Effectiveness of multimodal pain management after bipolar hemiarthroplasty for hip fracture: a randomized, controlled study.

PubMed

Kang, Hyun; Ha, Yong-Chan; Kim, Jin-Yun; Woo, Young-Cheol; Lee, Jae-Sung; Jang, Eui-Chan

2013-02-20

Appropriate pain management affects outcome after hip fracture surgery. Although multimodal pain management is commonly used for pain control for patients undergoing elective surgery, few studies have evaluated its use in those undergoing hip fracture surgery. This prospective randomized study was designed to determine the clinical value of multimodal pain management with preemptive pain medication and intraoperative periarticular multimodal drug injections in patients undergoing bipolar hip hemiarthroplasty. Of eighty-two cognitively intact elderly patients about to undergo bipolar hemiarthroplasty after a hip fracture, forty-three were randomly assigned to receive preemptive pain medication and intraoperative periarticular injections (Group I) and thirty-nine were assigned to not receive preemptive medication and injections (Group II). These two groups were compared with regard to the pain level on postoperative days one, four, and seven; at discharge; and when they started walking and standing exercises. Total amounts of fentanyl used, the frequency of use of patient-controlled analgesia, patient satisfaction at discharge, and perioperative complications were recorded. Group I had a lower pain level than Group II on postoperative days one and four, but no intergroup difference in pain level was observed on postoperative day seven. The total amount of fentanyl used and the frequency of use of patient-controlled analgesia were also lower in Group I. Patient satisfaction at discharge was higher in Group I. No significant intergroup differences were found in the times until the patients walked or performed standing exercises or in the complications. Multimodal pain management provides additional pain relief until the fourth postoperative day, improves patient satisfaction at discharge, and reduces total narcotic consumption for postoperative pain management after hip hemiarthroplasty for hip fractures.

Sharing Solutions: Persistence and Grounding in Multimodal Collaborative Problem Solving

ERIC Educational Resources Information Center

Dillenbourg, Pierre; Traum, David

2006-01-01

This article reports on an exploratory study of the relationship between grounding and problem solving in multimodal computer-mediated collaboration. This article examines two different media, a shared whiteboard and a MOO environment that includes a text chat facility. A study was done on how the acknowledgment rate (how often partners give…

Optimal rail container shipment planning problem in multimodal transportation

NASA Astrophysics Data System (ADS)

Cao, Chengxuan; Gao, Ziyou; Li, Keping

2012-09-01

The optimal rail container shipment planning problem in multimodal transportation is studied in this article. The characteristics of the multi-period planning problem is presented and the problem is formulated as a large-scale 0-1 integer programming model, which maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited capacities. Two heuristic algorithms are proposed to obtain an approximate optimal solution of the problem. Finally, numerical experiments are conducted to demonstrate the proposed formulation and heuristic algorithms.

Creative Multimodal Learning Environments and Blended Interaction for Problem-Based Activity in HCI Education

ERIC Educational Resources Information Center

Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis; Arh, Tanja; Klobucar, Tomaž; Pipan, Matija

2015-01-01

This exploratory case study aims to examine how students benefit from a multimodal learning environment while they engage in collaborative problem-based activity in a Human Computer Interaction (HCI) university course. For 12 weeks, 30 students, in groups of 5-7 each, participated in weekly face-to-face meetings and online interactions.…

A framework for the nationwide multimode transportation demand analysis.

DOT National Transportation Integrated Search

2010-09-01

This study attempts to analyze the impact of traffic on the US highway system considering both passenger vehicles and : trucks. For the analysis, a pseudo-dynamic traffic assignment model is proposed to estimate the time-dependent link flow : from th...

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Lin, Guang; Li, Weixuan; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Ensemble smoother (ES) has been widely used in inverse modeling of hydrologic systems. However, for problems where the distribution of model parameters is multimodal, using ES directly would be problematic. One popular solution is to use a clustering algorithm to identify each mode and update the clusters with ES separately. However, this strategy may not be very efficient when the dimension of parameter space is high or the number of modes is large. Alternatively, we propose in this paper a very simple and efficient algorithm, i.e., the iterative local updating ensemble smoother (ILUES), to explore multimodal distributions of model parameters in nonlinear hydrologic systems. The ILUES algorithm works by updating local ensembles of each sample with ES to explore possible multimodal distributions. To achieve satisfactory data matches in nonlinear problems, we adopt an iterative form of ES to assimilate the measurements multiple times. Numerical cases involving nonlinearity and multimodality are tested to illustrate the performance of the proposed method. It is shown that overall the ILUES algorithm can well quantify the parametric uncertainties of complex hydrologic models, no matter whether the multimodal distribution exists.

