commercial systems, which support the development of RDE-systems there is none offering a comprehensive terminological support. Therefore, we developed the software system TERMTrial which consists of a component for the definition and management of terminology systems for cooperative groups of clinical trials and two components for the terminology-based automatic generation of trial databases and terminology-based interactive design of electronic case report forms (eCRFs). TERMTrial combines the advantages of remote data entry with a comprehensive terminological control.
A tool for developing an automatic insect identification system based on wing outlines
Yang, He-Ping; Ma, Chun-Sen; Wen, Hui; Zhan, Qing-Bin; Wang, Xin-Li
2015-01-01
For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main functions: (1) outline digitization and Elliptic Fourier transformation and (2) classifier model training by pattern recognition of support vector machines and model validation. To demonstrate the utility of this program, a sample of 120 owlflies (Neuroptera: Ascalaphidae) was split into training and validation sets. After training, the sample was sorted into seven species using this tool. In five repeated experiments, the mean accuracy for identification of each species ranged from 90% to 98%. The accuracy increased to 99% when the samples were first divided into two groups based on features of their compound eyes. DAIIS can therefore be a useful tool for developing a system of automated insect identification. PMID:26251292
Group-based differences in anti-aging bias among medical students.
Ruiz, Jorge G; Andrade, Allen D; Anam, Ramanakumar; Taldone, Sabrina; Karanam, Chandana; Hogue, Christie; Mintzer, Michael J
2015-01-01
Medical students (MS) may develop ageist attitudes early in their training that may predict their future avoidance of caring for the elderly. This study sought to determine MS' patterns of explicit and implicit anti-aging bias, intent to practice with older people and using the quad model, the role of gender, race, and motivation-based differences. One hundred and three MS completed an online survey that included explicit and implicit measures. Explicit measures revealed a moderately positive perception of older people. Female medical students and those high in internal motivation showed lower anti-aging bias, and both were more likely to intend to practice with older people. Although the implicit measure revealed more negativity toward the elderly than the explicit measures, there were no group differences. However, using the quad model the authors identified gender, race, and motivation-based differences in controlled and automatic processes involved in anti-aging bias.
Automated Detection of Actinic Keratoses in Clinical Photographs
Hames, Samuel C.; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H. Peter; Prow, Tarl W.
2015-01-01
Background Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. Objective The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Methods Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist’s assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. Results The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist’s intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. Conclusions The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is a feasible avenue of investigation for overcoming variability in clinical assessment. Future studies should focus on more sophisticated features to improve sensitivity for actinic keratoses without erythema and limit false positives associated with the anatomical structures on the face. PMID:25615930
van Minnen, Agnes; Becker, Eni S.; van Oostrom, Iris; Speckens, Anne; Rinck, Mike; Vrijsen, Janna N.
2018-01-01
Depression risk genes in combination with childhood events have been associated with biased processing as an intermediate phenotype for depression. The aim of the present conceptual replication study was to investigate the role of biased automatic approach-avoidance tendencies as a candidate intermediate phenotype for depression, in the context of genes (5-HTTLPR polymorphism) and childhood trauma. A naturalistic remitted depressed patients sample (N = 209) performed an Approach-Avoidance Task (AAT) with facial expressions (angry, sad, happy and neutral). Childhood trauma was assessed with a questionnaire. Genotype groups were created based on allele frequency: LaLa versus S/Lg-carriers. The latter is associated with depression risk. We found that remitted S/Lg-carriers who experienced childhood trauma automatically avoided sad facial expressions relatively more than LaLa homozygotes with childhood trauma. Remitted LaLa-carriers who had not experienced childhood trauma, avoided sad faces relatively more than LaLa homozygotes with childhood trauma. We did not find a main effect of childhood trauma, nor differential avoidance of any of the other facial expressions. Although tentative, the results suggest that automatic approach-avoidance tendencies for disorder-congruent materials may be a fitting intermediate phenotype for depression. The specific pattern of tendencies, and the relation to depression, may depend on the genetic risk profile and childhood trauma, but replication is needed before firm conclusions can be drawn. PMID:29547643
Stoeger, Angela S.; Zeppelzauer, Matthias; Baotic, Anton
2015-01-01
Animal vocal signals are increasingly used to monitor wildlife populations and to obtain estimates of species occurrence and abundance. In the future, acoustic monitoring should function not only to detect animals, but also to extract detailed information about populations by discriminating sexes, age groups, social or kin groups, and potentially individuals. Here we show that it is possible to estimate age groups of African elephants (Loxodonta africana) based on acoustic parameters extracted from rumbles recorded under field conditions in a National Park in South Africa. Statistical models reached up to 70 % correct classification to four age groups (infants, calves, juveniles, adults) and 95 % correct classification when categorising into two groups (infants/calves lumped into one group versus adults). The models revealed that parameters representing absolute frequency values have the most discriminative power. Comparable classification results were obtained by fully automated classification of rumbles by high-dimensional features that represent the entire spectral envelope, such as MFCC (75 % correct classification) and GFCC (74 % correct classification). The reported results and methods provide the scientific foundation for a future system that could potentially automatically estimate the demography of an acoustically monitored elephant group or population. PMID:25821348
Finite element fatigue analysis of rectangular clutch spring of automatic slack adjuster
NASA Astrophysics Data System (ADS)
Xu, Chen-jie; Luo, Zai; Hu, Xiao-feng; Jiang, Wen-song
2015-02-01
The failure of rectangular clutch spring of automatic slack adjuster directly affects the work of automatic slack adjuster. We establish the structural mechanics model of automatic slack adjuster rectangular clutch spring based on its working principle and mechanical structure. In addition, we upload such structural mechanics model to ANSYS Workbench FEA system to predict the fatigue life of rectangular clutch spring. FEA results show that the fatigue life of rectangular clutch spring is 2.0403×105 cycle under the effect of braking loads. In the meantime, fatigue tests of 20 automatic slack adjusters are carried out on the fatigue test bench to verify the conclusion of the structural mechanics model. The experimental results show that the mean fatigue life of rectangular clutch spring is 1.9101×105, which meets the results based on the finite element analysis using ANSYS Workbench FEA system.
Automatic Match between Delimitation Line and Real Terrain Based on Least-Cost Path Analysis
NASA Astrophysics Data System (ADS)
Feng, C. Q.; Jiang, N.; Zhang, X. N.; Ma, J.
2013-11-01
Nowadays, during the international negotiation on separating dispute areas, manual adjusting is lonely applied to the match between delimitation line and real terrain, which not only consumes much time and great labor force, but also cannot ensure high precision. Concerning that, the paper mainly explores automatic match between them and study its general solution based on Least -Cost Path Analysis. First, under the guidelines of delimitation laws, the cost layer is acquired through special disposals of delimitation line and terrain features line. Second, a new delimitation line gets constructed with the help of Least-Cost Path Analysis. Third, the whole automatic match model is built via Module Builder in order to share and reuse it. Finally, the result of automatic match is analyzed from many different aspects, including delimitation laws, two-sided benefits and so on. Consequently, a conclusion is made that the method of automatic match is feasible and effective.
Automatic mathematical modeling for space application
NASA Technical Reports Server (NTRS)
Wang, Caroline K.
1987-01-01
A methodology for automatic mathematical modeling is described. The major objective is to create a very friendly environment for engineers to design, maintain and verify their model and also automatically convert the mathematical model into FORTRAN code for conventional computation. A demonstration program was designed for modeling the Space Shuttle Main Engine simulation mathematical model called Propulsion System Automatic Modeling (PSAM). PSAM provides a very friendly and well organized environment for engineers to build a knowledge base for base equations and general information. PSAM contains an initial set of component process elements for the Space Shuttle Main Engine simulation and a questionnaire that allows the engineer to answer a set of questions to specify a particular model. PSAM is then able to automatically generate the model and the FORTRAN code. A future goal is to download the FORTRAN code to the VAX/VMS system for conventional computation.
Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops
Jansen, Roel; Hofstee, Jan Willem; Bouwmeester, Harro; van Henten, Eldert
2010-01-01
Gas chromatograph–mass spectrometers (GC-MS) have been used and shown utility for volatile-based inspection of greenhouse crops. However, a widely recognized difficulty associated with GC-MS application is the large and complex data generated by this instrument. As a consequence, experienced analysts are often required to process this data in order to determine the concentrations of the volatile organic compounds (VOCs) of interest. Manual processing is time-consuming, labour intensive and may be subject to errors due to fatigue. The objective of this study was to assess whether or not GC-MS data can also be automatically processed in order to determine the concentrations of crop health associated VOCs in a greenhouse. An experimental dataset that consisted of twelve data files was processed both manually and automatically to address this question. Manual processing was based on simple peak integration while the automatic processing relied on the algorithms implemented in the MetAlign™ software package. The results of automatic processing of the experimental dataset resulted in concentrations similar to that after manual processing. These results demonstrate that GC-MS data can be automatically processed in order to accurately determine the concentrations of crop health associated VOCs in a greenhouse. When processing GC-MS data automatically, noise reduction, alignment, baseline correction and normalisation are required. PMID:22163594
Automatic image enhancement based on multi-scale image decomposition
NASA Astrophysics Data System (ADS)
Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong
2014-01-01
In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.
Automatic cortical thickness analysis on rodent brain
NASA Astrophysics Data System (ADS)
Lee, Joohwi; Ehlers, Cindy; Crews, Fulton; Niethammer, Marc; Budin, Francois; Paniagua, Beatriz; Sulik, Kathy; Johns, Josephine; Styner, Martin; Oguz, Ipek
2011-03-01
Localized difference in the cortex is one of the most useful morphometric traits in human and animal brain studies. There are many tools and methods already developed to automatically measure and analyze cortical thickness for the human brain. However, these tools cannot be directly applied to rodent brains due to the different scales; even adult rodent brains are 50 to 100 times smaller than humans. This paper describes an algorithm for automatically measuring the cortical thickness of mouse and rat brains. The algorithm consists of three steps: segmentation, thickness measurement, and statistical analysis among experimental groups. The segmentation step provides the neocortex separation from other brain structures and thus is a preprocessing step for the thickness measurement. In the thickness measurement step, the thickness is computed by solving a Laplacian PDE and a transport equation. The Laplacian PDE first creates streamlines as an analogy of cortical columns; the transport equation computes the length of the streamlines. The result is stored as a thickness map over the neocortex surface. For the statistical analysis, it is important to sample thickness at corresponding points. This is achieved by the particle correspondence algorithm which minimizes entropy between dynamically moving sample points called particles. Since the computational cost of the correspondence algorithm may limit the number of corresponding points, we use thin-plate spline based interpolation to increase the number of corresponding sample points. As a driving application, we measured the thickness difference to assess the effects of adolescent intermittent ethanol exposure that persist into adulthood and performed t-test between the control and exposed rat groups. We found significantly differing regions in both hemispheres.
Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra
2014-01-01
Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. Objective The aims were to describe how to: (i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and (ii) automatically identify the features that best distinguish the groups. Methods The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described – simple or complex; presentation order – which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo18 were used,which included 200 healthy Brazilians of both genders. Results and Conclusion A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods. PMID:29213908
Zeng, Xueqiang; Luo, Gang
2017-12-01
Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing.
Li, Chunhua; Zhao, Pengpeng; Sheng, Victor S; Xian, Xuefeng; Wu, Jian; Cui, Zhiming
2017-01-01
Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost.
Automatic system for detecting pornographic images
NASA Astrophysics Data System (ADS)
Ho, Kevin I. C.; Chen, Tung-Shou; Ho, Jun-Der
2002-09-01
Due to the dramatic growth of network and multimedia technology, people can more easily get variant information by using Internet. Unfortunately, it also makes the diffusion of illegal and harmful content much easier. So, it becomes an important topic for the Internet society to protect and safeguard Internet users from these content that may be encountered while surfing on the Net, especially children. Among these content, porno graphs cause more serious harm. Therefore, in this study, we propose an automatic system to detect still colour porno graphs. Starting from this result, we plan to develop an automatic system to search porno graphs or to filter porno graphs. Almost all the porno graphs possess one common characteristic that is the ratio of the size of skin region and non-skin region is high. Based on this characteristic, our system first converts the colour space from RGB colour space to HSV colour space so as to segment all the possible skin-colour regions from scene background. We also apply the texture analysis on the selected skin-colour regions to separate the skin regions from non-skin regions. Then, we try to group the adjacent pixels located in skin regions. If the ratio is over a given threshold, we can tell if the given image is a possible porno graph. Based on our experiment, less than 10% of non-porno graphs are classified as pornography, and over 80% of the most harmful porno graphs are classified correctly.
Resection planning for robotic acoustic neuroma surgery
NASA Astrophysics Data System (ADS)
McBrayer, Kepra L.; Wanna, George B.; Dawant, Benoit M.; Balachandran, Ramya; Labadie, Robert F.; Noble, Jack H.
2016-03-01
Acoustic neuroma surgery is a procedure in which a benign mass is removed from the Internal Auditory Canal (IAC). Currently this surgical procedure requires manual drilling of the temporal bone followed by exposure and removal of the acoustic neuroma. This procedure is physically and mentally taxing to the surgeon. Our group is working to develop an Acoustic Neuroma Surgery Robot (ANSR) to perform the initial drilling procedure. Planning the ANSR's drilling region using pre-operative CT requires expertise and around 35 minutes' time. We propose an approach for automatically producing a resection plan for the ANSR that would avoid damage to sensitive ear structures and require minimal editing by the surgeon. We first compute an atlas-based segmentation of the mastoid section of the temporal bone, refine it based on the position of anatomical landmarks, and apply a safety margin to the result to produce the automatic resection plan. In experiments with CTs from 9 subjects, our automated process resulted in a resection plan that was verified to be safe in every case. Approximately 2 minutes were required in each case for the surgeon to verify and edit the plan to permit functional access to the IAC. We measured a mean Dice coefficient of 0.99 and surface error of 0.08 mm between the final and automatically proposed plans. These preliminary results indicate that our approach is a viable method for resection planning for the ANSR and drastically reduces the surgeon's planning effort.
Tasking and sharing sensing assets using controlled natural language
NASA Astrophysics Data System (ADS)
Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David
2012-06-01
We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.
A deep-learning based automatic pulmonary nodule detection system
NASA Astrophysics Data System (ADS)
Zhao, Yiyuan; Zhao, Liang; Yan, Zhennan; Wolf, Matthias; Zhan, Yiqiang
2018-02-01
Lung cancer is the deadliest cancer worldwide. Early detection of lung cancer is a promising way to lower the risk of dying. Accurate pulmonary nodule detection in computed tomography (CT) images is crucial for early diagnosis of lung cancer. The development of computer-aided detection (CAD) system of pulmonary nodules contributes to making the CT analysis more accurate and with more efficiency. Recent studies from other groups have been focusing on lung cancer diagnosis CAD system by detecting medium to large nodules. However, to fully investigate the relevance between nodule features and cancer diagnosis, a CAD that is capable of detecting nodules with all sizes is needed. In this paper, we present a deep-learning based automatic all size pulmonary nodule detection system by cascading two artificial neural networks. We firstly use a U-net like 3D network to generate nodule candidates from CT images. Then, we use another 3D neural network to refine the locations of the nodule candidates generated from the previous subsystem. With the second sub-system, we bring the nodule candidates closer to the center of the ground truth nodule locations. We evaluate our system on a public CT dataset provided by the Lung Nodule Analysis (LUNA) 2016 grand challenge. The performance on the testing dataset shows that our system achieves 90% sensitivity with an average of 4 false positives per scan. This indicates that our system can be an aid for automatic nodule detection, which is beneficial for lung cancer diagnosis.
Automated Vocal Analysis of Children with Hearing Loss and Their Typical and Atypical Peers
VanDam, Mark; Oller, D. Kimbrough; Ambrose, Sophie E.; Gray, Sharmistha; Richards, Jeffrey A.; Xu, Dongxin; Gilkerson, Jill; Silbert, Noah H.; Moeller, Mary Pat
2014-01-01
Objectives This study investigated automatic assessment of vocal development in children with hearing loss as compared with children who are typically developing, have language delays, and autism spectrum disorder. Statistical models are examined for performance in a classification model and to predict age within the four groups of children. Design The vocal analysis system analyzed over 1900 whole-day, naturalistic acoustic recordings from 273 toddlers and preschoolers comprising children who were typically developing, hard of hearing, language delayed, or autistic. Results Samples from children who were hard-of-hearing patterned more similarly to those of typically-developing children than to the language-delayed or autistic samples. The statistical models were able to classify children from the four groups examined and estimate developmental age based on automated vocal analysis. Conclusions This work shows a broad similarity between children with hearing loss and typically developing children, although children with hearing loss show some delay in their production of speech. Automatic acoustic analysis can now be used to quantitatively compare vocal development in children with and without speech-related disorders. The work may serve to better distinguish among various developmental disorders and ultimately contribute to improved intervention. PMID:25587667
A hypothetical neurological association between dehumanization and human rights abuses.
Murrow, Gail B; Murrow, Richard
2015-07-01
Dehumanization is anecdotally and historically associated with reduced empathy for the pain of dehumanized individuals and groups and with psychological and legal denial of their human rights and extreme violence against them. We hypothesize that 'empathy' for the pain and suffering of dehumanized social groups is automatically reduced because, as the research we review suggests, an individual's neural mechanisms of pain empathy best respond to (or produce empathy for) the pain of people whom the individual automatically or implicitly associates with her or his own species. This theory has implications for the philosophical conception of 'human' and of 'legal personhood' in human rights jurisprudence. It further has implications for First Amendment free speech jurisprudence, including the doctrine of 'corporate personhood' and consideration of the potential harm caused by dehumanizing hate speech. We suggest that the new, social neuroscience of empathy provides evidence that both the vagaries of the legal definition or legal fiction of 'personhood' and hate speech that explicitly and implicitly dehumanizes may (in their respective capacities to artificially humanize or dehumanize) manipulate the neural mechanisms of pain empathy in ways that could pose more of a true threat to human rights and rights-based democracy than previously appreciated.
Knowing who's boss: implicit perceptions of status from the nonverbal expression of pride.
Shariff, Azim F; Tracy, Jessica L
2009-10-01
Evolutionary theory suggests that the universal recognition of nonverbal expressions of emotions functions to enhance fitness. Specifically, emotion expressions may send survival-relevant messages to other social group members, who have the capacity to automatically interpret these signals. In the present research, we used 3 different implicit association methodologies to test whether the nonverbal expression of pride sends a functional, automatically perceived signal about a social group member's increased social status. Results suggest that the pride expression strongly signals high status, and this association cannot be accounted for by positive valence or artifacts of the expression such as expanded size due to outstretched arms. These findings suggest that the pride expression may function to uniquely communicate the high status of those who show it. Discussion focuses on the implications of these findings for social functions of emotion expressions and the automatic communication of status.
Holst, H; Aström, K; Järund, A; Palmer, J; Heyden, A; Kahl, F; Tägil, K; Evander, E; Sparr, G; Edenbrandt, L
2000-04-01
The purpose of this study was to develop a completely automated method for the interpretation of ventilation-perfusion (V-P) lung scintigrams used in the diagnosis of pulmonary embolism. An artificial neural network was trained for the diagnosis of pulmonary embolism using 18 automatically obtained features from each set of V-P scintigrams. The techniques used to process the images included their alignment to templates, the construction of quotient images based on the ventilation and perfusion images, and the calculation of measures describing V-P mismatches in the quotient images. The templates represented lungs of normal size and shape without any pathological changes. Images that could not be properly aligned to the templates were detected and excluded automatically. After exclusion of those V-P scintigrams not properly aligned to the templates, 478 V-P scintigrams remained in a training group of consecutive patients with suspected pulmonary embolism, and a further 87 V-P scintigrams formed a separate test group comprising patients who had undergone pulmonary angiography. The performance of the neural network, measured as the area under the receiver operating characteristic curve, was 0.87 (95% confidence limits 0.82-0.92) in the training group and 0.79 (0.69-0.88) in the test group. It is concluded that a completely automated method can be used for the interpretation of V-P scintigrams. The performance of this method is similar to others previously presented, whereby features were extracted manually.
Automatic classification of sleep stages based on the time-frequency image of EEG signals.
Bajaj, Varun; Pachori, Ram Bilas
2013-12-01
In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
A cloud-based system for automatic glaucoma screening.
Fengshou Yin; Damon Wing Kee Wong; Ying Quan; Ai Ping Yow; Ngan Meng Tan; Gopalakrishnan, Kavitha; Beng Hai Lee; Yanwu Xu; Zhuo Zhang; Jun Cheng; Jiang Liu
2015-08-01
In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases including glaucoma. However, these systems are usually standalone software with basic functions only, limiting their usage in a large scale. In this paper, we introduce an online cloud-based system for automatic glaucoma screening through the use of medical image-based pattern classification technologies. It is designed in a hybrid cloud pattern to offer both accessibility and enhanced security. Raw data including patient's medical condition and fundus image, and resultant medical reports are collected and distributed through the public cloud tier. In the private cloud tier, automatic analysis and assessment of colour retinal fundus images are performed. The ubiquitous anywhere access nature of the system through the cloud platform facilitates a more efficient and cost-effective means of glaucoma screening, allowing the disease to be detected earlier and enabling early intervention for more efficient intervention and disease management.
Motor Skills, Automaticity and Developmental Dyslexia: A Review of the Research Literature
ERIC Educational Resources Information Center
Savage, Robert
2004-01-01
This paper reviews a body of prominent theories of automaticity in developmental dyslexia. The first part of the review considers the relationship between dyslexia and rapid automatic naming and fluency. Additional theoretical and empirical advances are suggested to this already strong research base. In particular, there is a need is for…
Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria
2017-10-01
Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.
Sentence Similarity Analysis with Applications in Automatic Short Answer Grading
ERIC Educational Resources Information Center
Mohler, Michael A. G.
2012-01-01
In this dissertation, I explore unsupervised techniques for the task of automatic short answer grading. I compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating…
Wang, Fu-biao; Ma, Yu-cai; Sun, Le-ping; Hong, Qing-biao; Gao, Yang; Zhang, Chang-lin; Du, Guang-lin; Lu, Da-qin; Sun, Zhi-yong; Wang, Wei; Dai, Jian-rong; Liang, You-sheng
2016-02-01
To develop a machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding and to evaluate its effectiveness of field application, so as to provide a novel Oncomelania hupensis snail control technique in the large-scale marshlands. The machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding, which was suitable for use in complex marshland areas, was developed according to the mechanization and automation principles, and was used for O. hupensis snail control in the marshland. The effect of the machine on environmental cleaning and plough was evaluated, and the distribution of living snails was observed at various soil layers following plough. The snail control effects of plough alone and plough followed by mollusciciding were compared. The machine could simultaneously complete the procedures of getting vegetation down and cut vegetation into pieces, plough and snail control by spraying niclosamide. After plough, the constituent ratios of living snails were 36.31%, 25.60%, 22.62% and 15.48% in the soil layers at depths of 0-5, 6-10, 11-15 cm and 16-20 cm respectively, and 61.91% living snails were found in the 0-10 cm soil layers. Seven and fifteen days after the experiment, the mortality rates of snails were 9.38% and 8.29% in the plough alone group, and 63.04% and 80.70% in the plough + mollusciciding group respectively (χ²₇ d = 42.74, χ²₁₅ d = 155.56, both P values < 0.01). Thirty days after the experiment, the densities of snails were 3.02 snails/0.1 m² and 0.53 snails/ 0.1 m² in the soil surface of the plough alone group and the plough + mollusciciding group, which decreased by 64.92% and 93.60%, respectively, and the decrease rate of snail density was approximately 30% higher in the plough + mollusciciding group than that in the plough alone group. The machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding achieves the integration of mechanical environmental cleaning and automatic niclosamide spraying in the complex marshland areas, which provides a novel technique of field snail control in the large-scale setting in China.
A prototype system to support evidence-based practice.
Demner-Fushman, Dina; Seckman, Charlotte; Fisher, Cheryl; Hauser, Susan E; Clayton, Jennifer; Thoma, George R
2008-11-06
Translating evidence into clinical practice is a complex process that depends on the availability of evidence, the environment into which the research evidence is translated, and the system that facilitates the translation. This paper presents InfoBot, a system designed for automatic delivery of patient-specific information from evidence-based resources. A prototype system has been implemented to support development of individualized patient care plans. The prototype explores possibilities to automatically extract patients problems from the interdisciplinary team notes and query evidence-based resources using the extracted terms. Using 4,335 de-identified interdisciplinary team notes for 525 patients, the system automatically extracted biomedical terminology from 4,219 notes and linked resources to 260 patient records. Sixty of those records (15 each for Pediatrics, Oncology & Hematology, Medical & Surgical, and Behavioral Health units) have been selected for an ongoing evaluation of the quality of automatically proactively delivered evidence and its usefulness in development of care plans.
Cai, Lile; Tay, Wei-Liang; Nguyen, Binh P; Chui, Chee-Kong; Ong, Sim-Heng
2013-01-01
Transfer functions play a key role in volume rendering of medical data, but transfer function manipulation is unintuitive and can be time-consuming; achieving an optimal visualization of patient anatomy or pathology is difficult. To overcome this problem, we present a system for automatic transfer function design based on visibility distribution and projective color mapping. Instead of assigning opacity directly based on voxel intensity and gradient magnitude, the opacity transfer function is automatically derived by matching the observed visibility distribution to a target visibility distribution. An automatic color assignment scheme based on projective mapping is proposed to assign colors that allow for the visual discrimination of different structures, while also reflecting the degree of similarity between them. When our method was tested on several medical volumetric datasets, the key structures within the volume were clearly visualized with minimal user intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Clement, Warren F.; Gorder, Pater J.; Jewell, Wayne F.; Coppenbarger, Richard
1990-01-01
Developing a single-pilot all-weather NOE capability requires fully automatic NOE navigation and flight control. Innovative guidance and control concepts are being investigated to (1) organize the onboard computer-based storage and real-time updating of NOE terrain profiles and obstacles; (2) define a class of automatic anticipative pursuit guidance algorithms to follow the vertical, lateral, and longitudinal guidance commands; (3) automate a decision-making process for unexpected obstacle avoidance; and (4) provide several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the recorded environment which is then used to determine an appropriate evasive maneuver if a nonconformity is observed. This research effort has been evaluated in both fixed-base and moving-base real-time piloted simulations thereby evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and reengagement of the automatic system.
A Prototype System to Support Evidence-based Practice
Demner-Fushman, Dina; Seckman, Charlotte; Fisher, Cheryl; Hauser, Susan E.; Clayton, Jennifer; Thoma, George R.
2008-01-01
Translating evidence into clinical practice is a complex process that depends on the availability of evidence, the environment into which the research evidence is translated, and the system that facilitates the translation. This paper presents InfoBot, a system designed for automatic delivery of patient-specific information from evidence-based resources. A prototype system has been implemented to support development of individualized patient care plans. The prototype explores possibilities to automatically extract patients’ problems from the interdisciplinary team notes and query evidence-based resources using the extracted terms. Using 4,335 de-identified interdisciplinary team notes for 525 patients, the system automatically extracted biomedical terminology from 4,219 notes and linked resources to 260 patient records. Sixty of those records (15 each for Pediatrics, Oncology & Hematology, Medical & Surgical, and Behavioral Health units) have been selected for an ongoing evaluation of the quality of automatically proactively delivered evidence and its usefulness in development of care plans. PMID:18998835
Automatic smoke evacuation in laparoscopic surgery: a simplified method for objective evaluation.
Takahashi, Hidekazu; Yamasaki, Makoto; Hirota, Masashi; Miyazaki, Yasuaki; Moon, Jeong Ho; Souma, Yoshihito; Mori, Masaki; Doki, Yuichiro; Nakajima, Kiyokazu
2013-08-01
Although its theoretical usefulness has been reported, the true value of automatic smoke evacuation system in laparoscopic surgery remains unknown. This is mainly due to the lack of objective evaluation. The purpose of this study was to determine the efficacy of the automatic smoke evacuator in laparoscopic surgery, by real-time objective evaluation system using an industrial smoke-detection device. Six pigs were used in this study. Three surgical ports were placed and electrosurgical smoke was generated in a standard fashion, using either a high-frequency electrosurgical unit (HF-ESU) or laparosonic coagulating shears (LCS). The smoke was evacuated immediately in the evacuation group but not in the control nonevacuation group. The laparoscopic field-of-view was subjectively evaluated by ten independent surgeons. The composition of the surgical smoke was analyzed by mass spectrometry. The residual smoke in the abdominal cavity was aspirated manually into a smoke tester, and stains on a filter paper were image captured, digitized, and semiquantified. Subjective evaluation indicated superior field-of-view in the evacuation group, compared with the control, at 15 s after activation of the HF-ESU (P < 0.05). The smoke comprised various chemical compounds, including known carcinogens. The estimated volume of intra-abdominal residual smoke after activation of HF-ESU was significantly lower in the evacuation group (47.4 ± 16.6) than the control (76.7 ± 2.4, P = 0.0018). Only marginal amount of surgical smoke was detected in both groups after LCS when the tissue pad was free from burnt tissue deposits. However, the amount was significantly lower in the evacuation group (21.3 ± 10.7) than the control (75 ± 39.9, P = 0.044) when the tissue pad contained tissue sludge. Automatic smoke evacuation provides better field-of-view and reduces the risk of exposure to harmful compounds.
New orbit recalculations of comet C/1890 F1 Brooks and its dynamical evolution
NASA Astrophysics Data System (ADS)
Królikowska, Małgorzata; Dybczyński, Piotr A.
2016-08-01
C/1890 F1 Brooks belongs to a group of 19 comets used by Jan Oort to support his famous hypothesis on the existence of a spherical cloud containing hundreds of billions of comets with orbits of semi-major axes between 50 000 and 150 000 au. Comet Brooks stands out from this group because of a long series of astrometric observations as well as a nearly 2-yr-long observational arc. Rich observational material makes this comet an ideal target for testing the rationality of an effort to recalculate astrometric positions on the basis of original (comet-star) measurements using modern star catalogues. This paper presents the results of such a new analysis based on two different methods: (I) automatic re-reduction based on cometary positions and the (comet-star) measurements and (II) partially automatic re-reduction based on the contemporary data for the reference stars originally used. We show that both methods offer a significant reduction in the uncertainty of orbital elements. Based on the most preferred orbital solution, the dynamical evolution of comet Brooks during three consecutive perihelion passages is discussed. We conclude that C/1890 F1 is a dynamically old comet that passed the Sun at a distance below 5 au during its previous perihelion passage. Furthermore, its next perihelion passage will be a little closer than during the 1890-1892 apparition. C/1890 F1 is interesting also because it suffered extremely small planetary perturbations when it travelled through the planetary zone. Therefore, in the next passage through perihelion, it will once again be a comet from the Oort spike.
Autonomously generating operations sequences for a Mars Rover using AI-based planning
NASA Technical Reports Server (NTRS)
Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg
2001-01-01
This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.
NASA Astrophysics Data System (ADS)
Armando, Alessandro; Giunchiglia, Enrico; Ponta, Serena Elisa
We present an approach to the formal specification and automatic analysis of business processes under authorization constraints based on the action language \\cal{C}. The use of \\cal{C} allows for a natural and concise modeling of the business process and the associated security policy and for the automatic analysis of the resulting specification by using the Causal Calculator (CCALC). Our approach improves upon previous work by greatly simplifying the specification step while retaining the ability to perform a fully automatic analysis. To illustrate the effectiveness of the approach we describe its application to a version of a business process taken from the banking domain and use CCALC to determine resource allocation plans complying with the security policy.
Instance-based categorization: automatic versus intentional forms of retrieval.
Neal, A; Hesketh, B; Andrews, S
1995-03-01
Two experiments are reported which attempt to disentangle the relative contribution of intentional and automatic forms of retrieval to instance-based categorization. A financial decision-making task was used in which subjects had to decide whether a bank would approve loans for a series of applicants. Experiment 1 found that categorization was sensitive to instance-specific knowledge, even when subjects had practiced using a simple rule. L. L. Jacoby's (1991) process-dissociation procedure was adapted for use in Experiment 2 to infer the relative contribution of intentional and automatic retrieval processes to categorization decisions. The results provided (1) strong evidence that intentional retrieval processes influence categorization, and (2) some preliminary evidence suggesting that automatic retrieval processes may also contribute to categorization decisions.
Support vector machine for automatic pain recognition
NASA Astrophysics Data System (ADS)
Monwar, Md Maruf; Rezaei, Siamak
2009-02-01
Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.
Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long
2016-01-01
We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229
Hasson, Dan; Anderberg, Ulla Maria; Theorell, Töres; Arnetz, Bengt B
2005-07-25
The aim of the present study was to assess possible effects on mental and physical well-being and stress-related biological markers of a web-based health promotion tool. A randomized, prospectively controlled study was conducted with before and after measurements, involving 303 employees (187 men and 116 women, age 23-64) from four information technology and two media companies. Half of the participants were offered web-based health promotion and stress management training (intervention) lasting for six months. All other participants constituted the reference group. Different biological markers were measured to detect possible physiological changes. After six months the intervention group had improved statistically significantly compared to the reference group on ratings of ability to manage stress, sleep quality, mental energy, concentration ability and social support. The anabolic hormone dehydroepiandosterone sulphate (DHEA-S) decreased significantly in the reference group as compared to unchanged levels in the intervention group. Neuropeptide Y (NPY) increased significantly in the intervention group compared to the reference group. Chromogranin A (CgA) decreased significantly in the intervention group as compared to the reference group. Tumour necrosis factor alpha (TNFalpha) decreased significantly in the reference group compared to the intervention group. Logistic regression analysis revealed that group (intervention vs. reference) remained a significant factor in five out of nine predictive models. The results indicate that an automatic web-based system might have short-term beneficial physiological and psychological effects and thus might be an opportunity in counteracting some clinically relevant and common stress and health issues of today.
Nimbi, Filippo Maria; Tripodi, Francesca; Simonelli, Chiara; Nobre, Pedro
2018-03-01
The Sexual Modes Questionnaire (SMQ) is a validated and widespread used tool to assess the association among negative automatic thoughts, emotions, and sexual response during sexual activity in men and women. To test the psychometric characteristics of the Italian version of the SMQ focusing on the Automatic Thoughts subscale (SMQ-AT). After linguistic translation, the psychometric properties (internal consistency, construct, and discriminant validity) were evaluated. 1,051 participants (425 men and 626 women, 776 healthy and 275 clinical groups complaining about sexual problems) participated in the present study. 2 confirmatory factor analyses were conducted to test the fit of the original factor structures of the SMQ versions. In addition, 2 principal component analyses were performed to highlight 2 new factorial structures that were further validated with confirmatory factor analyses. Cronbach α and composite reliability were used as internal consistency measures and differences between clinical and control groups were run to test the discriminant validity for the male and female versions. The associations with emotions and sexual functioning measures also are reported. Principal component analyses identified 5 factors in the male version: erection concerns thoughts, lack of erotic thoughts, age- and body-related thoughts, negative thoughts toward sex, and worries about partner's evaluation and failure anticipation thoughts. In the female version 6 factors were found: sexual abuse thoughts, lack of erotic thoughts, low self-body image thoughts, failure and disengagement thoughts, sexual passivity and control, and partner's lack of affection. Confirmatory factor analysis supported the adequacy of the factor structure for men and women. Moreover, the SMQ showed a strong association with emotional response and sexual functioning, differentiating between clinical and control groups. This measure is useful to evaluate patients and design interventions focused on negative automatic thoughts during sexual activity and to develop multicultural research. This study reports on the translation and validation of the Italian version of a clinically useful and widely used measure (assessing automatic thoughts during sexual activity). Limits regarding sampling technique and use of the Automatic Thoughts subscale are discussed in the article. The present findings support the validity and the internal consistency of the Italian version of the SMQ-AT and allow the assessment of negative automatic thoughts during sexual activity for clinical and research purposes. Nimbi FM, Tripodi F, Simonelli C, Nobre P. Sexual Modes Questionnaire (SMQ): Translation and Psychometric Properties of the Italian Version of the Automatic Thought Scale. J Sex Med 2018;15:396-409. Copyright © 2018 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
Antoniewicz, Franziska; Brand, Ralf
2016-04-01
This multistudy report used an experimental approach to alter automatic evaluations of exercise (AEE). First, we investigated the plasticity of AEE (study 1). A computerized evaluative conditioning task was developed that altered the AEE of participants in two experimental groups (acquisition of positive/negative associations involving exercising) and a control group (η2 part. = .11). Second, we examined connections between changes in AEE and subsequent exercise behavior (chosen intensity on a bike ergometer; study 2) in individuals that were placed in groups according to their baseline AEE. Group differences in exercise behavior were detected (η2 part. = .29). The effect was driven by the performance of the group with preexisting negative AEE that acquired more positive associations. This illustrates the effect of altered AEE on subsequent exercise behavior and the potential of AEE as a target for exercise intervention.
Nowinski, Wieslaw L; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G; Marchenko, Yevgen; Volkau, Ihar
2009-10-01
Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to Terminologia Anatomica. Because the cerebral models are fully segmented and labeled, our approach enables automatic and random atlas-derived generation of questions to test location and naming of cerebral structures. This is done in four steps: test individualization by the instructor, test taking by the students at their convenience, automatic student assessment by the application, and communication of the individual assessment to the instructor. A computer-based application with an interactive 3D atlas and a preliminary mobile-based application were developed to realize this approach. The application works in two test modes: instructor and student. In the instructor mode, the instructor customizes the test by setting the scope of testing and student performance criteria, which takes a few seconds. In the student mode, the student is tested and automatically assessed. Self-testing is also feasible at any time and pace. Our approach is automatic both with respect to test generation and student assessment. It is also objective, rapid, and customizable. We believe that this approach is novel from computer-based, mobile-based, and atlas-assisted standpoints.
The unbalanced signal measuring of automotive brake drum
NASA Astrophysics Data System (ADS)
Wang, Xiao-Dong; Ye, Sheng-Hua; Zhang, Bang-Cheng
2005-04-01
For the purpose of the research and development of automatic balancing system by mass removing, the dissertation deals with the measuring method of the unbalance signal, the design the automatic balance equipment and the software. This paper emphases the testing system of the balancer of automotive brake drum. The paper designs the band-pass filter product with favorable automatic follow of electronic product, and with favorable automatic follow capability, filtration effect and stability. The system of automatic balancing system by mass removing based on virtual instrument is designed in this paper. A lab system has been constructed. The results of contrast experiments indicate the notable effect of 1-plane automatic balance and the high precision of dynamic balance, and demonstrate the application value of the system.
Diagnosis related group grouping study of senile cataract patients based on E-CHAID algorithm.
Luo, Ai-Jing; Chang, Wei-Fu; Xin, Zi-Rui; Ling, Hao; Li, Jun-Jie; Dai, Ping-Ping; Deng, Xuan-Tong; Zhang, Lei; Li, Shao-Gang
2018-01-01
To figure out the contributed factors of the hospitalization expenses of senile cataract patients (HECP) and build up an area-specified senile cataract diagnosis related group (DRG) of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund. The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector (E-CHAID) model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc. The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases. The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.
Diagnosis related group grouping study of senile cataract patients based on E-CHAID algorithm
Luo, Ai-Jing; Chang, Wei-Fu; Xin, Zi-Rui; Ling, Hao; Li, Jun-Jie; Dai, Ping-Ping; Deng, Xuan-Tong; Zhang, Lei; Li, Shao-Gang
2018-01-01
AIM To figure out the contributed factors of the hospitalization expenses of senile cataract patients (HECP) and build up an area-specified senile cataract diagnosis related group (DRG) of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund. METHODS The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector (E-CHAID) model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc. RESULTS The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases. CONCLUSION The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund. PMID:29487824
Dissociative identity disorder and prepulse inhibition of the acoustic startle reflex
Dale, Karl Yngvar; Flaten, Magne Arve; Elden, Åke; Holte, Arne
2008-01-01
A group of persons with dissociative identity disorder (DID) was compared with a group of persons with other dissociative disorders, and a group of nondiagnosed controls with regard to prepulse inhibition (PPI) of the acoustic startle reflex. The findings suggest maladaptive attentional processes at a controlled level, but not at a preattentive automatic level, in persons with DID. The prepulse occupied more controlled attentional resources in the DID group compared with the other two groups. Preattentive automatic processing, on the other hand, was normal in the DID group. Moreover, startle reflexes did not habituate in the DID group. In conclusion, increased PPI and delayed habituation is consistent with increased vigilance in individuals with DID. The present findings of reduced habituation of startle reflexes and increased PPI in persons with DID suggest the operation of a voluntary process that directs attention away from unpleasant or threatening stimuli. Aberrant voluntary attentional processes may thus be a defining characteristic in DID. PMID:18830396
NASA Astrophysics Data System (ADS)
Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra
2018-03-01
The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task.
Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra
2018-03-01
The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
NASA Astrophysics Data System (ADS)
Qin, Xulei; Cong, Zhibin; Halig, Luma V.; Fei, Baowei
2013-03-01
An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.
Development and evaluation of automatic landing control laws for power lift STOL aircraft
NASA Technical Reports Server (NTRS)
Feinreich, B.; Gevaert, G.
1981-01-01
A series of investigations were conducted to generate and verify through ground bases simulation and flight research a data base to aid in the design and certification of advanced propulsive lift short takeoff and landing aircraft. Problems impacting the design of powered lift short haul aircraft that are to be landed automatically on STOL runways in adverse weather were examined. An understanding of the problems was gained by a limited coverage of important elements that are normally included in the certification process of a CAT 3 automatic landing system.
FAMA: Fast Automatic MOOG Analysis
NASA Astrophysics Data System (ADS)
Magrini, Laura; Randich, Sofia; Friel, Eileen; Spina, Lorenzo; Jacobson, Heather; Cantat-Gaudin, Tristan; Donati, Paolo; Baglioni, Roberto; Maiorca, Enrico; Bragaglia, Angela; Sordo, Rosanna; Vallenari, Antonella
2014-02-01
FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.
NASA Astrophysics Data System (ADS)
Widyaningrum, E.; Gorte, B. G. H.
2017-05-01
LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.
Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad
2017-01-01
Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.
Olguin Olguin, Daniel; Waber, Benjamin N; Kim, Taemie; Mohan, Akshay; Ara, Koji; Pentland, Alex
2009-02-01
We present the design, implementation, and deployment of a wearable computing platform for measuring and analyzing human behavior in organizational settings. We propose the use of wearable electronic badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels in order to capture individual and collective patterns of behavior. Our goal is to be able to understand how patterns of behavior shape individuals and organizations. By using on-body sensors in large groups of people for extended periods of time in naturalistic settings, we have been able to identify, measure, and quantify social interactions, group behavior, and organizational dynamics. We deployed this wearable computing platform in a group of 22 employees working in a real organization over a period of one month. Using these automatic measurements, we were able to predict employees' self-assessments of job satisfaction and their own perceptions of group interaction quality by combining data collected with our platform and e-mail communication data. In particular, the total amount of communication was predictive of both of these assessments, and betweenness in the social network exhibited a high negative correlation with group interaction satisfaction. We also found that physical proximity and e-mail exchange had a negative correlation of r = -0.55 (p 0.01), which has far-reaching implications for past and future research on social networks.