Challenges in treatment of posttraumatic stress disorder in refugees: towards integration of evidence-based treatments with contextual and culture-sensitive perspectives

PubMed Central

Drožđek, Boris

2015-01-01

Background Research shows that trauma-focused therapy and multimodal interventions are the two most often used strategies in treatment of refugees suffering from posttraumatic stress disorder (PTSD). While preliminary evidence suggests that trauma-focused approaches may have some efficacy, this could not be established for multimodal interventions. However, it may be that multimodal interventions have been studied in more treatment-resistant refugees with very high levels of psychopathology, disability, and chronicity. In the past decades, various models for understanding of the complex relationship between mental health problems and well-being have emerged. They aim at framing mental health problems in individualized, contextual, epigenetic, and culturally sensitive ways, and may be useful in tailoring content and timing of multimodal interventions. Objective To draw clinicians’ attention to the possibility of using the Integrative Contextual Model for understanding and assessment of posttrauma mental health sequelae while tailoring multimodal interventions; to present a possible way of combining multimodal with evidence-based trauma-focused approaches; and to improve the understanding and treatment of PTSD and other mental health problems in refugee survivors of prolonged and repeated trauma. Method Based on literature, clinical experience, and presentation of a fictional case, the use of the Integrative Contextual Model in tailoring the treatment of severe PTSD in a refugee patient is presented and discussed. Results The Integrative Contextual Model for understanding and assessing factors, which may play a role in causing and maintaining of PTSD and comorbidity in refugees, may help tailoring of multimodal interventions. These interventions can be combined with evidence-based trauma-focused treatments. Conclusion The field of refugee mental health intervention and clinical practice with traumatized refugees may be enriched with the use of contextual and developmental models for assessment and conceptualization of posttrauma sequelae. Multimodal and trauma-focused interventions may be applied sequentially in a course of the treatment trajectory. PMID:25573504

Learning multimodal dictionaries.

PubMed

Monaci, Gianluca; Jost, Philippe; Vandergheynst, Pierre; Mailhé, Boris; Lesage, Sylvain; Gribonval, Rémi

2007-09-01

Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This paradigm can be also extremely useful in many signal processing and computer vision problems involving mutually related signals. The simultaneous processing of multimodal data can, in fact, reveal information that is otherwise hidden when considering the signals independently. However, in natural multimodal signals, the statistical dependencies between modalities are in general not obvious. Learning fundamental multimodal patterns could offer deep insight into the structure of such signals. In this paper, we present a novel model of multimodal signals based on their sparse decomposition over a dictionary of multimodal structures. An algorithm for iteratively learning multimodal generating functions that can be shifted at all positions in the signal is proposed, as well. The learning is defined in such a way that it can be accomplished by iteratively solving a generalized eigenvector problem, which makes the algorithm fast, flexible, and free of user-defined parameters. The proposed algorithm is applied to audiovisual sequences and it is able to discover underlying structures in the data. The detection of such audio-video patterns in audiovisual clips allows to effectively localize the sound source on the video in presence of substantial acoustic and visual distractors, outperforming state-of-the-art audiovisual localization algorithms.

Robust Multimodal Dictionary Learning

PubMed Central

Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674

Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints

PubMed Central

Sun, Yan; Lang, Maoxiang; Wang, Danzhu

2016-01-01

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294

Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

PubMed Central

Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

2012-01-01

When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance. PMID:22778600

Palmprint and face multi-modal biometric recognition based on SDA-GSVD and its kernelization.