Nguyen, Nga; Vandenbroucke, Laurent; Hernández, Alfredo; Pham, Tu; Beuchée, Alain; Pladys, Patrick
2017-05-01
This study examined the heart rate variability characteristics associated with early-onset neonatal sepsis in a prospective, observational controlled study. Eligible patients were full-term neonates hospitalised with clinical signs that suggested early-onset sepsis and a C-reactive protein of >10 mg/L. Sepsis was considered proven in cases of symptomatic septicaemia, meningitis, pneumonia or enterocolitis. Heart rate variability parameters (n = 16) were assessed from five-, 15- and 30-minute stationary sequences automatically selected from electrocardiographic recordings performed at admission and compared with a control group using the U-test with post hoc Benjamini-Yekutieli correction. Stationary sequences corresponded to the periods with the lowest changes of heart rate variability over time. A total of 40 full-term infants were enrolled, including 14 with proven sepsis. The mean duration of the cardiac cycle length was lower in the proven sepsis group than in the control group (n = 11), without other significant changes in heart rate variability parameters. These durations, measured in five-minute stationary periods, were 406 (367-433) ms in proven sepsis group versus 507 (463-522) ms in the control group (p < 0.05). Early-onset neonatal sepsis was associated with a high mean heart rate measured during automatically selected stationary periods. ©2017 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.
Automatic Extraction of Metadata from Scientific Publications for CRIS Systems
ERIC Educational Resources Information Center
Kovacevic, Aleksandar; Ivanovic, Dragan; Milosavljevic, Branko; Konjovic, Zora; Surla, Dusan
2011-01-01
Purpose: The aim of this paper is to develop a system for automatic extraction of metadata from scientific papers in PDF format for the information system for monitoring the scientific research activity of the University of Novi Sad (CRIS UNS). Design/methodology/approach: The system is based on machine learning and performs automatic extraction…
ERIC Educational Resources Information Center
Lorié, William A.
2013-01-01
A reverse engineering approach to automatic item generation (AIG) was applied to a figure-based publicly released test item from the Organisation for Economic Cooperation and Development (OECD) Programme for International Student Assessment (PISA) mathematical literacy cognitive instrument as part of a proof of concept. The author created an item…
ERIC Educational Resources Information Center
Young, Victoria; Mihailidis, Alex
2010-01-01
Despite their growing presence in home computer applications and various telephony services, commercial automatic speech recognition technologies are still not easily employed by everyone; especially individuals with speech disorders. In addition, relatively little research has been conducted on automatic speech recognition performance with older…
Eliminating the Simon Effect by Instruction
ERIC Educational Resources Information Center
Theeuwes, Marijke; Liefooghe, Baptist; De Houwer, Jan
2014-01-01
A growing body of research demonstrates that instructions can elicit automatic response activations. The results of the present study indicate that instruction-based response activations can also counteract automatic response activations based on long-term associations. To this end, we focused on the Simon effect, which is the observation that…
A Network of Automatic Control Web-Based Laboratories
ERIC Educational Resources Information Center
Vargas, Hector; Sanchez Moreno, J.; Jara, Carlos A.; Candelas, F. A.; Torres, Fernando; Dormido, Sebastian
2011-01-01
This article presents an innovative project in the context of remote experimentation applied to control engineering education. Specifically, the authors describe their experience regarding the analysis, design, development, and exploitation of web-based technologies within the scope of automatic control. This work is part of an inter-university…
Development of an automatic subsea blowout preventer stack control system using PLC based SCADA.
Cai, Baoping; Liu, Yonghong; Liu, Zengkai; Wang, Fei; Tian, Xiaojie; Zhang, Yanzhen
2012-01-01
An extremely reliable remote control system for subsea blowout preventer stack is developed based on the off-the-shelf triple modular redundancy system. To meet a high reliability requirement, various redundancy techniques such as controller redundancy, bus redundancy and network redundancy are used to design the system hardware architecture. The control logic, human-machine interface graphical design and redundant databases are developed by using the off-the-shelf software. A series of experiments were performed in laboratory to test the subsea blowout preventer stack control system. The results showed that the tested subsea blowout preventer functions could be executed successfully. For the faults of programmable logic controllers, discrete input groups and analog input groups, the control system could give correct alarms in the human-machine interface. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Lyall-Wilson, Jennifer Rae
2013-01-01
The dissertation research explores an approach to automatic concept-based query expansion to improve search engine performance. It uses a network-based approach for identifying the concept represented by the user's query and is founded on the idea that a collection-specific association thesaurus can be used to create a reasonable representation of…
ERIC Educational Resources Information Center
Pujayanto, Pujayanto; Budiharti, Rini; Adhitama, Egy; Nuraini, Niken Rizky Amalia; Putri, Hanung Vernanda
2018-01-01
This research proposes the development of a web-based assessment system to identify students' misconception. The system, named WAS (web-based assessment system), can identify students' misconception profile on linear kinematics automatically after the student has finished the test. The test instrument was developed and validated. Items were…
Automatic Extraction of Urban Built-Up Area Based on Object-Oriented Method and Remote Sensing Data
NASA Astrophysics Data System (ADS)
Li, L.; Zhou, H.; Wen, Q.; Chen, T.; Guan, F.; Ren, B.; Yu, H.; Wang, Z.
2018-04-01
Built-up area marks the use of city construction land in the different periods of the development, the accurate extraction is the key to the studies of the changes of urban expansion. This paper studies the technology of automatic extraction of urban built-up area based on object-oriented method and remote sensing data, and realizes the automatic extraction of the main built-up area of the city, which saves the manpower cost greatly. First, the extraction of construction land based on object-oriented method, the main technical steps include: (1) Multi-resolution segmentation; (2) Feature Construction and Selection; (3) Information Extraction of Construction Land Based on Rule Set, The characteristic parameters used in the rule set mainly include the mean of the red band (Mean R), Normalized Difference Vegetation Index (NDVI), Ratio of residential index (RRI), Blue band mean (Mean B), Through the combination of the above characteristic parameters, the construction site information can be extracted. Based on the degree of adaptability, distance and area of the object domain, the urban built-up area can be quickly and accurately defined from the construction land information without depending on other data and expert knowledge to achieve the automatic extraction of the urban built-up area. In this paper, Beijing city as an experimental area for the technical methods of the experiment, the results show that: the city built-up area to achieve automatic extraction, boundary accuracy of 2359.65 m to meet the requirements. The automatic extraction of urban built-up area has strong practicality and can be applied to the monitoring of the change of the main built-up area of city.
NASA Astrophysics Data System (ADS)
Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir
2008-03-01
Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.
Reisner, Andrew T; Chen, Liangyou; McKenna, Thomas M; Reifman, Jaques
2008-10-01
Prehospital severity scores can be used in routine prehospital care, mass casualty care, and military triage. If computers could reliably calculate clinical scores, new clinical and research methodologies would be possible. One obstacle is that vital signs measured automatically can be unreliable. We hypothesized that Signal Quality Indices (SQI's), computer algorithms that differentiate between reliable and unreliable monitored physiologic data, could improve the predictive power of computer-calculated scores. In a retrospective analysis of trauma casualties transported by air ambulance, we computed the Triage Revised Trauma Score (RTS) from archived travel monitor data. We compared the areas-under-the-curve (AUC's) of receiver operating characteristic curves for prediction of mortality and red blood cell transfusion for 187 subjects with comparable quantities of good-quality and poor-quality data. Vital signs deemed reliable by SQI's led to significantly more discriminatory severity scores than vital signs deemed unreliable. We also compared automatically-computed RTS (using the SQI's) versus RTS computed from vital signs documented by medics. For the subjects in whom the SQI algorithms identified 15 consecutive seconds of reliable vital signs data (n = 350), the automatically-computed scores' AUC's were the same as the medic-based scores' AUC's. Using the Prehospital Index in place of RTS led to very similar results, corroborating our findings. SQI algorithms improve automatically-computed severity scores, and automatically-computed scores using SQI's are equivalent to medic-based scores.
Paschalis, Vassilis; Theodorou, Anastasios A.; Panayiotou, George; Kyparos, Antonios; Patikas, Dimitrios; Grivas, Gerasimos V.; Nikolaidis, Michalis G.; Vrabas, Ioannis S.
2013-01-01
A novel automatic escalator was designed, constructed and used in the present investigation. The aim of the present investigation was to compare the effect of two repeated sessions of stair descending versus stair ascending exercise on muscle performance and health-related parameters in young healthy men. Twenty males participated and were randomly divided into two equal-sized groups: a stair descending group (muscle-damaging group) and a stair ascending group (non-muscle-damaging group). Each group performed two sessions of stair descending or stair ascending exercise on the automatic escalator while a three week period was elapsed between the two exercise sessions. Indices of muscle function, insulin sensitivity, blood lipid profile and redox status were assessed before and immediately after, as well as at day 2 and day 4 after both exercise sessions. It was found that the first bout of stair descending exercise caused muscle damage, induced insulin resistance and oxidative stress as well as affected positively blood lipid profile. However, after the second bout of stair descending exercise the alterations in all parameters were diminished or abolished. On the other hand, the stair ascending exercise induced only minor effects on muscle function and health-related parameters after both exercise bouts. The results of the present investigation indicate that stair descending exercise seems to be a promising way of exercise that can provoke positive effects on blood lipid profile and antioxidant status. PMID:23437093
Automatic attentional orienting to other people's gaze in schizophrenia.
Langdon, Robyn; Seymour, Kiley; Williams, Tracey; Ward, Philip B
2017-08-01
Explicit tests of social cognition have revealed pervasive deficits in schizophrenia. Less is known of automatic social cognition in schizophrenia. We used a spatial orienting task to investigate automatic shifts of attention cued by another person's eye gaze in 29 patients and 28 controls. Central photographic images of a face with eyes shifted left or right, or looking straight ahead, preceded targets that appeared left or right of the cue. To examine automatic effects, cue direction was non-predictive of target location. Cue-target intervals were 100, 300, and 800 ms. In non-social control trials, arrows replaced eye-gaze cues. Both groups showed automatic attentional orienting indexed by faster reaction times (RTs) when arrows were congruent with target location across all cue-target intervals. Similar congruency effects were seen for eye-shift cues at 300 and 800 ms intervals, but patients showed significantly larger congruency effects at 800 ms, which were driven by delayed responses to incongruent target locations. At short 100-ms cue-target intervals, neither group showed faster RTs for congruent than for incongruent eye-shift cues, but patients were significantly slower to detect targets after direct-gaze cues. These findings conflict with previous studies using schematic line drawings of eye-shifts that have found automatic attentional orienting to be reduced in schizophrenia. Instead, our data indicate that patients display abnormalities in responding to gaze direction at various stages of gaze processing-reflected by a stronger preferential capture of attention by another person's direct eye contact at initial stages of gaze processing and difficulties disengaging from a gazed-at location once shared attention is established.
Hsu, Li-Yueh; Wragg, Andrew; Anderson, Stasia A; Balaban, Robert S; Boehm, Manfred; Arai, Andrew E
2008-02-01
This study presents computerized automatic image analysis for quantitatively evaluating dynamic contrast-enhanced MRI in an ischemic rat hindlimb model. MRI at 7 T was performed on animals in a blinded placebo-controlled experiment comparing multipotent adult progenitor cell-derived progenitor cell (MDPC)-treated, phosphate buffered saline (PBS)-injected, and sham-operated rats. Ischemic and non-ischemic limb regions of interest were automatically segmented from time-series images for detecting changes in perfusion and late enhancement. In correlation analysis of the time-signal intensity histograms, the MDPC-treated limbs correlated well with their corresponding non-ischemic limbs. However, the correlation coefficient of the PBS control group was significantly lower than that of the MDPC-treated and sham-operated groups. In semi-quantitative parametric maps of contrast enhancement, there was no significant difference in hypo-enhanced area between the MDPC and PBS groups at early perfusion-dependent time frames. However, the late-enhancement area was significantly larger in the PBS than the MDPC group. The results of this exploratory study show that MDPC-treated rats could be objectively distinguished from PBS controls. The differences were primarily determined by late contrast enhancement of PBS-treated limbs. These computerized methods appear promising for assessing perfusion and late enhancement in dynamic contrast-enhanced MRI.
[Comparison of different types automatic water-supply system for mouse rearing (author's transl)].
Kikuchi, S; Suzuki, M; Tagashira, Y
1979-04-01
Rearing and breeding scores were compared between groups of mice (JCL : ICR and ddN strains) raised with two different types of automatic water-supply systems; the Japanese type and the American type, using manual water-supply system as control. The mice raised with the manual water-supply system were superior in body weight gain as compared to those with two automatic water-supply systems. As to the survival rate, however, the m; anual water-supply system and the Japanese type gave better results than the American type. As to weanling rate in the breeding test, the manual water-supply system gave somewhat better result than either of the two automatic types. Accidental water leaks, which are serious problems of automatic systems, occurred frequently only when the American type was used. Only one defect of the Japanese type revealed was that it was unfavorable for mice with smaller size (e.g., young ddN mice), resulting in lower body weight gain as well as lower breeding scores.
Water footbath, automatic flushing, and disinfection to improve the health of bovine feet.
Fjeldaas, T; Knappe-Poindecker, M; Bøe, K E; Larssen, R B
2014-05-01
Disinfecting footbaths are used to treat and prevent interdigital dermatitis (ID) and heel horn erosion (HHE). However, many disinfectants are disadvantageous for the environment and, as an alternative, washing of the feet has been introduced. Our aim was to investigate the effect of water footbaths (trial 1), footbaths with CuSO4 (trial 2), automatic water flushing (trial 3), and water flushing followed by disinfection with a glutaraldehyde-based compound (trial 4) in 4 randomized controlled clinical trials performed in a freestall dairy herd of approximately 45 Norwegian Red cows. At trimming before and after each trial, hind foot diseases, hardness of the claw horn (in D-units), locomotion, and cleanliness of the claws were recorded. Before each trial, the cows were divided in comparable study and control groups, based on prevalence of ID and HHE, parity, and days in milk. Using a transponder-regulated gate, the study groups were led through a footbath (trials 1 and 2) or an automatic washer (trials 3 and 4), whereas the control groups were left untreated. Each trial lasted 3 mo and the curative effect in diseased cows and the preventive effect in cows with healthy feet on ID, HHE, and ID + HHE were analyzed. In trial 2, a preventive effect of CuSO4 on HHE compared with the untreated cows was observed. During trial 1, 100% (11/11) of the treated cows with ID got better and 22% (2/9) without ID became diseased, whereas 92% (11/12) of the treated cows with ID + HHE got better and 38% (3/8) without ID + HHE became diseased. During trial 2, 69% (9/13) of the treated cows with ID got better and 11% (1/9) without ID became diseased. During trial 4, 19% (3/16) of the untreated cows with ID + HHE got better and 71% (5/7) without ID + HHE became diseased. In trial 3, no significant effects on ID, HHE, or ID + HHE were revealed. In trial 2 (CuSO4), the treated cows' claw horn was harder after the trial compared with the controls (D-unit difference: 13.25). In trial 3 (stationary water flushing) the treated cows' claw horn was softer after the trial when compared with the controls (D-unit difference: -15.66). The CuSO4 footbaths were useful to prevent HHE and indicate that automatic stationary flushing with only water had no beneficial effect on ID or HHE. The claw horn of cows walking through CuSO4 became harder and the claw horn of cows that had their hind feet flushed with water became softer compared with the controls. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Matsuda, H; Mizumura, S; Nemoto, K; Yamashita, F; Imabayashi, E; Sato, N; Asada, T
2012-06-01
The necessity for structural MRI is greater than ever to both diagnose AD in its early stage and objectively evaluate its progression. We propose a new VBM-based software program for automatic detection of early specific atrophy in AD. A target VOI was determined by group comparison of 30 patients with very mild AD and 40 age-matched healthy controls by using SPM. Then this target VOI was incorporated into a newly developed automated software program independently running on a Windows PC for VBM by using SPM8 plus DARTEL. ROC analysis was performed for discrimination of 116 other patients with AD with very mild stage (n = 45), mild stage (n = 30) and moderate-to-advanced stages (n = 41) from 40 other age-matched healthy controls by using a z score map in the target VOI. Medial temporal structures involving the entire region of the entorhinal cortex, hippocampus, and amygdala showed significant atrophy in the patients with very mild AD and were determined as a target VOI. When we used the severity score of atrophy in this target VOI, 91.6%, 95.8%, and 98.2% accuracies were obtained in the very mild AD, mild AD, and moderate-to-severe AD groups, respectively. In the very mild AD group, a high specificity of 97.5% with a sensitivity of 86.4% was obtained, and age at onset of AD did not influence this accuracy. This software program with application of SPM8 plus DARTEL to VBM provides a high performance for AD diagnosis by using MRI.
Riley, Kristen E; Lee, Jasper S; Safren, Steven A
2017-10-01
Depression in people living with HIV/AIDS (PLWHA) is highly prevalent and related to worse adherence to antiretroviral therapy, but is amenable to change via CBT. Cognitive-behavioral therapy for adherence and depression (CBT-AD) specifically addresses negative automatic thoughts (ATs) as one component of the treatment. There is little research on the temporal nature of the relation between ATs and depression. HIV-positive adults with depression (N=240) were randomized to CBT-AD, information/supportive psychotherapy for adherence and depression (ISP-AD), or one session of adherence counseling alone (ETAU). ATs were self-reported (Automatic Thoughts Questionnaire; ATQ) and depression was assessed by blinded interview (Montgomery-Asberg Depression Rating Scale; MADRS) at baseline, and 4-, 8-, and 12-months. We performed autoregressive cross-lagged panel models. Broadly, decreases in ATs were followed by decreases in depression, but decreases in depression were not followed by decreases in ATs. In CBT-AD, decreases in ATs were followed by decreases in depression, and vice versa. However, in the ISP group, while depression and ATs both significantly influenced each other, not all relations were in the direction expected. This study adds to the evidence base for cognitive interventions to decrease depression in individuals with a chronic medical condition, HIV/AIDS.
Definition and automatic anatomy recognition of lymph node zones in the pelvis on CT images
NASA Astrophysics Data System (ADS)
Liu, Yu; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Guo, Shuxu; Attor, Rosemary; Reinicke, Danica; Torigian, Drew A.
2016-03-01
Currently, unlike IALSC-defined thoracic lymph node zones, no explicitly provided definitions for lymph nodes in other body regions are available. Yet, definitions are critical for standardizing the recognition, delineation, quantification, and reporting of lymphadenopathy in other body regions. Continuing from our previous work in the thorax, this paper proposes a standardized definition of the grouping of pelvic lymph nodes into 10 zones. We subsequently employ our earlier Automatic Anatomy Recognition (AAR) framework designed for body-wide organ modeling, recognition, and delineation to actually implement these zonal definitions where the zones are treated as anatomic objects. First, all 10 zones and key anatomic organs used as anchors are manually delineated under expert supervision for constructing fuzzy anatomy models of the assembly of organs together with the zones. Then, optimal hierarchical arrangement of these objects is constructed for the purpose of achieving the best zonal recognition. For actual localization of the objects, two strategies are used -- optimal thresholded search for organs and one-shot method for the zones where the known relationship of the zones to key organs is exploited. Based on 50 computed tomography (CT) image data sets for the pelvic body region and an equal division into training and test subsets, automatic zonal localization within 1-3 voxels is achieved.
Mark, Daniel B.; Anstrom, Kevin J.; McNulty, Steven E.; Flaker, Greg C.; Tonkin, Andrew M.; Smith, Warren M.; Toff, William D.; Dorian, Paul; Clapp-Channing, Nancy E.; Anderson, Jill; Johnson, George; Schron, Eleanor B.; Poole, Jeanne E.; Lee, Kerry L.; Bardy, Gust H.
2010-01-01
Background Public access automatic external defibrillators (AEDs) can save lives, but most deaths from out-of-hospital sudden cardiac arrest occur at home. The Home Automatic External Defibrillator Trial (HAT) found no survival advantage for adding a home AED to cardiopulmonary resuscitation (CPR) training for 7001 patients with a prior anterior wall myocardial infarction. Quality of life (QOL) outcomes for both the patient and spouse/companion were secondary endpoints. Methods A subset of 1007 study patients and their spouse/companions was randomly selected for ascertainment of QOL by structured interview at baseline and 12 and 24 months following enrollment. The primary QOL measures were the Medical Outcomes Study 36-Item Short-Form (SF-36) psychological well-being (reflecting anxiety and depression) and vitality (reflecting energy and fatigue) subscales. Results For patients and spouse/companions, the psychological well-being and vitality scales did not differ significantly between those randomly assigned an AED plus CPR training and controls who received CPR training only. None of the other QOL measures collected showed a clinically and statistically significant difference between treatment groups. Patients in the AED group were more likely to report being extremely or quite a bit reassured by their treatment assignment. Spouse/companions in the AED group reported being less often nervous about the possibility of using AED/CPR treatment than those in the CPR group. Conclusions Adding access to a home AED to CPR training did not affect quality of life either for patients with a prior anterior myocardial infarction or their spouse/companion but did provide more reassurance to the patients without increasing anxiety for spouse/companions. PMID:20362722
Selvester scoring in patients with strict LBBB using the QUARESS software.
Xia, Xiaojuan; Chaudhry, Uzma; Wieslander, Björn; Borgquist, Rasmus; Wagner, Galen S; Strauss, David G; Platonov, Pyotr; Ugander, Martin; Couderc, Jean-Philippe
2015-01-01
Estimation of the infarct size from body-surface ECGs in post-myocardial infarction patients has become possible using the Selvester scoring method. Automation of this scoring has been proposed in order to speed-up the measurement of the score and improving the inter-observer variability in computing a score that requires strong expertise in electrocardiography. In this work, we evaluated the quality of the QuAReSS software for delivering correct Selvester scoring in a set of standard 12-lead ECGs. Standard 12-lead ECGs were recorded in 105 post-MI patients prescribed implantation of an implantable cardiodefibrillator (ICD). Amongst the 105 patients with standard clinical left bundle branch block (LBBB) patterns, 67 had a LBBB pattern meeting the strict criteria. The QuAReSS software was applied to these 67 tracings by two independent groups of cardiologists (from a clinical group and an ECG core laboratory) to measure the Selvester score semi-automatically. Using various level of agreement metrics, we compared the scores between groups and when automatically measured by the software. The average of the absolute difference in Selvester scores measured by the two independent groups was 1.4±1.5 score points, whereas the difference between automatic method and the two manual adjudications were 1.2±1.2 and 1.3±1.2 points. Eighty-two percent score agreement was observed between the two independent measurements when the difference of score was within two point ranges, while 90% and 84% score agreements were reached using the automatic method compared to the two manual adjudications. The study confirms that the QuAReSS software provides valid measurements of the Selvester score in patients with strict LBBB with minimal correction from cardiologists. Copyright © 2015 Elsevier Inc. All rights reserved.
Simpson, Austin J; Todd, Andrew R
2017-09-01
Reasoning about what other people see, know, and want is essential for navigating social life. Yet, even neurodevelopmentally healthy adults make perspective-taking errors. Here, we examined how the group membership of perspective-taking targets (ingroup vs. outgroup) affects processes underlying visual perspective-taking. In three experiments using two bases of group identity (university affiliation and minimal groups), interference from one's own differing perspective (i.e., egocentric intrusion) was stronger when responding from an ingroup versus an outgroup member's perspective. Spontaneous perspective calculation, as indexed by interference from another's visual perspective when reporting one's own (i.e., altercentric intrusion), did not differ across target group membership in any of our experiments. Process-dissociation analyses, which aim to isolate automatic processes underlying altercentric-intrusion effects, further revealed negligible effects of target group membership on perspective calculation. Meta-analytically, however, there was suggestive evidence that shared group membership facilitates responding from others' perspectives when self and other perspectives are aligned. Copyright © 2017 Elsevier B.V. All rights reserved.
Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT
NASA Astrophysics Data System (ADS)
Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi
2017-05-01
Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.
Trendel, Olivier; Werle, Carolina O C
2016-09-01
Eating behaviors largely result from automatic processes. Yet, in existing research, automatic or implicit attitudes toward food often fail to predict eating behaviors. Applying findings in cognitive neuroscience research, we propose and find that a central reason why implicit attitudes toward food are not good predictors of eating behaviors is that implicit attitudes are driven by two distinct constructs that often have diverging evaluative consequences: the automatic affective reactions to food (e.g., tastiness; the affective basis of implicit attitudes) and the automatic cognitive reactions to food (e.g., healthiness; the cognitive basis of implicit attitudes). More importantly, we find that the affective and cognitive bases of implicit attitudes directly and uniquely influence actual food choices under different conditions. While the affective basis of implicit attitude is the main driver of food choices, it is the only driver when cognitive resources during choice are limited. The cognitive basis of implicit attitudes uniquely influences food choices when cognitive resources during choice are plentiful but only for participants low in impulsivity. Researchers interested in automatic processes in eating behaviors could thus benefit by distinguishing between the affective and cognitive bases of implicit attitudes. Copyright © 2015 Elsevier Ltd. All rights reserved.
Arkheia: Data Management and Communication for Open Computational Neuroscience
Antolík, Ján; Davison, Andrew P.
2018-01-01
Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience. PMID:29556187
Kaakinen, M; Huttunen, S; Paavolainen, L; Marjomäki, V; Heikkilä, J; Eklund, L
2014-01-01
Phase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.
Arkheia: Data Management and Communication for Open Computational Neuroscience.
Antolík, Ján; Davison, Andrew P
2018-01-01
Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience.
NASA Astrophysics Data System (ADS)
Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Ramirez-Cortes, J.; Renero-Carrillo, F.
2015-11-01
This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 94.33% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented.
Higher-order automatic differentiation of mathematical functions
NASA Astrophysics Data System (ADS)
Charpentier, Isabelle; Dal Cappello, Claude
2015-04-01
Functions of mathematical physics such as the Bessel functions, the Chebyshev polynomials, the Gauss hypergeometric function and so forth, have practical applications in many scientific domains. On the one hand, differentiation formulas provided in reference books apply to real or complex variables. These do not account for the chain rule. On the other hand, based on the chain rule, the automatic differentiation has become a natural tool in numerical modeling. Nevertheless automatic differentiation tools do not deal with the numerous mathematical functions. This paper describes formulas and provides codes for the higher-order automatic differentiation of mathematical functions. The first method is based on Faà di Bruno's formula that generalizes the chain rule. The second one makes use of the second order differential equation they satisfy. Both methods are exemplified with the aforementioned functions.
Density estimation in aerial images of large crowds for automatic people counting
NASA Astrophysics Data System (ADS)
Herrmann, Christian; Metzler, Juergen
2013-05-01
Counting people is a common topic in the area of visual surveillance and crowd analysis. While many image-based solutions are designed to count only a few persons at the same time, like pedestrians entering a shop or watching an advertisement, there is hardly any solution for counting large crowds of several hundred persons or more. We addressed this problem previously by designing a semi-automatic system being able to count crowds consisting of hundreds or thousands of people based on aerial images of demonstrations or similar events. This system requires major user interaction to segment the image. Our principle aim is to reduce this manual interaction. To achieve this, we propose a new and automatic system. Besides counting the people in large crowds, the system yields the positions of people allowing a plausibility check by a human operator. In order to automatize the people counting system, we use crowd density estimation. The determination of crowd density is based on several features like edge intensity or spatial frequency. They indicate the density and discriminate between a crowd and other image regions like buildings, bushes or trees. We compare the performance of our automatic system to the previous semi-automatic system and to manual counting in images. By counting a test set of aerial images showing large crowds containing up to 12,000 people, the performance gain of our new system will be measured. By improving our previous system, we will increase the benefit of an image-based solution for counting people in large crowds.
Extending Wi-Fi Direct for Automated Operations
2015-03-01
functionalities. These added functionalities include: automatic device discovery, a mutual awareness of capabilities between devices (inter-device capability ...functionalities include: automatic device discove1y, a mutual awareness of capabilities between devices (inter-device capability awareness...Figure 7. P2P Device GO Negotiation Request (The P2P IE includes P2P Capability , P2P Device Info, Group Owner Intent, Configuration Timeout, Listen
ERIC Educational Resources Information Center
Taub, Gordon E.; Szente, Judit
2012-01-01
The purpose of this study was to explore the relationship between phonological awareness (PA) and rapid automatized naming (RAN) on the reading fluency (RF) of students from traditionally underrepresented groups. The study included 86 participants attending 1st through 4th grade within an inner-city charter school located in a high-poverty, urban…
Shaping Attention with Reward: Effects of Reward on Space- and Object-Based Selection
Shomstein, Sarah; Johnson, Jacoba
2014-01-01
The contribution of rewarded actions to automatic attentional selection remains obscure. We hypothesized that some forms of automatic orienting, such as object-based selection, can be completely abandoned in lieu of reward maximizing strategy. While presenting identical visual stimuli to the observer, in a set of two experiments, we manipulate what is being rewarded (different object targets or random object locations) and the type of reward received (money or points). It was observed that reward alone guides attentional selection, entirely predicting behavior. These results suggest that guidance of selective attention, while automatic, is flexible and can be adjusted in accordance with external non-sensory reward-based factors. PMID:24121412
Wolf, Beverly; Abbott, Robert D; Berninger, Virginia W
2017-02-01
In Study 1, the treatment group ( N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group ( N =16 first graders, M = 7 years 1 month, 7 girls) received manuscript handwriting instruction not systematically related to the other literacy activities. ANOVA showed both groups improved on automatic alphabet writing from memory; but ANCOVA with the automatic alphabet writing task as covariate showed that the treatment group improved significantly more than control group from the second to ninth month of first grade on dictated spelling and recognition of word-specific spellings among phonological foils. In Study 2 new groups received either a second year of manuscript ( N = 29, M = 7 years 8 months, 16 girls) or introduction to cursive (joined) instruction in second grade ( N = 24, M = 8 years 0 months, 11 girls) embedded in the Slingerland literacy program. ANCOVA with automatic alphabet writing as covariate showed that those who received a second year of manuscript handwriting instruction improved more on sustained handwriting over 30, 60, and 90 seconds than those who had had only one year of manuscript instruction; both groups improved in spelling and composing from the second to ninth month of second grade. Results are discussed in reference to mastering one handwriting format before introducing another format at a higher grade level and always embedding handwriting instruction in writing and reading instruction aimed at all levels of language.
Wolf, Beverly; Abbott, Robert D.; Berninger, Virginia W.
2016-01-01
In Study 1, the treatment group (N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group (N =16 first graders, M = 7 years 1 month, 7 girls) received manuscript handwriting instruction not systematically related to the other literacy activities. ANOVA showed both groups improved on automatic alphabet writing from memory; but ANCOVA with the automatic alphabet writing task as covariate showed that the treatment group improved significantly more than control group from the second to ninth month of first grade on dictated spelling and recognition of word-specific spellings among phonological foils. In Study 2 new groups received either a second year of manuscript (N = 29, M = 7 years 8 months, 16 girls) or introduction to cursive (joined) instruction in second grade (N = 24, M = 8 years 0 months, 11 girls) embedded in the Slingerland literacy program. ANCOVA with automatic alphabet writing as covariate showed that those who received a second year of manuscript handwriting instruction improved more on sustained handwriting over 30, 60, and 90 seconds than those who had had only one year of manuscript instruction; both groups improved in spelling and composing from the second to ninth month of second grade. Results are discussed in reference to mastering one handwriting format before introducing another format at a higher grade level and always embedding handwriting instruction in writing and reading instruction aimed at all levels of language. PMID:28190930
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing
Xian, Xuefeng; Cui, Zhiming
2017-01-01
Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost. PMID:28588611
Update on Automated Classification of Interplanetary Dust Particles
NASA Technical Reports Server (NTRS)
Maroger, I.; Lasue, J.; Zolensky, M.
2018-01-01
Every year, the Earth accretes about 40,000 tons of extraterrestrial material less than 1 mm in size on its surface. These dust particles originate from active comets, from impacts between asteroids and may also be coming from interstellar space for the very small particles. Since 1981, NASA Jonhson Space Center (JSC) has been systematically collecting the dust from Earth's strastosphere by airborne collectors and gathered them into "Cosmic Dust Catalogs". In those catalogs, a preliminary analysis of the dust particles based on SEM images, some geological characteristics and X-ray energy-dispersive spectrometry (EDS) composition is compiled. Based on those properties, the IDPs are classified into four main groups: C (Cosmic), TCN (Natural Terrestrial Contaminant), TCA (Artificial Terrestrial Contaminant) and AOS (Aluminium Oxide Sphere). Nevertheless, 20% of those particles remain ambiguously classified. Lasue et al. presented a methodology to help automatically classify the particles published in the catalog 15 based on their EDS spectra and nonlinear multivariate projections (as shown in Fig. 1). This work allowed to relabel 155 particles out of the 467 particles in catalog 15 and reclassify some contaminants as potential cosmic dusts. Further analyses of three such particles indicated their probable cosmic origin. The current work aims to bring complementary information to the automatic classification of IDPs to improve identification criteria.
Wallner, Jürgen; Hochegger, Kerstin; Chen, Xiaojun; Mischak, Irene; Reinbacher, Knut; Pau, Mauro; Zrnc, Tomislav; Schwenzer-Zimmerer, Katja; Zemann, Wolfgang; Schmalstieg, Dieter; Egger, Jan
2018-01-01
Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p<0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the two groups. Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.
A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)
Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon
1990-01-01
Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...
Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George
2017-06-26
We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.
Freiman, Moti; Nickisch, Hannes; Prevrhal, Sven; Schmitt, Holger; Vembar, Mani; Maurovich-Horvat, Pál; Donnelly, Patrick; Goshen, Liran
2017-03-01
The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery stenosis from coronary computed tomography angiography (CCTA). Two sets of data were used in our work: (a) multivendor CCTA datasets of 18 subjects from the MICCAI 2012 challenge with automatically generated centerlines and 3 reference segmentations of 78 coronary segments and (b) additional CCTA datasets of 97 subjects with 132 coronary lesions that had invasive reference standard FFR measurements. We extracted the coronary artery centerlines for the 97 datasets by an automated software program followed by manual correction if required. An automatic machine-learning-based algorithm segmented the coronary tree with and without accounting for the PVE. We obtained CCTA-based FFR measurements using a flow simulation in the coronary trees that were generated by the automatic algorithm with and without accounting for PVE. We assessed the potential added value of PVE integration as a part of the automatic coronary lumen segmentation algorithm by means of segmentation accuracy using the MICCAI 2012 challenge framework and by means of flow simulation overall accuracy, sensitivity, specificity, negative and positive predictive values, and the receiver operated characteristic (ROC) area under the curve. We also evaluated the potential benefit of accounting for PVE in automatic segmentation for flow simulation for lesions that were diagnosed as obstructive based on CCTA which could have indicated a need for an invasive exam and revascularization. Our segmentation algorithm improves the maximal surface distance error by ~39% compared to previously published method on the 18 datasets from the MICCAI 2012 challenge with comparable Dice and mean surface distance. Results with and without accounting for PVE were comparable. In contrast, integrating PVE analysis into an automatic coronary lumen segmentation algorithm improved the flow simulation specificity from 0.6 to 0.68 with the same sensitivity of 0.83. Also, accounting for PVE improved the area under the ROC curve for detecting hemodynamically significant CAD from 0.76 to 0.8 compared to automatic segmentation without PVE analysis with invasive FFR threshold of 0.8 as the reference standard. Accounting for PVE in flow simulation to support the detection of hemodynamic significant disease in CCTA-based obstructive lesions improved specificity from 0.51 to 0.73 with same sensitivity of 0.83 and the area under the curve from 0.69 to 0.79. The improvement in the AUC was statistically significant (N = 76, Delong's test, P = 0.012). Accounting for the partial volume effects in automatic coronary lumen segmentation algorithms has the potential to improve the accuracy of CCTA-based hemodynamic assessment of coronary artery lesions. © 2017 American Association of Physicists in Medicine.
Reliable clarity automatic-evaluation method for optical remote sensing images
NASA Astrophysics Data System (ADS)
Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen
2015-10-01
Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.
NASA Astrophysics Data System (ADS)
Hehl, Friedrich W.; McCrea, J. Dermott
1986-03-01
Automatic conservation of energy-momentum and angular momentum is guaranteed in a gravitational theory if, via the field equations, the conservation laws for the material currents are reduced to the contracted Bianchi identities. We first execute an irreducible decomposition of the Bianchi identities in a Riemann-Cartan space-time. Then, starting from a Riemannian space-time with or without torsion, we determine those gravitational theories which have automatic conservation: general relativity and the Einstein-Cartan-Sciama-Kibble theory, both with cosmological constant, and the nonviable pseudoscalar model. The Poincaré gauge theory of gravity, like gauge theories of internal groups, has no automatic conservation in the sense defined above. This does not lead to any difficulties in principle. Analogies to 3-dimensional continuum mechanics are stressed throughout the article.
Knowledge Base for Automatic Generation of Online IMS LD Compliant Course Structures
ERIC Educational Resources Information Center
Pacurar, Ecaterina Giacomini; Trigano, Philippe; Alupoaie, Sorin
2006-01-01
Our article presents a pedagogical scenarios-based web application that allows the automatic generation and development of pedagogical websites. These pedagogical scenarios are represented in the IMS Learning Design standard. Our application is a web portal helping teachers to dynamically generate web course structures, to edit pedagogical content…
Automatic Generation of Customized, Model Based Information Systems for Operations Management.
The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)
Automatic Online Lecture Highlighting Based on Multimedia Analysis
ERIC Educational Resources Information Center
Che, Xiaoyin; Yang, Haojin; Meinel, Christoph
2018-01-01
Textbook highlighting is widely considered to be beneficial for students. In this paper, we propose a comprehensive solution to highlight the online lecture videos in both sentence- and segment-level, just as is done with paper books. The solution is based on automatic analysis of multimedia lecture materials, such as speeches, transcripts, and…
Evaluating Automatic Speech Recognition-Based Language Learning Systems: A Case Study
ERIC Educational Resources Information Center
van Doremalen, Joost; Boves, Lou; Colpaert, Jozef; Cucchiarini, Catia; Strik, Helmer
2016-01-01
The purpose of this research was to evaluate a prototype of an automatic speech recognition (ASR)-based language learning system that provides feedback on different aspects of speaking performance (pronunciation, morphology and syntax) to students of Dutch as a second language. We carried out usability reviews, expert reviews and user tests to…
NASA Technical Reports Server (NTRS)
Chambers, A. B.; Blackaby, J. R.; Miles, J. B.
1973-01-01
Experimental results for three subjects walking on a treadmill at exercise rates of up to 590 watts showed that thermal comfort could be maintained in a liquid cooled garment by using an automatic temperature controller based on sweat rate. The addition of head- and neck-cooling to an Apollo type liquid cooled garment increased its effectiveness and resulted in greater subjective comfort. The biothermal model of man developed in the second portion of the study utilized heat rates and exchange coefficients based on the experimental data, and included the cooling provisions of a liquid-cooled garment with automatic temperature control based on sweat rate. Simulation results were good approximations of the experimental results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiong, Z; Vijayan, S; Oines, A
Purpose: To compare PCXMC and EGSnrc calculated organ and effective radiation doses from cone-beam computed tomography (CBCT) and interventional fluoroscopically-guided procedures using automatic exposure-event grouping. Methods: For CBCT, we used PCXMC20Rotation.exe to automatically calculate the doses and compared the results to those calculated using EGSnrc with the Zubal patient phantom. For interventional procedures, we use the dose tracking system (DTS) which we previously developed to produce a log file of all geometry and exposure parameters for every x-ray pulse during a procedure, and the data in the log file is input into PCXMC and EGSnrc for dose calculation. A MATLABmore » program reads data from the log files and groups similar exposures to reduce calculation time. The definition files are then automatically generated in the format used by PCXMC and EGSnrc. Processing is done at the end of the procedure after all exposures are completed. Results: For the Toshiba Infinix CBCT LCI-Middle-Abdominal protocol, most organ doses calculated with PCXMC20Rotation closely matched those calculated with EGSnrc. The effective doses were 33.77 mSv with PCXMC20Rotation and 32.46 mSv with EGSnrc. For a simulated interventional cardiac procedure, similar close agreement in organ dose was obtained between the two codes; the effective doses were 12.02 mSv with PCXMC and 11.35 mSv with EGSnrc. The calculations can be completed on a PC without manual intervention in less than 15 minutes with PCXMC and in about 10 hours with EGSnrc, depending on the level of data grouping and accuracy desired. Conclusion: Effective dose and most organ doses in CBCT and interventional radiology calculated by PCXMC closely match those calculated by EGSnrc. Data grouping, which can be done automatically, makes the calculation time with PCXMC on a standard PC acceptable. This capability expands the dose information that can be provided by the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less
[An automatic system controlled by microcontroller for carotid sinus perfusion].
Yi, X L; Wang, M Y; Fan, Z Z; He, R R
2001-08-01
To establish a new method for controlling automatically the carotid perfusion pressure. A cheap practical automatic perfusion unit based on AT89C2051 micro controller was designed. The unit, LDB-M perfusion pump and the carotid sinus of an animal constituted an automatic perfusion system. This system was able to provide ramp and stepwise updown perfusion pattern and has been used in the research of baroreflex. It can insure the precision and reproducibility of perfusion pressure curve, and improve the technical level in corresponding medical field.
Understanding adolescent response to a technology-based depression prevention program.
Gladstone, Tracy; Marko-Holguin, Monika; Henry, Jordan; Fogel, Joshua; Diehl, Anne; Van Voorhees, Benjamin W
2014-01-01
Guided by the Behavioral Vaccine Theory of prevention, this study uses a no-control group design to examine intervention variables that predict favorable changes in depressive symptoms at 6- to 8-week follow-up in at-risk adolescents who participated in a primary care, Internet-based prevention program. Participants included 83 adolescents from primary care settings ages 14 to 21 (M = 17.5, SD = 2.04), 56.2% female, with 41% non-White. Participants completed self-report measures, met with a physician, and then completed a 14-module Internet intervention targeting the prevention of depression. Linear regression models indicated that several intervention factors (duration on website in days, the strength of the relationship with the physician, perceptions of ease of use, and the perceived relevance of the material presented) were significantly associated with greater reductions in depressive symptoms from baseline to follow-up. Automatic negative thoughts significantly mediated the relation between change in depressive symptoms scores and both duration of use and physician relationship. Several intervention variables predicted favorable changes in depressive symptom scores among adolescents who participated in an Internet-based prevention program, and the strength of two of these variables was mediated by automatic negative thoughts. These findings support the importance of cognitive factors in preventing adolescent depression and suggest that modifiable aspects of technology-based intervention experience and relationships should be considered in optimizing intervention design.