PubMed

Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

2012-01-01

When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

Effects of Multimodal Analgesia on the Success of Mouse Embryo Transfer Surgery

PubMed Central

Parker, John M.; Austin, Jamie; Wilkerson, James; Carbone, Larry

2011-01-01

Multimodal analgesia is promoted as the best practice pain management for invasive animal research procedures. Universal acceptance and incorporation of multimodal analgesia requires assessing potential effects on study outcome. The focus of this study was to assess effects on embryo survival after multimodal analgesia comprising an opioid and nonsteroidal antiinflammatory drug (NSAID) compared with opioid-only analgesia during embryo transfer procedures in transgenic mouse production. Mice were assigned to receive either carprofen (5 mg/kg) with buprenorphine (0.1 mg/kg; CB) or vehicle with buprenorphine (0.1 mg/kg; VB) in a prospective, double-blinded placebo controlled clinical trial. Data were analyzed in surgical sets of 1 to 3 female mice receiving embryos chimeric for a shared targeted embryonic stem-cell clone and host blastocyst cells. A total of 99 surgical sets were analyzed, comprising 199 Crl:CD1 female mice and their 996 offspring. Neither yield (pups weaned per embryo implanted in the surgical set) nor birth rate (average number of pups weaned per dam in the set) differed significantly between the CB and VB conditions. Multimodal opioid–NSAID analgesia appears to have no significant positive or negative effect on the success of producing novel lines of transgenic mice by blastocyst transfer. PMID:21838973

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Genre, Reflection, and Multimodality: Capturing Uptake in the Making

ERIC Educational Resources Information Center

Fiscus, Jaclyn M.

2017-01-01

Scholarship on metacognition in the composition classroom shows how asking students to create reflective texts can help cue, analyze, and assess transfer. By following the composition processes of 13 students doing a remixing assignment, this project examines how genre mediates reflection. I use Rhetorical Genre Studies' conception of…

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

NASA Astrophysics Data System (ADS)

Liu, Zhiyuan; Meng, Qiang

2014-05-01

This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users' route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users' generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.

Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification.

PubMed

Rajagopal, Gayathri; Palaniswamy, Ramamoorthy

2015-01-01

This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature level fusion to achieve better performance. The main aim of the proposed system is to increase the recognition accuracy using feature level fusion. The features at the feature level fusion are raw biometric data which contains rich information when compared to decision and matching score level fusion. Hence information fused at the feature level is expected to obtain improved recognition accuracy. However, information fused at feature level has the problem of curse in dimensionality; here PCA (principal component analysis) is used to diminish the dimensionality of the feature sets as they are high dimensional. The proposed multimodal results were compared with other multimodal and monomodal approaches. Out of these comparisons, the multimodal multifeature palmprint iris fusion offers significant improvements in the accuracy of the suggested multimodal biometric system. The proposed algorithm is tested using created virtual multimodal database using UPOL iris database and PolyU palmprint database.

Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification

PubMed Central

Rajagopal, Gayathri; Palaniswamy, Ramamoorthy

2015-01-01

This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature level fusion to achieve better performance. The main aim of the proposed system is to increase the recognition accuracy using feature level fusion. The features at the feature level fusion are raw biometric data which contains rich information when compared to decision and matching score level fusion. Hence information fused at the feature level is expected to obtain improved recognition accuracy. However, information fused at feature level has the problem of curse in dimensionality; here PCA (principal component analysis) is used to diminish the dimensionality of the feature sets as they are high dimensional. The proposed multimodal results were compared with other multimodal and monomodal approaches. Out of these comparisons, the multimodal multifeature palmprint iris fusion offers significant improvements in the accuracy of the suggested multimodal biometric system. The proposed algorithm is tested using created virtual multimodal database using UPOL iris database and PolyU palmprint database. PMID:26640813

Blissymbols and Manual Signs: A Multimodal Approach to Intervention in a Case of Multiple Disability.

ERIC Educational Resources Information Center

Hooper, Janice; And Others

1987-01-01

A multimodal intervention program designed for a nine-year-old with severe communication problems (secondary to cerebral palsy, receptive dysphasia, and auditory agnosia) combined manual signs and graphic symbols to help her communicate. The intensive, highly structured program had significant positive results. (Author/CB)

Designing a Digital Story Assignment for Basic Writers Using the TPCK Framework

ERIC Educational Resources Information Center

Bandi-Rao, Shoba; Sepp, Mary

2014-01-01

The process of digital storytelling allows basic writers to take a personal narrative and translate it into a multimodal and multidimensional experience, motivating a diverse group of writers with different learning styles to engage more creatively and meaningfully in the writing process. Digital storytelling has the capacity to contextualize…

Digital Collaboration inside and outside Educational Systems

ERIC Educational Resources Information Center

Birkeland, Nils Rune; Drange, Eli-Marie Danbolt; Tønnessen, Elise Seip

2015-01-01

This article takes its outset in findings from an ongoing research project investigating the use of digital and multimodal resources in teacher education (TE) in Norway. The material studied is mandatory assignments in different courses in TE, asking how teacher students collaborate through digital media in their production of texts for learning,…

Student-Generated Instructional Videos Facilitate Learning through Positive Emotions

ERIC Educational Resources Information Center

Pirhonen, Juhani; Rasi, Päivi

2017-01-01

The central focus of this study is a learning method in which university students produce instructional videos about the content matter as part of their learning process, combined with other learning assignments. The rationale for this is to promote a more multimodal pedagogy, and to provide students opportunities for a more learner-centred,…

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

Multimodal Therapy Involving High-Intensity Interval Training Improves the Physical Fitness, Motor Skills, Social Behavior, and Quality of Life of Boys With ADHD: A Randomized Controlled Study.

PubMed

Meßler, Carolin Friederike; Holmberg, Hans-Christer; Sperlich, Billy

2018-06-01

To compare the effects of multimodal therapy including supervised high-intensity interval training (HIIT) with those of standard multimodal therapy (TRAD) concerning key variables of physical fitness (peak power and oxygen uptake), motor skills, social behavior, and quality of life in boys with ADHD. A single-center, two-arm randomized, controlled design was used, with 28 boys (8-13 years of age, IQ = 83-136) being randomly assigned to multimodal HIIT (three sessions/week, 4 × 4-min intervals at 95% of peak heart rate) or TRAD. The Movement Assessment Battery for Children II evaluated motor skills and the German version of the hyperkinetic disorder questionnaire for external evaluation by the guardians (FBB-HKS) or German version of the hyperkinetic disorder questionnaire for self-assessment by the children (SBB-HKS) and the KINDL-R questionnaires mental health and health-related quality of life. Both interventions enhanced peak power, and HIIT also reduced submaximal oxygen uptake. HIIT was more effective than TRAD in improving the total score for motor skills (including manual dexterity and ball skills; p < .05), self-esteem, friends, and competence ( p < .05) and, moreover, improved subjective ratings of attention. Three weeks of multimodal therapy including HIIT improved physical fitness, motor skills, certain aspects of quality of life, competence, and attention in boys with ADHD.

Adolescent Substance Use in the Multimodal Treatment Study of Attention-Deficit/Hyperactivity Disorder (ADHD) (MTA) as a Function of Childhood ADHD, Random Assignment to Childhood Treatments, and Subsequent Medication

PubMed Central

Molina, Brooke S.G.; Hinshaw, Stephen P.; Arnold, L. Eugene; Swanson, James M.; Pelham, William E.; Hechtman, Lily; Hoza, Betsy; Epstein, Jeffery N.; Wigal, Timothy; Abikoff, Howard B.; Greenhill, Laurence L.; Jensen, Peter S.; Wells, Karen C.; Vitiello, Benedetto; Gibbons, Robert D.; Howard, Andrea; Houck, Patricia R.; Hur, Kwan; Lu, Bo; Marcus, Sue

2013-01-01

Objectives To determine long-term effects on substance use and substance use disorder (SUD), up to 8 years after childhood enrollment, of the randomly assigned 14-month treatments in the multisite Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (MTA; n=436); to test whether (a) medication at follow-up, (b) cumulative psychostimulant treatment over time, or (c) both relate to substance use/SUD; to compare substance use/SUD in the ADHD sample to the non-ADHD childhood classmate comparison group (n=261). Method Mixed-effects regression models with planned contrasts were used for all tests except the important cumulative stimulant treatment question, for which propensity score matching analysis was used. Results The originally randomized treatment groups did not differ significantly on substance use/SUD by the 8 year follow-up or earlier (M age = 17 years). Neither medication at follow-up (mostly stimulants) nor cumulative stimulant treatment was associated with adolescent substance use/SUD. Substance use at all time points, including use of two or more substances and SUD, were each greater in the ADHD than non-ADHD samples, regardless of sex. Conclusions Medication for ADHD did not protect from, nor contribute to, visible risk of substance use or SUD by adolescence, whether analyzed as randomized treatment assignment in childhood, as medication at follow-up, or as cumulative stimulant treatment over an 8 year follow-up from childhood. These results suggest the need to identify alternative or adjunctive adolescent-focused approaches to substance abuse prevention and treatment for boys and girls with ADHD, especially given their increased risk for use and abuse of multiple substances that is not improved with stimulant medication. Clinical trial registration information—Multimodal Treatment Study of Children with Attention Deficit and Hyperactivity Disorder (MTA); http://clinical trials.gov/; NCT00000388. PMID:23452682