Automatic construction of a recurrent neural network based classifier for vehicle passage detection
NASA Astrophysics Data System (ADS)
Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur
2017-03-01
Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.
Automatic Implementation of Ttethernet-Based Time-Triggered Avionics Applications
NASA Astrophysics Data System (ADS)
Gorcitz, Raul Adrian; Carle, Thomas; Lesens, David; Monchaux, David; Potop-Butucaruy, Dumitru; Sorel, Yves
2015-09-01
The design of safety-critical embedded systems such as those used in avionics still involves largely manual phases. But in avionics the definition of standard interfaces embodied in standards such as ARINC 653 or TTEthernet should allow the definition of fully automatic code generation flows that reduce the costs while improving the quality of the generated code, much like compilers have done when replacing manual assembly coding. In this paper, we briefly present such a fully automatic implementation tool, called Lopht, for ARINC653-based time-triggered systems, and then explain how it is currently extended to include support for TTEthernet networks.
Automated processing of shoeprint images based on the Fourier transform for use in forensic science.
de Chazal, Philip; Flynn, John; Reilly, Richard B
2005-03-01
The development of a system for automatically sorting a database of shoeprint images based on the outsole pattern in response to a reference shoeprint image is presented. The database images are sorted so that those from the same pattern group as the reference shoeprint are likely to be at the start of the list. A database of 476 complete shoeprint images belonging to 140 pattern groups was established with each group containing two or more examples. A panel of human observers performed the grouping of the images into pattern categories. Tests of the system using the database showed that the first-ranked database image belongs to the same pattern category as the reference image 65 percent of the time and that a correct match appears within the first 5 percent of the sorted images 87 percent of the time. The system has translational and rotational invariance so that the spatial positioning of the reference shoeprint images does not have to correspond with the spatial positioning of the shoeprint images of the database. The performance of the system for matching partial-prints was also determined.
Automatic 3D segmentation of spinal cord MRI using propagated deformable models
NASA Astrophysics Data System (ADS)
De Leener, B.; Cohen-Adad, J.; Kadoury, S.
2014-03-01
Spinal cord diseases or injuries can cause dysfunction of the sensory and locomotor systems. Segmentation of the spinal cord provides measures of atrophy and allows group analysis of multi-parametric MRI via inter-subject registration to a template. All these measures were shown to improve diagnostic and surgical intervention. We developed a framework to automatically segment the spinal cord on T2-weighted MR images, based on the propagation of a deformable model. The algorithm is divided into three parts: first, an initialization step detects the spinal cord position and orientation by using the elliptical Hough transform on multiple adjacent axial slices to produce an initial tubular mesh. Second, a low-resolution deformable model is iteratively propagated along the spinal cord. To deal with highly variable contrast levels between the spinal cord and the cerebrospinal fluid, the deformation is coupled with a contrast adaptation at each iteration. Third, a refinement process and a global deformation are applied on the low-resolution mesh to provide an accurate segmentation of the spinal cord. Our method was evaluated against a semi-automatic edge-based snake method implemented in ITK-SNAP (with heavy manual adjustment) by computing the 3D Dice coefficient, mean and maximum distance errors. Accuracy and robustness were assessed from 8 healthy subjects. Each subject had two volumes: one at the cervical and one at the thoracolumbar region. Results show a precision of 0.30 +/- 0.05 mm (mean absolute distance error) in the cervical region and 0.27 +/- 0.06 mm in the thoracolumbar region. The 3D Dice coefficient was of 0.93 for both regions.
Hirose, Tomoaki; Igami, Tsuyoshi; Koga, Kusuto; Hayashi, Yuichiro; Ebata, Tomoki; Yokoyama, Yukihiro; Sugawara, Gen; Mizuno, Takashi; Yamaguchi, Junpei; Mori, Kensaku; Nagino, Masato
2017-03-01
Fusion angiography using reconstructed multidetector-row computed tomography (MDCT) images, and cholangiography using reconstructed images from MDCT with a cholangiographic agent include an anatomical gap due to the different periods of MDCT scanning. To conquer such gaps, we attempted to develop a cholangiography procedure that automatically reconstructs a cholangiogram from portal-phase MDCT images. The automatically produced cholangiography procedure utilized an original software program that was developed by the Graduate School of Information Science, Nagoya University. This program structured 5 candidate biliary tracts, and automatically selected one as the candidate for cholangiography. The clinical value of the automatically produced cholangiography procedure was estimated based on a comparison with manually produced cholangiography. Automatically produced cholangiograms were reconstructed for 20 patients who underwent MDCT scanning before biliary drainage for distal biliary obstruction. The procedure showed the ability to extract the 5 main biliary branches and the 21 subsegmental biliary branches in 55 and 25 % of the cases, respectively. The extent of aberrant connections and aberrant extractions outside the biliary tract was acceptable. Among all of the cholangiograms, 5 were clinically applied with no correction, 8 were applied with modest improvements, and 3 produced a correct cholangiography before automatic selection. Although our procedure requires further improvement based on the analysis of additional patient data, it may represent an alternative to direct cholangiography in the future.
Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf
2018-05-01
Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.
Kim, Jae-Jin; Kim, Dae-Jin; Kim, Tae-Gyun; Seok, Jeong-Ho; Chun, Ji Won; Oh, Maeng-Keun; Park, Hae-Jeong
2007-12-01
The thalamus, which consists of multiple subnuclei, has been of particular interest in the study of schizophrenia. This study aimed to identify abnormalities in the connectivity-based subregions of the thalamus in patients with schizophrenia. Thalamic volume was measured by a manual tracing on superimposed images of T1-weighted and diffusion tensor images in 30 patients with schizophrenia and 22 normal volunteers. Cortical regional volumes automatically measured by a surface-based approach and thalamic subregional volumes measured by a connectivity-based technique were compared between the two groups and their correlations between the connected regions were calculated in each group. Volume reduction was observed in the bilateral orbitofrontal cortices and the left cingulate gyrus on the cortical side, whereas in subregions connected to the right orbitofrontal cortex and bilateral parietal cortices on the thalamic side. Significant volumetric correlations were identified between the right dorsal prefrontal cortex and its related thalamic subregion and between the left parietal cortex and its related thalamic subregion only in the normal group. Our results suggest that patients with schizophrenia have a structural deficit in the corticothalamic systems, especially in the orbitofrontal-thalamic system. Our findings may present evidence of corticothalamic connection problems in schizophrenia.
A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.
Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa
2015-12-01
Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.
Menzel, Claudia; Kovács, Gyula; Amado, Catarina; Hayn-Leichsenring, Gregor U; Redies, Christoph
2018-05-06
In complex abstract art, image composition (i.e., the artist's deliberate arrangement of pictorial elements) is an important aesthetic feature. We investigated whether the human brain detects image composition in abstract artworks automatically (i.e., independently of the experimental task). To this aim, we studied whether a group of 20 original artworks elicited a visual mismatch negativity when contrasted with a group of 20 images that were composed of the same pictorial elements as the originals, but in shuffled arrangements, which destroy artistic composition. We used a passive oddball paradigm with parallel electroencephalogram recordings to investigate the detection of image type-specific properties. We observed significant deviant-standard differences for the shuffled and original images, respectively. Furthermore, for both types of images, differences in amplitudes correlated with the behavioral ratings of the images. In conclusion, we show that the human brain can detect composition-related image properties in visual artworks in an automatic fashion. Copyright © 2018 Elsevier B.V. All rights reserved.
Wittekind, Charlotte E; Behmer, Friederike; Muhtz, Christoph; Fritzsche, Anja; Moritz, Steffen; Jelinek, Lena
2015-08-30
Avoidance of trauma-related stimuli is a key feature of Posttraumatic Stress Disorder (PTSD). However, avoidance has almost exclusively been investigated with explicit measures targeting more strategic aspects of behavior. The aim of the present study was to examine automatic avoidance in older individuals displaced as children at the end of World War II with (n=22) and without PTSD (n=26) and in non-traumatized control participants (n=23) with an Approach-Avoidance Task (AAT). Participants were instructed to respond to the color (gray, brown) of trauma-related, neutral, and control pictures by pushing or pulling a joystick. Groups did not differ significantly as to their behavioral tendencies towards trauma-related pictures. Thus, there was no evidence for automatic avoidance in individuals with PTSD. However, high vigilance was associated with stronger implicit avoidance towards trauma-related pictures in the PTSD group. Several explanations for the non-significant results as well as implications and limitations of the present findings are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Reinecke, Andrea; Becker, Eni S; Rinck, Mike
2009-12-01
Following cognitive models of anxiety, biases occur if threat processing is automatic versus strategic. Therefore, most of these models predict attentional bias, but not explicit memory bias. We suggest dividing memory into the highly automatic working memory (WM) component versus long-term memory when investigating bias in anxiety. WM for threat has rarely been investigated although its main function is stimulus monitoring, particularly important in anxiety. We investigated WM for spiders in spider fearfuls (SFs) versus non-anxious controls (NACs). In Experiment 1 (23 SFs/24 NACs), we replicated an earlier WM study, reducing strategic processing options. This led to stronger group differences and, thus, clearer WM threat biases. There were no group differences in Experiment 2 (18 SFs/19 NACs), using snakes instead of spiders to test whether WM biases are material-specific. This article supports cognitive models of anxiety in that biases are more likely to occur when reducing strategic processing. However, it contradicts the assumption that explicit memory biases are not characteristic of anxiety.
Donges, Uta-Susan; Dukalski, Bibiana; Kersting, Anette; Suslow, Thomas
2015-01-01
Instability of affects and interpersonal relations are important features of borderline personality disorder (BPD). Interpersonal problems of individuals suffering from BPD might develop based on abnormalities in the processing of facial affects and high sensitivity to negative affective expressions. The aims of the present study were to examine automatic evaluative shifts and latencies as a function of masked facial affects in patients with BPD compared to healthy individuals. As BPD comorbidity rates for mental and personality disorders are high, we investigated also the relationships of affective processing characteristics with specific borderline symptoms and comorbidity. Twenty-nine women with BPD and 38 healthy women participated in the study. The majority of patients suffered from additional Axis I disorders and/or additional personality disorders. In the priming experiment, angry, happy, neutral, or no facial expression was briefly presented (for 33 ms) and masked by neutral faces that had to be evaluated. Evaluative decisions and response latencies were registered. Borderline-typical symptomatology was assessed with the Borderline Symptom List. In the total sample, valence-congruent evaluative shifts and delays of evaluative decision due to facial affect were observed. No between-group differences were obtained for evaluative decisions and latencies. The presence of comorbid anxiety disorders was found to be positively correlated with evaluative shifting owing to masked happy primes, regardless of baseline-neutral or no facial expression condition. The presence of comorbid depressive disorder, paranoid personality disorder, and symptoms of social isolation and self-aggression were significantly correlated with response delay due to masked angry faces, regardless of baseline. In the present affective priming study, no abnormalities in the automatic recognition and processing of facial affects were observed in BPD patients compared to healthy individuals. The presence of comorbid anxiety disorders could make patients more susceptible to the influence of a happy expression on judgment processes at an automatic processing level. Comorbid depressive disorder, paranoid personality disorder, and symptoms of social isolation and self-aggression may enhance automatic attention allocation to threatening facial expressions in BPD. Increased automatic vigilance for social threat stimuli might contribute to affective instability and interpersonal problems in specific patients with BPD.
Resting-state functional connectivity indexes reading competence in children and adults.
Koyama, Maki S; Di Martino, Adriana; Zuo, Xi-Nian; Kelly, Clare; Mennes, Maarten; Jutagir, Devika R; Castellanos, F Xavier; Milham, Michael P
2011-06-08
Task-based neuroimaging studies face the challenge of developing tasks capable of equivalently probing reading networks across different age groups. Resting-state fMRI, which requires no specific task, circumvents these difficulties. Here, in 25 children (8-14 years) and 25 adults (21-46 years), we examined the extent to which individual differences in reading competence can be related to resting-state functional connectivity (RSFC) of regions implicated in reading. In both age groups, reading standard scores correlated positively with RSFC between the left precentral gyrus and other motor regions, and between Broca's and Wernicke's areas. This suggests that, regardless of age group, stronger coupling among motor regions, as well as between language/speech regions, subserves better reading, presumably reflecting automatized articulation. We also observed divergent RSFC-behavior relationships in children and adults, particularly those anchored in the left fusiform gyrus (FFG) (the visual word form area). In adults, but not children, better reading performance was associated with stronger positive correlations between FFG and phonology-related regions (Broca's area and the left inferior parietal lobule), and with stronger negative relationships between FFG and regions of the "task-negative" default network. These results suggest that both positive RSFC (functional coupling) between reading regions and negative RSFC (functional segregation) between a reading region and default network regions are important for automatized reading, characteristic of adult readers. Together, our task-independent RSFC findings highlight the importance of appreciating developmental changes in the neural correlates of reading competence, and suggest that RSFC may serve to facilitate the identification of reading disorders in different age groups.
Jiang, Zhi-Bo; Ren, Wei-Cong; Shi, Yuan-Yuan; Li, Xing-Xing; Lei, Xuan; Fan, Jia-Hui; Zhang, Cong; Gu, Ren-Jie; Wang, Li-Fei; Xie, Yun-Ying; Hong, Bin
2018-05-18
Sansanmycins (SS), one of several known uridyl peptide antibiotics (UPAs) possessing a unique chemical scaffold, showed a good inhibitory effect on the highly refractory pathogens Pseudomonas aeruginosa and Mycobacterium tuberculosis, especially on the multi-drug resistant M. tuberculosis. This study employed high performance liquid chromatography-mass spectrometry detector (HPLC-MSD) ion trap and LTQ orbitrap tandem mass spectrometry (MS/MS) to explore sansanmycin analogues manually and automatically by re-analysis of the Streptomyces sp. SS fermentation broth. The structure-based manual screening method, based on analysis of the fragmentation pathway of known UPAs and on comparisons of the MS/MS spectra with that of sansanmycin A (SS-A), resulted in identifying twenty sansanmycin analogues, including twelve new structures (1-12). Furthermore, to deeply explore sansanmycin analogues, we utilized a GNPS based molecular networking workflow to re-analyze the HPLC-MS/MS data automatically. As a result, eight more new sansanmycins (13-20) were discovered. Compound 1 was discovered to lose two amino acids of residue 1 (AA 1 ) and (2S, 3S)-N 3 -methyl-2,3-diamino butyric acid (DABA) from the N-terminus, and compounds 6, 11 and 12 were found to contain a 2',3'-dehydrated 4',5'-enamine-3'-deoxyuridyl moiety, which have not been reported before. Interestingly, three trace components with novel 5,6-dihydro-5'-aminouridyl group (16-18) were detected for the first time in the sansanmycin-producing strain. Their structures were primarily determined by detail analysis of the data from MS/MS. Compounds 8 and 10 were further confirmed by nuclear magnetic resonance (NMR) data, which proved the efficiency and accuracy of the method of HPLC-MS/MS for exploration of novel UPAs. Comparing to manual screening, the networking method can provide systematic visualization results. Manual screening and networking method may complement with each other to facilitate the mining of novel UPAs. Copyright © 2018 Elsevier B.V. All rights reserved.
Wolf, M; Miller, L; Donnelly, K
2000-01-01
The most important implication of the double-deficit hypothesis (Wolf & Bowers, in this issue) concerns a new emphasis on fluency and automaticity in intervention for children with developmental reading disabilities. The RAVE-O (Retrieval, Automaticity, Vocabulary Elaboration, Orthography) program is an experimental, fluency-based approach to reading intervention that is designed to accompany a phonological analysis program. In an effort to address multiple possible sources of dysfluency in readers with disabilities, the program involves comprehensive emphases both on fluency in word attack, word identification, and comprehension and on automaticity in underlying componential processes (e.g., phonological, orthographic, semantic, and lexical retrieval skills). The goals, theoretical principles, and applied activities of the RAVE-O curriculum are described with particular stress on facilitating the development of rapid orthographic pattern recognition and on changing children's attitudes toward language.
Castillo, Andrés M; Bernal, Andrés; Patiny, Luc; Wist, Julien
2015-08-01
We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra. Copyright © 2015 John Wiley & Sons, Ltd.
A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)
Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon
1992-01-01
Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...
Hülsheger, Ute R; Lang, Jonas W B; Schewe, Anna F; Zijlstra, Fred R H
2015-03-01
We investigated the relationship between deep acting, automatic regulation and customer tips with 2 different study designs. The first study was a daily diary study using a sample of Dutch waiters and taxi-drivers and assessed the link of employees' daily self-reported levels of deep acting and automatic regulation with the amount of tips provided by customers (N = 166 measurement occasions nested in 34 persons). Whereas deep acting refers to deliberate attempts to modify felt emotions and involves conscious effort, automatic regulation refers to automated emotion regulatory processes that result in the natural experience of desired emotions and do not involve deliberate control and effort. Multilevel analyses revealed that both types of emotion regulation were positively associated with customer tips. The second study was an experimental field study using a sample of German hairdressers (N = 41). Emotion regulation in terms of both deep acting and automatic regulation was manipulated using a brief self-training intervention and daily instructions to use cognitive change and attentional deployment. Results revealed that participants in the intervention group received significantly more tips than participants in the control group. PsycINFO Database Record (c) 2015 APA, all rights reserved.
Automatic classification of atypical lymphoid B cells using digital blood image processing.
Alférez, S; Merino, A; Mujica, L E; Ruiz, M; Bigorra, L; Rodellar, J
2014-08-01
There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in nonpathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells. We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification. The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively. The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells. © 2013 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Endah, S. N.; Nugraheni, D. M. K.; Adhy, S.; Sutikno
2017-04-01
According to Law No. 32 of 2002 and the Indonesian Broadcasting Commission Regulation No. 02/P/KPI/12/2009 & No. 03/P/KPI/12/2009, stated that broadcast programs should not scold with harsh words, not harass, insult or demean minorities and marginalized groups. However, there are no suitable tools to censor those words automatically. Therefore, researches to develop a system of intelligent software to censor the words automatically are needed. To conduct censor, the system must be able to recognize the words in question. This research proposes the classification of speech divide into two classes using Support Vector Machine (SVM), first class is set of rude words and the second class is set of properly words. The speech pitch values as an input in SVM, it used for the development of the system for the Indonesian rude swear word. The results of the experiment show that SVM is good for this system.
Automatic Traffic Advisory and Resolution Service (ATARS) Multi-Site Algorithms. Revision 1,
1980-10-01
Summary Concept Description The Automatic Traffic Advisory and Resolution Service is a ground based collision avoidance system to be implemented in the...capability. A ground based computer processes the data and continuously provides proximity warning information and, when necessary, resolution advisories to...of ground- based air traffic control which provides proximity warning and separation services to uncontrolled aircraft in a given region of airspace. it
Automatic non-proliferative diabetic retinopathy screening system based on color fundus image.
Xiao, Zhitao; Zhang, Xinpeng; Geng, Lei; Zhang, Fang; Wu, Jun; Tong, Jun; Ogunbona, Philip O; Shan, Chunyan
2017-10-26
Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients. This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images. Firstly, the fundus structures, including blood vessels, optic disc and macula, are extracted and located, respectively. In particular, a new optic disc localization method using parabolic fitting is proposed based on the physiological structure characteristics of optic disc and blood vessels. Then, early lesions, such as microaneurysms, hemorrhages and hard exudates, are detected based on their respective characteristics. An equivalent optical model simulating human eyes is designed based on the anatomical structure of retina. Main structures and early lesions are reconstructed in the 3D space for better visualization. Finally, the severity of each image is evaluated based on the international criteria of diabetic retinopathy. The system has been tested on public databases and images from hospitals. Experimental results demonstrate that the proposed system achieves high accuracy for main structures and early lesions detection. The results of severity classification for non-proliferative diabetic retinopathy are also accurate and suitable. Our system can assist ophthalmologists for clinical diagnosis, automatic screening and course progression of patients.
Automatic Event Detection in Search for Inter-Moss Loops in IRIS Si IV Slit-Jaw Images
NASA Technical Reports Server (NTRS)
Fayock, Brian; Winebarger, Amy R.; De Pontieu, Bart
2015-01-01
The high-resolution capabilities of the Interface Region Imaging Spectrometer (IRIS) mission have allowed the exploration of the finer details of the solar magnetic structure from the chromosphere to the lower corona that have previously been unresolved. Of particular interest to us are the relatively short-lived, low-lying magnetic loops that have foot points in neighboring moss regions. These inter-moss loops have also appeared in several AIA pass bands, which are generally associated with temperatures that are at least an order of magnitude higher than that of the Si IV emission seen in the 1400 angstrom pass band of IRIS. While the emission lines seen in these pass bands can be associated with a range of temperatures, the simultaneous appearance of these loops in IRIS 1400 and AIA 171, 193, and 211 suggest that they are not in ionization equilibrium. To study these structures in detail, we have developed a series of algorithms to automatically detect signal brightening or events on a pixel-by-pixel basis and group them together as structures for each of the above data sets. These algorithms have successfully picked out all activity fitting certain adjustable criteria. The resulting groups of events are then statistically analyzed to determine which characteristics can be used to distinguish the inter-moss loops from all other structures. While a few characteristic histograms reveal that manually selected inter-moss loops lie outside the norm, a combination of several characteristics will need to be used to determine the statistical likelihood that a group of events be categorized automatically as a loop of interest. The goal of this project is to be able to automatically pick out inter-moss loops from an entire data set and calculate the characteristics that have previously been determined manually, such as length, intensity, and lifetime. We will discuss the algorithms, preliminary results, and current progress of automatic characterization.
ERIC Educational Resources Information Center
Dumas, Jean E.
2005-01-01
Disagreements and conflicts in families with disruptive children often reflect rigid patterns of behavior that have become overlearned and automatized with repeated practice. These patterns are mindless: They are performed with little or no awareness and are highly resistant to change. This article introduces a new, mindfulness-based model of…
Automatic three-dimensional measurement of large-scale structure based on vision metrology.
Zhu, Zhaokun; Guan, Banglei; Zhang, Xiaohu; Li, Daokui; Yu, Qifeng
2014-01-01
All relevant key techniques involved in photogrammetric vision metrology for fully automatic 3D measurement of large-scale structure are studied. A new kind of coded target consisting of circular retroreflective discs is designed, and corresponding detection and recognition algorithms based on blob detection and clustering are presented. Then a three-stage strategy starting with view clustering is proposed to achieve automatic network orientation. As for matching of noncoded targets, the concept of matching path is proposed, and matches for each noncoded target are found by determination of the optimal matching path, based on a novel voting strategy, among all possible ones. Experiments on a fixed keel of airship have been conducted to verify the effectiveness and measuring accuracy of the proposed methods.
Automatic calibration method for plenoptic camera
NASA Astrophysics Data System (ADS)
Luan, Yinsen; He, Xing; Xu, Bing; Yang, Ping; Tang, Guomao
2016-04-01
An automatic calibration method is proposed for a microlens-based plenoptic camera. First, all microlens images on the white image are searched and recognized automatically based on digital morphology. Then, the center points of microlens images are rearranged according to their relative position relationships. Consequently, the microlens images are located, i.e., the plenoptic camera is calibrated without the prior knowledge of camera parameters. Furthermore, this method is appropriate for all types of microlens-based plenoptic cameras, even the multifocus plenoptic camera, the plenoptic camera with arbitrarily arranged microlenses, or the plenoptic camera with different sizes of microlenses. Finally, we verify our method by the raw data of Lytro. The experiments show that our method has higher intelligence than the methods published before.
Automatic detection of sleep macrostructure based on a sensorized T-shirt.
Bianchi, Anna M; Mendez, Martin O
2010-01-01
In the present work we apply a fully automatic procedure to the analysis of signal coming from a sensorized T-shit, worn during the night, for sleep evaluation. The goodness and reliability of the signals recorded trough the T-shirt was previously tested, while the employed algorithms for feature extraction and sleep classification were previously developed on standard ECG recordings and the obtained classification was compared to the standard clinical practice based on polysomnography (PSG). In the present work we combined T-shirt recordings and automatic classification and could obtain reliable sleep profiles, i.e. the sleep classification in WAKE, REM (rapid eye movement) and NREM stages, based on heart rate variability (HRV), respiration and movement signals.
NASA Astrophysics Data System (ADS)
Qin, Xulei; Cong, Zhibin; Fei, Baowei
2013-11-01
An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 ± 1.7% and 87.3 ± 1.9%, the absolute distances were 2.0 ± 0.42 mm and 1.79 ± 0.45 mm, and the Hausdorff distances were 6.86 ± 1.71 mm and 7.02 ± 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.
Expert systems identify fossils and manage large paleontological databases
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beightol, D.S.; Conrad, M.A.
EXPAL is a computer program permitting creation and maintenance of comprehensive databases in marine paleontology. It is designed to assist specialists and non-specialists. EXPAL includes a powerful expert system based on the morphological descriptors specific to a given group of fossils. The expert system may be used, for example, to describe and automatically identify an unknown specimen. EXPAL was first applied to Dasycladales (Calcareous green algae). Projects are under way for corresponding expert systems and databases on planktonic foraminifers and calpionellids. EXPAL runs on an IBM XT or compatible microcomputer.
NASA Technical Reports Server (NTRS)
Nalepka, R. F. (Principal Investigator); Kauth, R. J.; Thomas, G. S.
1976-01-01
The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.
Automatic morphometry in Alzheimer's disease and mild cognitive impairment☆☆☆
Heckemann, Rolf A.; Keihaninejad, Shiva; Aljabar, Paul; Gray, Katherine R.; Nielsen, Casper; Rueckert, Daniel; Hajnal, Joseph V.; Hammers, Alexander
2011-01-01
This paper presents a novel, publicly available repository of anatomically segmented brain images of healthy subjects as well as patients with mild cognitive impairment and Alzheimer's disease. The underlying magnetic resonance images have been obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. T1-weighted screening and baseline images (1.5 T and 3 T) have been processed with the multi-atlas based MAPER procedure, resulting in labels for 83 regions covering the whole brain in 816 subjects. Selected segmentations were subjected to visual assessment. The segmentations are self-consistent, as evidenced by strong agreement between segmentations of paired images acquired at different field strengths (Jaccard coefficient: 0.802 ± 0.0146). Morphometric comparisons between diagnostic groups (normal; stable mild cognitive impairment; mild cognitive impairment with progression to Alzheimer's disease; Alzheimer's disease) showed highly significant group differences for individual regions, the majority of which were located in the temporal lobe. Additionally, significant effects were seen in the parietal lobe. Increased left/right asymmetry was found in posterior cortical regions. An automatically derived white-matter hypointensities index was found to be a suitable means of quantifying white-matter disease. This repository of segmentations is a potentially valuable resource to researchers working with ADNI data. PMID:21397703
A hypothetical neurological association between dehumanization and human rights abuses
Murrow, Gail B.; Murrow, Richard
2015-01-01
Dehumanization is anecdotally and historically associated with reduced empathy for the pain of dehumanized individuals and groups and with psychological and legal denial of their human rights and extreme violence against them. We hypothesize that ‘empathy’ for the pain and suffering of dehumanized social groups is automatically reduced because, as the research we review suggests, an individual's neural mechanisms of pain empathy best respond to (or produce empathy for) the pain of people whom the individual automatically or implicitly associates with her or his own species. This theory has implications for the philosophical conception of ‘human’ and of ‘legal personhood’ in human rights jurisprudence. It further has implications for First Amendment free speech jurisprudence, including the doctrine of ‘corporate personhood’ and consideration of the potential harm caused by dehumanizing hate speech. We suggest that the new, social neuroscience of empathy provides evidence that both the vagaries of the legal definition or legal fiction of ‘personhood’ and hate speech that explicitly and implicitly dehumanizes may (in their respective capacities to artificially humanize or dehumanize) manipulate the neural mechanisms of pain empathy in ways that could pose more of a true threat to human rights and rights-based democracy than previously appreciated. PMID:27774198
Automatic blood vessel based-liver segmentation using the portal phase abdominal CT
NASA Astrophysics Data System (ADS)
Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen
2018-02-01
Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.
ASA24 enables multiple automatically coded self-administered 24-hour recalls and food records
A freely available web-based tool for epidemiologic, interventional, behavioral, or clinical research from NCI that enables multiple automatically coded self-administered 24-hour recalls and food records.
Pal, Jayanta Kumar; Ray, Shubhra Sankar; Pal, Sankar K
2017-10-01
MicroRNAs (miRNA) are one of the important regulators of cell division and also responsible for cancer development. Among the discovered miRNAs, not all are important for cancer detection. In this regard a fuzzy mutual information (FMI) based grouping and miRNA selection method (FMIGS) is developed to identify the miRNAs responsible for a particular cancer. First, the miRNAs are ranked and divided into several groups. Then the most important group is selected among the generated groups. Both the steps viz., ranking of miRNAs and selection of the most relevant group of miRNAs, are performed using FMI. Here the number of groups is automatically determined by the grouping method. After the selection process, redundant miRNAs are removed from the selected set of miRNAs as per user's necessity. In a part of the investigation we proposed a FMI based particle swarm optimization (PSO) method for selecting relevant miRNAs, where FMI is used as a fitness function to determine the fitness of the particles. The effectiveness of FMIGS and FMI based PSO is tested on five data sets and their efficiency in selecting relevant miRNAs are demonstrated. The superior performance of FMIGS to some existing methods are established and the biological significance of the selected miRNAs is observed by the findings of the biological investigation and publicly available pathway analysis tools. The source code related to our investigation is available at http://www.jayanta.droppages.com/FMIGS.html. Copyright © 2017 Elsevier Ltd. All rights reserved.
Gambacorta, Maria A; Boldrini, Luca; Valentini, Chiara; Dinapoli, Nicola; Mattiucci, Gian C; Chiloiro, Giuditta; Pasini, Danilo; Manfrida, Stefania; Caria, Nicola; Minsky, Bruce D; Valentini, Vincenzo
2016-07-05
To validate autocontouring software (AS) in a clinical practice including a two steps delineation quality assurance (QA) procedure.The existing delineation agreement among experts for rectal cancer and the overlap and time criteria that have to be verified to allow the use of AS were defined.Median Dice Similarity Coefficient (MDSC), Mean slicewise Hausdorff Distances (MSHD) and Total-Time saving (TT) were analyzed.Two expert Radiation Oncologists reviewed CT-scans of 44 patients and agreed the reference-CTV: the first 14 consecutive cases were used to populate the software Atlas and 30 were used as Test.Each expert performed a manual (group A) and an automatic delineation (group B) of 15 Test patients.The delineations were compared with the reference contours.The overlap between the manual and automatic delineations with MDSC and MSHD and the TT were analyzed.Three acceptance criteria were set: MDSC ≥ 0.75, MSHD ≤1mm and TT sparing ≥ 50%.At least 2 criteria had to be met, one of which had to be TT saving, to validate the system.The MDSC was 0.75, MSHD 2.00 mm and the TT saving 55.5% between group A and group B. MDSC among experts was 0.84.Autosegmentation systems in rectal cancer partially met acceptability criteria with the present version.
Beck, Eric N; Intzandt, Brittany N; Almeida, Quincy J
2018-01-01
It may be possible to use attention-based exercise to decrease demands associated with walking in Parkinson's disease (PD), and thus improve dual task walking ability. For example, an external focus of attention (focusing on the effect of an action on the environment) may recruit automatic control processes degenerated in PD, whereas an internal focus (limb movement) may recruit conscious (nonautomatic) control processes. Thus, we aimed to investigate how externally and internally focused exercise influences dual task walking and symptom severity in PD. Forty-seven participants with PD were randomized to either an Externally (n = 24) or Internally (n = 23) focused group and completed 33 one-hour attention-based exercise sessions over 11 weeks. In addition, 16 participants were part of a control group. Before, after, and 8 weeks following the program (pre/post/washout), gait patterns were measured during single and dual task walking (digit-monitoring task, ie, walking while counting numbers announced by an audio-track), and symptom severity (UPDRS-III) was assessed ON and OFF dopamine replacement. Pairwise comparisons (95% confidence intervals [CIs]) and repeated-measures analyses of variance were conducted. Pre to post: Dual task step time decreased in the external group (Δ = 0.02 seconds, CI 0.01-0.04). Dual task step length (Δ = 2.3 cm, CI 0.86-3.75) and velocity (Δ = 4.5 cm/s, CI 0.59-8.48) decreased (became worse) in the internal group. UPDRS-III scores (ON and OFF) decreased (improved) in only the External group. Pre to washout: Dual task step time ( P = .005) and percentage in double support ( P = .014) significantly decreased (improved) in both exercise groups, although only the internal group increased error on the secondary counting task (ie, more errors monitoring numbers). UPDRS-III scores in both exercise groups significantly decreased ( P = .001). Since dual task walking improvements were found immediately, and 8 weeks after the cessation of an externally focused exercise program, we conclude that externally focused exercise may improve on functioning of automatic control networks in PD. Internally focused exercise hindered dual tasking ability. Overall, externally focused exercise led to greater rehabilitation benefits in dual tasking and motor symptoms compared with internally focused exercise.
Facial Asymmetry-Based Age Group Estimation: Role in Recognizing Age-Separated Face Images.
Sajid, Muhammad; Taj, Imtiaz Ahmad; Bajwa, Usama Ijaz; Ratyal, Naeem Iqbal
2018-04-23
Face recognition aims to establish the identity of a person based on facial characteristics. On the other hand, age group estimation is the automatic calculation of an individual's age range based on facial features. Recognizing age-separated face images is still a challenging research problem due to complex aging processes involving different types of facial tissues, skin, fat, muscles, and bones. Certain holistic and local facial features are used to recognize age-separated face images. However, most of the existing methods recognize face images without incorporating the knowledge learned from age group estimation. In this paper, we propose an age-assisted face recognition approach to handle aging variations. Inspired by the observation that facial asymmetry is an age-dependent intrinsic facial feature, we first use asymmetric facial dimensions to estimate the age group of a given face image. Deeply learned asymmetric facial features are then extracted for face recognition using a deep convolutional neural network (dCNN). Finally, we integrate the knowledge learned from the age group estimation into the face recognition algorithm using the same dCNN. This integration results in a significant improvement in the overall performance compared to using the face recognition algorithm alone. The experimental results on two large facial aging datasets, the MORPH and FERET sets, show that the proposed age group estimation based on the face recognition approach yields superior performance compared to some existing state-of-the-art methods. © 2018 American Academy of Forensic Sciences.
Mullen, Richard; Faull, Andrea; Jones, Eleri S; Kingston, Kieran
2012-01-01
Previous studies have demonstrated that an external focus can enhance motor learning compared to an internal focus. The benefits of adopting an external focus are attributed to the use of less effortful automatic control processes, while an internal focus relies upon more effort-intensive consciously controlled processes. The aim of this study was to compare the effectiveness of a distal external focus with an internal focus in the acquisition of a simulated driving task and subsequent performance in a competitive condition designed to increase state anxiety. To provide further evidence for the automatic nature of externally controlled movements, the study included heart rate variability (HRV) as an index of mental effort. Sixteen participants completed eight blocks of four laps in either a distal external or internal focus condition, followed by two blocks of four laps in the competitive condition. During acquisition, the performance of both groups improved; however, the distal external focus group outperformed the internal focus group. The poorer performance of the internal focus group was accompanied by a larger reduction in HRV, indicating a greater investment of mental effort. In the competition condition, state anxiety increased, and for both groups, performance improved as a function of the increased anxiety. Increased heart rate and self-reported mental effort accompanied the performance improvement. The distal external focus group also outperformed the internal focus group across both neutral and competitive conditions and this more effective performance was again associated with lower levels of HRV. Overall, the results offer support for the suggestion that an external focus promotes a more automatic mode of functioning. In the competitive condition, both foci enhanced performance and while the improved performance may have been achieved at the expense of greater compensatory mental effort, this was not reflected in HRV scores.
Social Networks and Welfare in Future Animal Management.
Koene, Paul; Ipema, Bert
2014-03-17
It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.
A Modular Hierarchical Approach to 3D Electron Microscopy Image Segmentation
Liu, Ting; Jones, Cory; Seyedhosseini, Mojtaba; Tasdizen, Tolga
2014-01-01
The study of neural circuit reconstruction, i.e., connectomics, is a challenging problem in neuroscience. Automated and semi-automated electron microscopy (EM) image analysis can be tremendously helpful for connectomics research. In this paper, we propose a fully automatic approach for intra-section segmentation and inter-section reconstruction of neurons using EM images. A hierarchical merge tree structure is built to represent multiple region hypotheses and supervised classification techniques are used to evaluate their potentials, based on which we resolve the merge tree with consistency constraints to acquire final intra-section segmentation. Then, we use a supervised learning based linking procedure for the inter-section neuron reconstruction. Also, we develop a semi-automatic method that utilizes the intermediate outputs of our automatic algorithm and achieves intra-segmentation with minimal user intervention. The experimental results show that our automatic method can achieve close-to-human intra-segmentation accuracy and state-of-the-art inter-section reconstruction accuracy. We also show that our semi-automatic method can further improve the intra-segmentation accuracy. PMID:24491638
García-Betances, Rebeca I; Huerta, Mónica K
2012-01-01
A comparative review is presented of available technologies suitable for automatic reading of patient identification bracelet tags. Existing technologies' backgrounds, characteristics, advantages and disadvantages, are described in relation to their possible use by public health care centers with budgetary limitations. A comparative assessment is presented of suitable automatic identification systems based on graphic codes, both one- (1D) and two-dimensional (2D), printed on labels, as well as those based on radio frequency identification (RFID) tags. The analysis looks at the tradeoffs of these technologies to provide guidance to hospital administrator looking to deploy patient identification technology. The results suggest that affordable automatic patient identification systems can be easily and inexpensively implemented using 2D code printed on low cost bracelet labels, which can then be read and automatically decoded by ordinary mobile smart phones. Because of mobile smart phones' present versatility and ubiquity, the implantation and operation of 2D code, and especially Quick Response® (QR) Code, technology emerges as a very attractive alternative to automate the patients' identification processes in low-budget situations.
García-Betances, Rebeca I.; Huerta, Mónica K.
2012-01-01
A comparative review is presented of available technologies suitable for automatic reading of patient identification bracelet tags. Existing technologies’ backgrounds, characteristics, advantages and disadvantages, are described in relation to their possible use by public health care centers with budgetary limitations. A comparative assessment is presented of suitable automatic identification systems based on graphic codes, both one- (1D) and two-dimensional (2D), printed on labels, as well as those based on radio frequency identification (RFID) tags. The analysis looks at the tradeoffs of these technologies to provide guidance to hospital administrator looking to deploy patient identification technology. The results suggest that affordable automatic patient identification systems can be easily and inexpensively implemented using 2D code printed on low cost bracelet labels, which can then be read and automatically decoded by ordinary mobile smart phones. Because of mobile smart phones’ present versatility and ubiquity, the implantation and operation of 2D code, and especially Quick Response® (QR) Code, technology emerges as a very attractive alternative to automate the patients’ identification processes in low-budget situations. PMID:23569629
NASA Astrophysics Data System (ADS)
Fink, Wolfgang; Brooks, Alexander J.-W.; Tarbell, Mark A.; Dohm, James M.
2017-05-01
Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C4ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).
Automatic satellite capture and berthing with robot arm (ASCABRA)
NASA Technical Reports Server (NTRS)
Inaba, Noriyasu; Wakabayashi, Yasufumi; Iijima, Takahiko
1994-01-01
The NASDA office of R&D is studying an automatic technique to capture and berth free-floating satellites using a robot arm on another satellite. A demonstration experiment plan with the Japanese engineering test satellite ETS-7 is being developed based on the basic research on the ground. The overview and key technologies of this experiment plan are presented, and future applications of the automatic capture technique are also reviewed.
Automatic Publication of a MIS Product to GeoNetwork: Case of the AIS Indexer
2012-11-01
installation and configuration The following instructions are for installing and configuring the software packages Java 1.6 and MySQL 5.5 which are...An Automatic Identification System (AIS) reception indexer Java application was developed in the summer of 2011, based on the work of Lapinski and...release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT An Automatic Identification System (AIS) reception indexer Java application was
Yücel, Basak; Kora, Kaan; Ozyalçín, Süleyman; Alçalar, Nilüfer; Ozdemir, Ozay; Yücel, Aysen
2002-03-01
The role of psychological factors related to headache has long been a focus of investigation. The aim of this study was to evaluate depression, automatic thoughts, alexithymia, and assertiveness in persons with tension-type headache and to compare the results with those from healthy controls. One hundred five subjects with tension-type headache (according to the criteria of the International Headache Society classification) and 70 controls were studied. The Beck Depression Inventory, Automatic Thoughts Scale, Toronto Alexithymia Scale, and Rathus Assertiveness Schedule were administered to both groups. Sociodemographic variables and headache features were evaluated via a semistructured scale. Compared with healthy controls, the subjects with headache had significantly higher scores on measures of depression, automatic thoughts, and alexithymia and lower scores on assertiveness. Subjects with chronic tension-type headache had higher depression and automatic thoughts scores than those with episodic tension-type headache. These findings suggested that persons with tension-type headache have high depression scores and also may have difficulty with expression of their emotions. Headache frequency appears to influence the likelihood of coexisting depression.
Examination of a cognitive model of stress, burnout, and intention to resign for Japanese nurses.
Ohue, Takashi; Moriyama, Michiko; Nakaya, Takashi
2011-06-01
A reduction in burnout is required to decrease the voluntary turnover of nurses. This study was carried out with the aim of establishing a cognitive model of stress, burnout, and intention to resign for nurses. A questionnaire survey was administered to 336 nurses (27 male and 309 female) who had worked for ≤5 years at a hospital with multiple departments. The survey included an evaluation of burnout (Maslach Burnout Inventory), stress (Nursing Job Stressor Scale), automatic thoughts (Automatic Thoughts Questionnaire-Revised), and irrational beliefs (Japanese Irrational Belief Test), in addition to the intention to resign. The stressors that affected burnout in the nurses included conflict with other nursing staff, nursing role conflict, qualitative workload, quantitative workload, and conflict with patients. The irrational beliefs that were related to burnout included dependence, problem avoidance, and helplessness. In order to examine the automatic thoughts affecting burnout, groups with low and high negative automatic thoughts and low and high positive automatic thoughts were established. A two-way ANOVA showed a significant interaction of these factors with emotional exhaustion, but no significant interaction with depersonalization and a personal sense of accomplishment. Only the major effect was significant. The final model showed a process of "stressor → irrational beliefs → negative automatic thoughts/positive automatic thoughts → burnout". In addition, a relationship between burnout and an intention to resign was shown. These results suggest that stress and burnout in nurses might be prevented and that the number of nurses who leave their position could be decreased by changing irrational beliefs to rational beliefs, decreasing negative automatic thoughts, and facilitating positive automatic thoughts. © 2010 The Authors. Japan Journal of Nursing Science © 2010 Japan Academy of Nursing Science.
Mento, Giovanni
2017-12-01
A main distinction has been proposed between voluntary and automatic mechanisms underlying temporal orienting (TO) of selective attention. Voluntary TO implies the endogenous directing of attention induced by symbolic cues. Conversely, automatic TO is exogenously instantiated by the physical properties of stimuli. A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli. In this study a group of healthy adults underwent a cued reaction time task purposely designed to assess both voluntary and automatic TO. During the task, both post-cue and post-target event-related potentials (ERPs) were recorded by means of a high spatial resolution EEG system. In the results of the post-cue analysis, the P3a and P3b were identified as two distinct ERP markers showing distinguishable spatiotemporal features and reflecting automatic and voluntary a priori expectancy generation, respectively. The brain source reconstruction further revealed that distinct cortical circuits supported these two temporally dissociable components. Namely, the voluntary P3b was supported by a left sensorimotor network, while the automatic P3a was generated by a more distributed frontoparietal circuit. Additionally, post-cue contingent negative variation (CNV) and post-target P3 modulations were observed as common markers of voluntary and automatic expectancy implementation and response selection, although partially dissociable neural networks subserved these two mechanisms. Overall, these results provide new electrophysiological evidence suggesting that distinct neural substrates can be recruited depending on the voluntary or automatic cognitive nature of the cognitive mechanisms subserving TO. Copyright © 2017 Elsevier Ltd. All rights reserved.
2008-11-01
improves our TREC 2007 dictionary -based approach by automatically building an internal opinion dictionary from the collection itself. We measure the opin...detecting opinionated documents. The first approach improves our TREC 2007 dictionary -based approach by automat- ically building an internal opinion... dictionary from the collection itself. The second approach is based on the OpinionFinder tool, which identifies subjective sentences in text. In particular
Automatic Correction Algorithm of Hyfrology Feature Attribute in National Geographic Census
NASA Astrophysics Data System (ADS)
Li, C.; Guo, P.; Liu, X.
2017-09-01
A subset of the attributes of hydrologic features data in national geographic census are not clear, the current solution to this problem was through manual filling which is inefficient and liable to mistakes. So this paper proposes an automatic correction algorithm of hydrologic features attribute. Based on the analysis of the structure characteristics and topological relation, we put forward three basic principles of correction which include network proximity, structure robustness and topology ductility. Based on the WJ-III map workstation, we realize the automatic correction of hydrologic features. Finally, practical data is used to validate the method. The results show that our method is highly reasonable and efficient.
AISLE: an automatic volumetric segmentation method for the study of lung allometry.
Ren, Hongliang; Kazanzides, Peter
2011-01-01
We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.
Text String Detection from Natural Scenes by Structure-based Partition and Grouping
Yi, Chucai; Tian, YingLi
2012-01-01
Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) Image partition to find text character candidates based on local gradient features and color uniformity of character components. 2) Character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method, and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in non-horizontal orientations. PMID:21411405
Text string detection from natural scenes by structure-based partition and grouping.
Yi, Chucai; Tian, YingLi
2011-09-01
Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from a complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text strings with arbitrary orientations in complex natural scene images. Our proposed framework of text string detection consists of two steps: 1) image partition to find text character candidates based on local gradient features and color uniformity of character components and 2) character candidate grouping to detect text strings based on joint structural features of text characters in each text string such as character size differences, distances between neighboring characters, and character alignment. By assuming that a text string has at least three characters, we propose two algorithms of text string detection: 1) adjacent character grouping method and 2) text line grouping method. The adjacent character grouping method calculates the sibling groups of each character candidate as string segments and then merges the intersecting sibling groups into text string. The text line grouping method performs Hough transform to fit text line among the centroids of text candidates. Each fitted text line describes the orientation of a potential text string. The detected text string is presented by a rectangle region covering all characters whose centroids are cascaded in its text line. To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed methods outperform the state-of-the-art results on the public Robust Reading Dataset, which contains text only in horizontal orientation. Furthermore, the effectiveness of our methods to detect text strings with arbitrary orientations is evaluated on the Oriented Scene Text Dataset collected by ourselves containing text strings in nonhorizontal orientations.
Automatic Fastening Large Structures: a New Approach
NASA Technical Reports Server (NTRS)
Lumley, D. F.
1985-01-01
The external tank (ET) intertank structure for the space shuttle, a 27.5 ft diameter 22.5 ft long externally stiffened mechanically fastened skin-stringer-frame structure, was a labor intensitive manual structure built on a modified Saturn tooling position. A new approach was developed based on half-section subassemblies. The heart of this manufacturing approach will be 33 ft high vertical automatic riveting system with a 28 ft rotary positioner coming on-line in mid 1985. The Automatic Riveting System incorporates many of the latest automatic riveting technologies. Key features include: vertical columns with two sets of independently operating CNC drill-riveting heads; capability of drill, insert and upset any one piece fastener up to 3/8 inch diameter including slugs without displacing the workpiece offset bucking ram with programmable rotation and deep retraction; vision system for automatic parts program re-synchronization and part edge margin control; and an automatic rivet selection/handling system.
G-mode analysis of the reflection spectra of 84 asteroids.
NASA Astrophysics Data System (ADS)
Birlan, M.; Barucci, M. A.; Fulchignoni, M.
1996-01-01
A revised version of the G-mode multivariate statistics (Coradini et al. 1977) has been used to analyse a sample of 84 asteroids. This sample of asteroids is described by 29 variables, namely 23 colours between 0.9 and 2.35 microns obtained from the data base collected by Bell et al. (Private communication), 5 colors between 0.3 and 0.85 microns from the ECAS survey (Zellner et al. 1985) and the revised IRAS albedo (Tedesco et al. 1992). The G-mode method allows the user to obtain an automatic classification of the asteroids in spectrally homogeneous groups. The role of the IR colours in separating the various groups is outlined, particularly with regard to the fine subdivision of S and C taxonomical types.
Automatic Clustering of Rolling Element Bearings Defects with Artificial Neural Network
NASA Astrophysics Data System (ADS)
Antonini, M.; Faglia, R.; Pedersoli, M.; Tiboni, M.
2006-06-01
The paper presents the optimization of a methodology for automatic clustering based on Artificial Neural Networks to detect the presence of defects in rolling bearings. The research activity was developed in co-operation with an Italian company which is expert in the production of water pumps for automotive use (Industrie Saleri Italo). The final goal of the work is to develop a system for the automatic control of the pumps, at the end of the production line. In this viewpoint, we are gradually considering the main elements of the water pump, which can cause malfunctioning. The first elements we have considered are the rolling bearing, a very critic component for the system. The experimental activity is based on the vibration measuring of rolling bearings opportunely damaged; vibration signals are in the second phase elaborated; the third and last phase is an automatic clustering. Different signal elaboration techniques are compared to optimize the methodology.
Fiszman, Marcelo; Demner-Fushman, Dina; Kilicoglu, Halil; Rindflesch, Thomas C.
2009-01-01
As the number of electronic biomedical textual resources increases, it becomes harder for physicians to find useful answers at the point of care. Information retrieval applications provide access to databases; however, little research has been done on using automatic summarization to help navigate the documents returned by these systems. After presenting a semantic abstraction automatic summarization system for MEDLINE citations, we concentrate on evaluating its ability to identify useful drug interventions for fifty-three diseases. The evaluation methodology uses existing sources of evidence-based medicine as surrogates for a physician-annotated reference standard. Mean average precision (MAP) and a clinical usefulness score developed for this study were computed as performance metrics. The automatic summarization system significantly outperformed the baseline in both metrics. The MAP gain was 0.17 (p < 0.01) and the increase in the overall score of clinical usefulness was 0.39 (p < 0.05). PMID:19022398
Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang
2013-01-01
Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.
Surface smoothness: cartilage biomarkers for knee OA beyond the radiologist
NASA Astrophysics Data System (ADS)
Tummala, Sudhakar; Dam, Erik B.
2010-03-01
Fully automatic imaging biomarkers may allow quantification of patho-physiological processes that a radiologist would not be able to assess reliably. This can introduce new insight but is problematic to validate due to lack of meaningful ground truth expert measurements. Rather than quantification accuracy, such novel markers must therefore be validated against clinically meaningful end-goals such as the ability to allow correct diagnosis. We present a method for automatic cartilage surface smoothness quantification in the knee joint. The quantification is based on a curvature flow method used on tibial and femoral cartilage compartments resulting from an automatic segmentation scheme. These smoothness estimates are validated for their ability to diagnose osteoarthritis and compared to smoothness estimates based on manual expert segmentations and to conventional cartilage volume quantification. We demonstrate that the fully automatic markers eliminate the time required for radiologist annotations, and in addition provide a diagnostic marker superior to the evaluated semi-manual markers.
Controlled cooling of an electronic system for reduced energy consumption
DOE Office of Scientific and Technical Information (OSTI.GOV)
David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.
Energy efficient control of a cooling system cooling an electronic system is provided. The control includes automatically determining at least one adjusted control setting for at least one adjustable cooling component of a cooling system cooling the electronic system. The automatically determining is based, at least in part, on power being consumed by the cooling system and temperature of a heat sink to which heat extracted by the cooling system is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the coolingmore » system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on one or more experimentally obtained models relating the targeted temperature and power consumption of the one or more adjustable cooling components of the cooling system.« less
Automatic textual annotation of video news based on semantic visual object extraction
NASA Astrophysics Data System (ADS)
Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem
2003-12-01
In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.
Research in interactive scene analysis
NASA Technical Reports Server (NTRS)
Tenenbaum, J. M.; Garvey, T. D.; Weyl, S. A.; Wolf, H. C.
1975-01-01
An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.
DOE Office of Scientific and Technical Information (OSTI.GOV)
David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.
Energy efficient control of a cooling system cooling an electronic system is provided. The control includes automatically determining at least one adjusted control setting for at least one adjustable cooling component of a cooling system cooling the electronic system. The automatically determining is based, at least in part, on power being consumed by the cooling system and temperature of a heat sink to which heat extracted by the cooling system is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the coolingmore » system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on one or more experimentally obtained models relating the targeted temperature and power consumption of the one or more adjustable cooling components of the cooling system.« less
NASA Astrophysics Data System (ADS)
Wang, Bei; Sugi, Takenao; Wang, Xingyu; Nakamura, Masatoshi
Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.
Age Estimation Based on Children's Voice: A Fuzzy-Based Decision Fusion Strategy
Ting, Hua-Nong
2014-01-01
Automatic estimation of a speaker's age is a challenging research topic in the area of speech analysis. In this paper, a novel approach to estimate a speaker's age is presented. The method features a “divide and conquer” strategy wherein the speech data are divided into six groups based on the vowel classes. There are two reasons behind this strategy. First, reduction in the complicated distribution of the processing data improves the classifier's learning performance. Second, different vowel classes contain complementary information for age estimation. Mel-frequency cepstral coefficients are computed for each group and single layer feed-forward neural networks based on self-adaptive extreme learning machine are applied to the features to make a primary decision. Subsequently, fuzzy data fusion is employed to provide an overall decision by aggregating the classifier's outputs. The results are then compared with a number of state-of-the-art age estimation methods. Experiments conducted based on six age groups including children aged between 7 and 12 years revealed that fuzzy fusion of the classifier's outputs resulted in considerable improvement of up to 53.33% in age estimation accuracy. Moreover, the fuzzy fusion of decisions aggregated the complementary information of a speaker's age from various speech sources. PMID:25006595
Teaching with technology: automatically receiving information from the internet and web.
Wink, Diane M
2010-01-01
In this bimonthly series, the author examines how nurse educators can use the Internet and Web-based computer technologies such as search, communication, and collaborative writing tools, social networking and social bookmarking sites, virtual worlds, and Web-based teaching and learning programs. This article presents information and tools related to automatically receiving information from the Internet and Web.
A Model-Based Method for Content Validation of Automatically Generated Test Items
ERIC Educational Resources Information Center
Zhang, Xinxin; Gierl, Mark
2016-01-01
The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…
Systematic Design of High-performance Hybrid Feedback Algorithms
2015-06-24
Automatic Control, vol. 59, no. 9, pp. 2426- 2441 , 2014. J6. Liberzon, D.; Nešić, D.; Teel, A.R., “Lyapunov-based small-gain theorems for hybrid...on Automatic Control, vol. 59, no. 9, pp. 2426- 2441 , 2014. J6. Liberzon, D.; Nešić, D.; Teel, A.R., “Lyapunov-based small-gain theorems for hybrid
[A wavelet-transform-based method for the automatic detection of late-type stars].
Liu, Zhong-tian; Zhao, Rrui-zhen; Zhao, Yong-heng; Wu, Fu-chao
2005-07-01
The LAMOST project, the world largest sky survey project, urgently needs an automatic late-type stars detection system. However, to our knowledge, no effective methods for automatic late-type stars detection have been reported in the literature up to now. The present study work is intended to explore possible ways to deal with this issue. Here, by "late-type stars" we mean those stars with strong molecule absorption bands, including oxygen-rich M, L and T type stars and carbon-rich C stars. Based on experimental results, the authors find that after a wavelet transform with 5 scales on the late-type stars spectra, their frequency spectrum of the transformed coefficient on the 5th scale consistently manifests a unimodal distribution, and the energy of frequency spectrum is largely concentrated on a small neighborhood centered around the unique peak. However, for the spectra of other celestial bodies, the corresponding frequency spectrum is of multimodal and the energy of frequency spectrum is dispersible. Based on such a finding, the authors presented a wavelet-transform-based automatic late-type stars detection method. The proposed method is shown by extensive experiments to be practical and of good robustness.
Automatic approach to deriving fuzzy slope positions
NASA Astrophysics Data System (ADS)
Zhu, Liang-Jun; Zhu, A.-Xing; Qin, Cheng-Zhi; Liu, Jun-Zhi
2018-03-01
Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions.
A knowledge-base generating hierarchical fuzzy-neural controller.
Kandadai, R M; Tien, J M
1997-01-01
We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.
NASA Astrophysics Data System (ADS)
Takemine, S.; Rikimaru, A.; Takahashi, K.
The rice is one of the staple foods in the world High quality rice production requires periodically collecting rice growth data to control the growth of rice The height of plant the number of stem the color of leaf is well known parameters to indicate rice growth Rice growth diagnosis method based on these parameters is used operationally in Japan although collecting these parameters by field survey needs a lot of labor and time Recently a laborsaving method for rice growth diagnosis is proposed which is based on vegetation cover rate of rice Vegetation cover rate of rice is calculated based on discriminating rice plant areas in a digital camera image which is photographed in nadir direction Discrimination of rice plant areas in the image was done by the automatic binarization processing However in the case of vegetation cover rate calculation method depending on the automatic binarization process there is a possibility to decrease vegetation cover rate against growth of rice In this paper a calculation method of vegetation cover rate was proposed which based on the automatic binarization process and referred to the growth hysteresis information For several images obtained by field survey during rice growing season vegetation cover rate was calculated by the conventional automatic binarization processing and the proposed method respectively And vegetation cover rate of both methods was compared with reference value obtained by visual interpretation As a result of comparison the accuracy of discriminating rice plant areas was increased by the proposed
Hiçdurmaz, Duygu; Öz, Fatma
2016-01-01
In order to provide optimal professional care to patients, nurses must possess a positive self-image and professional identity. High interpersonal sensitivity, coping problems and dysfunctional automatic thoughts can prevent nursing students to be self-confident and successful nurses. Helping nursing students experiencing interpersonal sensitivity problems via cognitive-behavioral counseling strategies can contribute to shape good nurses. This study aims to evaluate interpersonal sensitivity, ways of coping and automatic thoughts of nursing students before and after a cognitive behavioral group counseling program. An intervention study with 43 nursing students. Measurements were done before the counseling program, at the end of the program and 4.5months after the program. The students were chosen from a faculty of nursing in Turkey. 43 second and third year nursing students who were experiencing interpersonal sensitivity problems constituted the sample. Brief Symptom Inventory, Ways of Coping Inventory and Automatic Thoughts Questionnaire were used for data collection. The students' scores of "interpersonal sensitivity", "hopeless" and "submissive" copings and "automatic thoughts" were significantly lower at the end of and 4.5months after the program than the scores before the program (Interpersonal sensitivity F=52.903, p=0.001; hopeless approach F=19.213, p=0.001; submissive approach F=4.326, p=0.016; automatic thoughts F=45.471, p=0.001). Scores of "self-confident", "optimistic" and "seeking social support" copings were higher at the end of and 4.5months after the program than the scores before the program (Self confident F=11.640, p=0.001; optimistic F=10.860, p=0.001; seeking social support F=10.411, p=0.001). This program helped the students to have better results at interpersonal sensitivity, ways of coping and automatic thoughts at the end of and 4.5 months after the program. We have reached the aim of the study. We suggest that such counseling programs should be regular and integrated into the services provided for students. Copyright © 2015 Elsevier Ltd. All rights reserved.
Automated knowledge-base refinement
NASA Technical Reports Server (NTRS)
Mooney, Raymond J.
1994-01-01
Over the last several years, we have developed several systems for automatically refining incomplete and incorrect knowledge bases. These systems are given an imperfect rule base and a set of training examples and minimally modify the knowledge base to make it consistent with the examples. One of our most recent systems, FORTE, revises first-order Horn-clause knowledge bases. This system can be viewed as automatically debugging Prolog programs based on examples of correct and incorrect I/O pairs. In fact, we have already used the system to debug simple Prolog programs written by students in a programming language course. FORTE has also been used to automatically induce and revise qualitative models of several continuous dynamic devices from qualitative behavior traces. For example, it has been used to induce and revise a qualitative model of a portion of the Reaction Control System (RCS) of the NASA Space Shuttle. By fitting a correct model of this portion of the RCS to simulated qualitative data from a faulty system, FORTE was also able to correctly diagnose simple faults in this system.
Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying
2013-01-01
High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons. Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.
Hwang, Mi-Jung; Seol, Geun Hee
2015-01-01
Heel blood sampling is a common but painful procedure for neonates. Automatic lancets have been shown to be more effective, with reduced pain and tissue damage, than manual lancets, but the effects of lancet type on cortical activation have not yet been compared. The study aimed to compare the effects of manual and automatic lancets on cerebral oxygenation and pain of heel blood sampling in 24 premature infants with respiratory distress syndrome. Effectiveness was measured by assessing numbers of pricks and squeezes and duration of heel blood sampling. Pain responses were measured using the premature infant pain profile score, heart rate, and oxygen saturation (SpO2). Regional cerebral oxygen saturation (rScO2) was measured using near-infrared spectroscopy, and cerebral fractional tissue oxygen extraction was calculated from SpO2 and rScO. Measures of effectiveness were significantly better with automatic than with manual lancing, including fewer heel punctures (P = .009) and squeezes (P < .001) and shorter duration of heel blood sampling (P = .002). rScO2 was significantly higher (P = .013) and cerebral fractional tissue oxygen extraction after puncture significantly lower (P = .040) with automatic lancing. Premature infant pain profile scores during (P = .004) and after (P = .048) puncture were significantly lower in the automatic than in the manual lancet group. Automatic lancets for heel blood sampling in neonates with respiratory distress syndrome significantly reduced pain and enhanced cerebral oxygenation, suggesting that heel blood should be sampled routinely using an automatic lancet.
Wang, Jieqiong; Miao, Wen; Li, Jing; Li, Meng; Zhen, Zonglei; Sabel, Bernhard; Xian, Junfang; He, Huiguang
2015-11-30
The lateral geniculate nucleus (LGN) is a key relay center of the visual system. Because the LGN morphology is affected by different diseases, it is of interest to analyze its morphology by segmentation. However, existing LGN segmentation methods are non-automatic, inefficient and prone to experimenters' bias. To address these problems, we proposed an automatic LGN segmentation algorithm based on T1-weighted imaging. First, the prior information of LGN was used to create a prior mask. Then region growing was applied to delineate LGN. We evaluated this automatic LGN segmentation method by (1) comparison with manually segmented LGN, (2) anatomically locating LGN in the visual system via LGN-based tractography, (3) application to control and glaucoma patients. The similarity coefficients of automatic segmented LGN and manually segmented one are 0.72 (0.06) for the left LGN and 0.77 (0.07) for the right LGN. LGN-based tractography shows the subcortical pathway seeding from LGN passes the optic tract and also reaches V1 through the optic radiation, which is consistent with the LGN location in the visual system. In addition, LGN asymmetry as well as LGN atrophy along with age is observed in normal controls. The investigation of glaucoma effects on LGN volumes demonstrates that the bilateral LGN volumes shrink in patients. The automatic LGN segmentation is objective, efficient, valid and applicable. Experiment results proved the validity and applicability of the algorithm. Our method will speed up the research on visual system and greatly enhance studies of different vision-related diseases. Copyright © 2015 Elsevier B.V. All rights reserved.
Riley, Gerard A; Venn, Paul
2015-01-01
Thirty-four participants with acquired brain injury learned word lists under two forms of vanishing cues - one in which the learning trial instructions encouraged intentional retrieval (i.e., explicit memory) and one in which they encouraged automatic retrieval (which encompasses implicit memory). The automatic instructions represented a novel approach in which the cooperation of participants was actively sought to avoid intentional retrieval. Intentional instructions resulted in fewer errors during the learning trials and better performance on immediate and delayed retrieval tests. The advantage of intentional over automatic instructions was generally less for those who had more severe memory and/or executive impairments. Most participants performed better under intentional instructions on both the immediate and the delayed tests. Although those who were more severely impaired in both memory and executive function also did better with intentional instructions on the immediate retrieval test, they were significantly more likely to show an advantage for automatic instructions on the delayed test. It is suggested that this pattern of results may reflect impairments in the consolidation of intentional memories in this group. When using vanishing cues, automatic instructions may be better for those with severe consolidation impairments, but otherwise intentional instructions may be better.
On the automaticity of response inhibition in individuals with alcoholism.
Noël, Xavier; Brevers, Damien; Hanak, Catherine; Kornreich, Charles; Verbanck, Paul; Verbruggen, Frederick
2016-06-01
Response inhibition is usually considered a hallmark of executive control. However, recent work indicates that stop performance can become associatively mediated ('automatic') over practice. This study investigated automatic response inhibition in sober and recently detoxified individuals with alcoholism.. We administered to forty recently detoxified alcoholics and forty healthy participants a modified stop-signal task that consisted of a training phase in which a subset of the stimuli was consistently associated with stopping or going, and a test phase in which this mapping was reversed. In the training phase, stop performance improved for the consistent stop stimuli, compared with control stimuli that were not associated with going or stopping. In the test phase, go performance tended to be impaired for old stop stimuli. Combined, these findings support the automatic inhibition hypothesis. Importantly, performance was similar in both groups, which indicates that automatic inhibitory control develops normally in individuals with alcoholism.. This finding is specific to individuals with alcoholism without other psychiatric disorders, which is rather atypical and prevents generalization. Personalized stimuli with a stronger affective content should be used in future studies. These results advance our understanding of behavioral inhibition in individuals with alcoholism. Furthermore, intact automatic inhibitory control may be an important element of successful cognitive remediation of addictive behaviors.. Copyright © 2016 Elsevier Ltd. All rights reserved.
Practical automatic Arabic license plate recognition system
NASA Astrophysics Data System (ADS)
Mohammad, Khader; Agaian, Sos; Saleh, Hani
2011-02-01
Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.
Wang, Caixia; Chen, Yuanyuan; Yang, Feng; Ren, Jie; Yu, Xin; Wang, Jiani; Sun, Siyu
2016-08-01
The present study aimed to assess the efficacy of computer-based endoscope cleaning and disinfection using a hospital management information system (HMIS). A total of 2,674 gastroscopes were eligible for inclusion in this study. For the processes of disinfection management, the gastroscopes were randomly divided into 2 groups: gastroscope disinfection HMIS (GD-HMIS) group and manual group. In the GD-HMIS group, an integrated circuit card (IC card) chip was installed to monitor and record endoscope cleaning and disinfection automatically and in real time, whereas the endoscope cleaning and disinfection in the manual group was recorded manually. The overall disinfection progresses for both groups were recorded, and the total operational time was calculated. For the GD-HMIS group, endoscope disinfection HMIS software was successfully developed. The time to complete a single session of cleaning and disinfecting on a gastroscope was 15.6 minutes (range, 14.3-17.2 minutes) for the GD-HMIS group and 21.3 minutes (range, 20.2-23.9 minutes) for the manual group. Failure to record information, such as the identification number of the endoscope, occasionally occurred in the manual group, which affected the accuracy and reliability of manual recording. Computer-based gastroscope cleaning and disinfection using a hospital management information system could monitor the process of gastroscope cleaning and disinfection in real time and improve the accuracy and reliability, thereby ensuring the quality of gastroscope cleaning and disinfection. Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
Hybrid Automatic Building Interpretation System
NASA Astrophysics Data System (ADS)
Pakzad, K.; Klink, A.; Müterthies, A.; Gröger, G.; Stroh, V.; Plümer, L.
2011-09-01
HABIS (Hybrid Automatic Building Interpretation System) is a system for an automatic reconstruction of building roofs used in virtual 3D building models. Unlike most of the commercially available systems, HABIS is able to work to a high degree automatically. The hybrid method uses different sources intending to exploit the advantages of the particular sources. 3D point clouds usually provide good height and surface data, whereas spatial high resolution aerial images provide important information for edges and detail information for roof objects like dormers or chimneys. The cadastral data provide important basis information about the building ground plans. The approach used in HABIS works with a multi-stage-process, which starts with a coarse roof classification based on 3D point clouds. After that it continues with an image based verification of these predicted roofs. In a further step a final classification and adjustment of the roofs is done. In addition some roof objects like dormers and chimneys are also extracted based on aerial images and added to the models. In this paper the used methods are described and some results are presented.
Brain Tumor Image Segmentation in MRI Image
NASA Astrophysics Data System (ADS)
Peni Agustin Tjahyaningtijas, Hapsari
2018-04-01
Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.
Inhibition of irrelevant information is not necessary to performance of expert chess players.
Postal, Virginie
2012-08-01
Some studies on expertise have demonstrated that the difference between novices and experts can be partly due to a lack of knowledge about which information is relevant for a given situation. This lack of knowledge seems to be associated with the selection of correct information and with inhibitory processes. However, while the efficiency of inhibitory processes can lead to better performance in the normal population, it seems that experts in chess do not base their performance on this process but rather on an automatic and parallel encoding of information. Two experiments investigated the processes involved in a check detection task. The congruence of the information was manipulated in a Stroop situation similar to Reingold, Charness, Scheltetus, & Stampe (2001). The results showed that the experts did not benefit from cuing with a congruent cue and that they did not show any interference effect by the incongruent cue, contrary to less skilled chess players who benefited from cuing (Exp. 1). An attentional priming procedure confirmed the automatic encoding of chess relations in the more skilled chess players by showing no advantage from the prime in this group (Exp. 2). Taken together, the results indicate that the processing was serial for the less skilled chess players and that it was automatic and parallel for the more expert chess players. The inhibition of irrelevant information does not seem necessary to process information rapidly and efficiently.
An automatic taxonomy of galaxy morphology using unsupervised machine learning
NASA Astrophysics Data System (ADS)
Hocking, Alex; Geach, James E.; Sun, Yi; Davey, Neil
2018-01-01
We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy we use no pre-selection or pre-filtering of target galaxy type to identify galaxies that are similar. We demonstrate the technique on the Hubble Space Telescope (HST) Frontier Fields. By training the algorithm using galaxies from one field (Abell 2744) and applying the result to another (MACS 0416.1-2403), we show how the algorithm can cleanly separate early and late type galaxies without any form of pre-directed training for what an 'early' or 'late' type galaxy is. We then apply the technique to the HST Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) fields, creating a catalogue of approximately 60 000 classifications. We show how the automatic classification groups galaxies of similar morphological (and photometric) type and make the classifications public via a catalogue, a visual catalogue and galaxy similarity search. We compare the CANDELS machine-based classifications to human-classifications from the Galaxy Zoo: CANDELS project. Although there is not a direct mapping between Galaxy Zoo and our hierarchical labelling, we demonstrate a good level of concordance between human and machine classifications. Finally, we show how the technique can be used to identify rarer objects and present lensed galaxy candidates from the CANDELS imaging.
Development of Software for Automatic Analysis of Intervention in the Field of Homeopathy.
Jain, Rajesh Kumar; Goyal, Shagun; Bhat, Sushma N; Rao, Srinath; Sakthidharan, Vivek; Kumar, Prasanna; Sajan, Kannanaikal Rappayi; Jindal, Sameer Kumar; Jindal, Ghanshyam D
2018-05-01
To study the effect of homeopathic medicines (in higher potencies) in normal subjects, Peripheral Pulse Analyzer (PPA) has been used to record physiologic variability parameters before and after administration of the medicine/placebo in 210 normal subjects. Data have been acquired in seven rounds; placebo was administered in rounds 1 and 2 and medicine in potencies 6, 30, 200, 1 M, and 10 M was administered in rounds 3 to 7, respectively. Five different medicines in the said potencies were given to a group of around 40 subjects each. Although processing of data required human intervention, a software application has been developed to analyze the processed data and detect the response to eliminate the undue delay as well as human bias in subjective analysis. This utility named Automatic Analysis of Intervention in the Field of Homeopathy is run on the processed PPA data and the outcome has been compared with the manual analysis. The application software uses adaptive threshold based on statistics for detecting responses in contrast to fixed threshold used in manual analysis. The automatic analysis has detected 12.96% higher responses than subjective analysis. Higher response rates have been manually verified to be true positive. This indicates robustness of the application software. The automatic analysis software was run on another set of pulse harmonic parameters derived from the same data set to study cardiovascular susceptibility and 385 responses were detected in contrast to 272 of variability parameters. It was observed that 65% of the subjects, eliciting response, were common. This not only validates the software utility for giving consistent yield but also reveals the certainty of the response. This development may lead to electronic proving of homeopathic medicines (e-proving).
Bastian, Thomas; Maire, Aurélia; Dugas, Julien; Ataya, Abbas; Villars, Clément; Gris, Florence; Perrin, Emilie; Caritu, Yanis; Doron, Maeva; Blanc, Stéphane; Jallon, Pierre; Simon, Chantal
2015-03-15
"Objective" methods to monitor physical activity and sedentary patterns in free-living conditions are necessary to further our understanding of their impacts on health. In recent years, many software solutions capable of automatically identifying activity types from portable accelerometry data have been developed, with promising results in controlled conditions, but virtually no reports on field tests. An automatic classification algorithm initially developed using laboratory-acquired data (59 subjects engaging in a set of 24 standardized activities) to discriminate between 8 activity classes (lying, slouching, sitting, standing, walking, running, and cycling) was applied to data collected in the field. Twenty volunteers equipped with a hip-worn triaxial accelerometer performed at their own pace an activity set that included, among others, activities such as walking the streets, running, cycling, and taking the bus. Performances of the laboratory-calibrated classification algorithm were compared with those of an alternative version of the same model including field-collected data in the learning set. Despite good results in laboratory conditions, the performances of the laboratory-calibrated algorithm (assessed by confusion matrices) decreased for several activities when applied to free-living data. Recalibrating the algorithm with data closer to real-life conditions and from an independent group of subjects proved useful, especially for the detection of sedentary behaviors while in transports, thereby improving the detection of overall sitting (sensitivity: laboratory model = 24.9%; recalibrated model = 95.7%). Automatic identification methods should be developed using data acquired in free-living conditions rather than data from standardized laboratory activity sets only, and their limits carefully tested before they are used in field studies. Copyright © 2015 the American Physiological Society.
Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.
DOT National Transportation Integrated Search
2012-12-01
This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...
Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas
Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.
2013-01-01
The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545
Schlaeger, Sarah; Freitag, Friedemann; Klupp, Elisabeth; Dieckmeyer, Michael; Weidlich, Dominik; Inhuber, Stephanie; Deschauer, Marcus; Schoser, Benedikt; Bublitz, Sarah; Montagnese, Federica; Zimmer, Claus; Rummeny, Ernst J; Karampinos, Dimitrios C; Kirschke, Jan S; Baum, Thomas
2018-01-01
Magnetic resonance imaging (MRI) can non-invasively assess muscle anatomy, exercise effects and pathologies with different underlying causes such as neuromuscular diseases (NMD). Quantitative MRI including fat fraction mapping using chemical shift encoding-based water-fat MRI has emerged for reliable determination of muscle volume and fat composition. The data analysis of water-fat images requires segmentation of the different muscles which has been mainly performed manually in the past and is a very time consuming process, currently limiting the clinical applicability. An automatization of the segmentation process would lead to a more time-efficient analysis. In the present work, the manually segmented thigh magnetic resonance imaging database MyoSegmenTUM is presented. It hosts water-fat MR images of both thighs of 15 healthy subjects and 4 patients with NMD with a voxel size of 3.2x2x4 mm3 with the corresponding segmentation masks for four functional muscle groups: quadriceps femoris, sartorius, gracilis, hamstrings. The database is freely accessible online at https://osf.io/svwa7/?view_only=c2c980c17b3a40fca35d088a3cdd83e2. The database is mainly meant as ground truth which can be used as training and test dataset for automatic muscle segmentation algorithms. The segmentation allows extraction of muscle cross sectional area (CSA) and volume. Proton density fat fraction (PDFF) of the defined muscle groups from the corresponding images and quadriceps muscle strength measurements/neurological muscle strength rating can be used for benchmarking purposes.
Automatic Invocation Linking for Collaborative Web-Based Corpora
NASA Astrophysics Data System (ADS)
Gardner, James; Krowne, Aaron; Xiong, Li
Collaborative online encyclopedias or knowledge bases such as Wikipedia and PlanetMath are becoming increasingly popular because of their open access, comprehensive and interlinked content, rapid and continual updates, and community interactivity. To understand a particular concept in these knowledge bases, a reader needs to learn about related and underlying concepts. In this chapter, we introduce the problem of invocation linking for collaborative encyclopedia or knowledge bases, review the state of the art for invocation linking including the popular linking system of Wikipedia, discuss the problems and challenges of automatic linking, and present the NNexus approach, an abstraction and generalization of the automatic linking system used by PlanetMath.org. The chapter emphasizes both research problems and practical design issues through discussion of real world scenarios and hence is suitable for both researchers in web intelligence and practitioners looking to adopt the techniques. Below is a brief outline of the chapter.
Prince, F H M; Ferket, I S; Kamphuis, S; Armbrust, W; Ten Cate, R; Hoppenreijs, E P A H; Koopman-Keemink, Y; van Rossum, M A J; van Santen-Hoeufft, M; Twilt, M; van Suijlekom-Smit, L W A
2008-09-01
Most clinical studies use paper case record forms (CRFs) to collect data. In the Dutch multi-centre observational study on biologicals we encountered several disadvantages of using the paper CRFs. These are delay in data collection, lack of overview in collected data and difficulties in obtaining up-to-date interim reports. Therefore, we wanted to create a more effective method of data collection compared with CRFs on paper in a multi-centre study. We designed a web-based register with the intention to make it easy to use for participating physicians and at the same time accurate and up-to-date. Security demands were taken into account to secure the safety of the patient data. The web-based register was tested with data from 161 juvenile idiopathic arthritis patients from nine different centres. Internal validity was obtained and user-friendliness guaranteed. To secure the completeness of the data automatically generated e-mail alerts were implemented into the web-based register. More transparency of data was achieved by including the option to automatically generate interim reports of data in the web-based register. The safety was tested and approved. By digitalizing the CRF we achieved our aim to provide easy, rapid and safe access to the database and contributed to a new way of data collection. Although the web-based register was designed for the current multi-centre observational study, this type of instrument can also be applied to other types of studies. We expect that especially collaborative study groups will find it an efficient tool to collect data.
Melles, Reinhilde J; ter Kuile, Moniek M; Dewitte, Marieke; van Lankveld, Jacques J D M; Brauer, Marieke; de Jong, Peter J
2014-03-01
The intense fear response to vaginal penetration in women with lifelong vaginismus, who have never been able to experience coitus, may reflect negative automatic and deliberate appraisals of vaginal penetration stimuli which might be modified by exposure treatment. The aim of this study is to examine whether (i) sexual stimuli elicit relatively strong automatic and deliberate threat associations in women with vaginismus, as well as relatively negative automatic and deliberate global affective associations, compared with symptom-free women; and (ii) these automatic and more deliberate attitudes can be modified by therapist-aided exposure treatment. A single target Implicit Association Test (st-IAT) was used to index automatic threat associations, and an Affective Simon Task (AST) to index global automatic affective associations. Participants were women with lifelong vaginismus (N = 68) and women without sexual problems (N = 70). The vaginismus group was randomly allocated to treatment (n = 34) and a waiting list control condition (n = 34). Indices of automatic threat were obtained by the st-IAT and automatic global affective associations by the AST, visual analogue scales (VAS) were used to assess deliberate appraisals of the sexual pictures (fear and global positive affect). More deliberate fear and less global positive affective associations with sexual stimuli were found in women with vaginismus. Following therapist-aided exposure treatment, the strength of fear was strongly reduced, whereas global positive affective associations were strengthened. Automatic associations did not differ between women with and without vaginismus and did not change following treatment. Relatively stronger negative (threat or global affect) associations with sexual stimuli in vaginismus appeared restricted to the deliberate level. Therapist-aided exposure treatment was effective in reducing subjective fear of sexual penetration stimuli and led to more global positive affective associations with sexual stimuli. The impact of exposure might be further improved by strengthening the association between vaginal penetration and positive affect (e.g., by using counter-conditioning techniques). © 2013 International Society for Sexual Medicine.
Tsai, P P; Nagelschmidt, N; Kirchner, J; Stelzer, H D; Hackbarth, H
2012-01-01
Preference tests have often been performed for collecting information about animals' acceptance of environmental refinement objects. In numerous published studies animals were individually tested during preference experiments, as it is difficult to observe group-housed animals with an automatic system. Thus, videotaping is still the most favoured method for observing preferences of socially-housed animals. To reduce the observation workload and to be able to carry out preference testing of socially-housed animals, an automatic recording system (DoubleCage) was developed for determining the location of group-housed animals in a preference test set-up. This system is able to distinguish the transition of individual animals between two cages and to record up to 16 animals at the same time (four animals per cage). The present study evaluated the reliability of the DoubleCage system. The data recorded by the DoubleCage program and the data obtained by human observation were compared. The measurements of the DoubleCage system and manual observation of the videotapes are comparable and significantly correlated (P < 0.0001) with good agreement. Using the DoubleCage system enables precise and reliable recording of the preferences of group-housed animals and a considerable reduction of animal observation time.
Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B
1997-01-01
An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.
A simulator evaluation of an automatic terminal approach system
NASA Technical Reports Server (NTRS)
Hinton, D. A.
1983-01-01
The automatic terminal approach system (ATAS) is a concept for improving the pilot/machine interface with cockpit automation. The ATAS can automatically fly a published instrument approach by using stored instrument approach data to automatically tune airplane avionics, control the airplane's autopilot, and display status information to the pilot. A piloted simulation study was conducted to determine the feasibility of an ATAS, determine pilot acceptance, and examine pilot/ATAS interaction. Seven instrument-rated pilots each flew four instrument approaches with a base-line heading select autopilot mode. The ATAS runs resulted in lower flight technical error, lower pilot workload, and fewer blunders than with the baseline autopilot. The ATAS status display enabled the pilots to maintain situational awareness during the automatic approaches. The system was well accepted by the pilots.
Object-based media and stream-based computing
NASA Astrophysics Data System (ADS)
Bove, V. Michael, Jr.
1998-03-01
Object-based media refers to the representation of audiovisual information as a collection of objects - the result of scene-analysis algorithms - and a script describing how they are to be rendered for display. Such multimedia presentations can adapt to viewing circumstances as well as to viewer preferences and behavior, and can provide a richer link between content creator and consumer. With faster networks and processors, such ideas become applicable to live interpersonal communications as well, creating a more natural and productive alternative to traditional videoconferencing. In this paper is outlined an example of object-based media algorithms and applications developed by my group, and present new hardware architectures and software methods that we have developed to enable meeting the computational requirements of object- based and other advanced media representations. In particular we describe stream-based processing, which enables automatic run-time parallelization of multidimensional signal processing tasks even given heterogenous computational resources.
Automatic Barometric Updates from Ground-Based Navigational Aids
1990-03-12
ro fAutomatic Barometric Updates US Department from of Transportation Ground-Based Federal Aviation Administration Navigational Aids Office of Safety...tighter vertical spacing controls , particularly for operations near Terminal Control Areas (TCAs), Airport Radar Service Areas (ARSAs), military climb and...E.F., Ruth, J.C., and Williges, B.H. (1987). Speech Controls and Displays. In Salvendy, G., E. Handbook of Human Factors/Ergonomics, New York, John
A State-of-the-Art Assessment of Automatic Name Placement.
1986-08-01
develop an automatic name placement system. 11 Balodis, M., "Positioning of typography on maps," Proc. ACSM Pall Con- vention, Salt Lake City, Utah, Sept...1983, pp. 28-44. This article deals with the selection of typography for maps. It describes psycho-visual experiments with groups of individuals to...Polytechnic Institute, Troy, NY 12181, May 1984. (Also available as Tech. Rept. IPL-TR-063.) SBalodis, M., "Positioning of typography on maps," Proc
Automatic mimicry reactions as related to differences in emotional empathy.
Sonnby-Borgström, Marianne
2002-12-01
The hypotheses of this investigation were derived by conceiving of automatic mimicking as a component of emotional empathy. Differences between subjects high and low in emotional empathy were investigated. The parameters compared were facial mimicry reactions, as represented by electromyographic (EMG) activity when subjects were exposed to pictures of angry or happy faces, and the degree of correspondence between subjects' facial EMG reactions and their self-reported feelings. The comparisons were made at different stimulus exposure times in order to elicit reactions at different levels of information processing. The high-empathy subjects were found to have a higher degree of mimicking behavior than the low-empathy subjects, a difference that emerged at short exposure times (17-40 ms) that represented automatic reactions. The low-empathy subjects tended already at short exposure times (17-40 ms) to show inverse zygomaticus muscle reactions, namely "smiling" when exposed to an angry face. The high-empathy group was characterized by a significantly higher correspondence between facial expressions and self-reported feelings. No differences were found between the high- and low-empathy subjects in their verbally reported feelings when presented a happy or an angry face. Thus, the differences between the groups in emotional empathy appeared to be related to differences in automatic somatic reactions to facial stimuli rather than to differences in their conscious interpretation of the emotional situation.
Peak Detection Method Evaluation for Ion Mobility Spectrometry by Using Machine Learning Approaches
Hauschild, Anne-Christin; Kopczynski, Dominik; D’Addario, Marianna; Baumbach, Jörg Ingo; Rahmann, Sven; Baumbach, Jan
2013-01-01
Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME). We manually generated a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors’ results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications. PMID:24957992