Adolescent substance use in the multimodal treatment study of attention-deficit/hyperactivity disorder (ADHD) (MTA) as a function of childhood ADHD, random assignment to childhood treatments, and subsequent medication.

PubMed

Molina, Brooke S G; Hinshaw, Stephen P; Eugene Arnold, L; Swanson, James M; Pelham, William E; Hechtman, Lily; Hoza, Betsy; Epstein, Jeffery N; Wigal, Timothy; Abikoff, Howard B; Greenhill, Laurence L; Jensen, Peter S; Wells, Karen C; Vitiello, Benedetto; Gibbons, Robert D; Howard, Andrea; Houck, Patricia R; Hur, Kwan; Lu, Bo; Marcus, Sue

2013-03-01

To determine long-term effects on substance use and substance use disorder (SUD), up to 8 years after childhood enrollment, of the randomly assigned 14-month treatments in the multisite Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (MTA; n = 436); to test whether medication at follow-up, cumulative psychostimulant treatment over time, or both relate to substance use/SUD; and to compare substance use/SUD in the ADHD sample to the non-ADHD childhood classmate comparison group (n = 261). Mixed-effects regression models with planned contrasts were used for all tests except the important cumulative stimulant treatment question, for which propensity score matching analysis was used. The originally randomized treatment groups did not differ significantly on substance use/SUD by the 8-year follow-up or earlier (mean age = 17 years). Neither medication at follow-up (mostly stimulants) nor cumulative stimulant treatment was associated with adolescent substance use/SUD. Substance use at all time points, including use of two or more substances and SUD, were each greater in the ADHD than in the non-ADHD samples, regardless of sex. Medication for ADHD did not protect from, or contribute to, visible risk of substance use or SUD by adolescence, whether analyzed as randomized treatment assignment in childhood, as medication at follow-up, or as cumulative stimulant treatment over an 8-year follow-up from childhood. These results suggest the need to identify alternative or adjunctive adolescent-focused approaches to substance abuse prevention and treatment for boys and girls with ADHD, especially given their increased risk for use and abuse of multiple substances that is not improved with stimulant medication. Clinical trial registration information-Multimodal Treatment Study of Children With Attention Deficit and Hyperactivity Disorder (MTA); http://clinical trials.gov/; NCT00000388. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. All rights reserved.

An analysis of science content and representations in introductory college physics textbooks and multimodal learning resources

NASA Astrophysics Data System (ADS)

Donnelly, Suzanne M.

This study features a comparative descriptive analysis of the physics content and representations surrounding the first law of thermodynamics as presented in four widely used introductory college physics textbooks representing each of four physics textbook categories (calculus-based, algebra/trigonometry-based, conceptual, and technical/applied). Introducing and employing a newly developed theoretical framework, multimodal generative learning theory (MGLT), an analysis of the multimodal characteristics of textbook and multimedia representations of physics principles was conducted. The modal affordances of textbook representations were identified, characterized, and compared across the four physics textbook categories in the context of their support of problem-solving. Keywords: college science, science textbooks, multimodal learning theory, thermodynamics, representations

Severe Pain Due to Paraspinal Abscess Formation in Two Patients with Squamous-Cell Carcinoma of the Head and Neck after Multimodal Treatment Including Cetuximab.

PubMed

Gerlach, Christina; Pretzell, Ina; Lieberknecht, Elisabeth; Mattyasovszky, Stefan; Weber, Martin

2018-01-01

Patients with squamous-cell carcinoma of the head and neck (SCCHN) on palliative therapy usually have a bad prognosis and suffer from various symptoms. With increasing use of targeted agents in cancer patients at the end of life, the correct assignment of therapy-related symptoms becomes increasingly difficult as cancer-related symptoms usually increase as well. We report on 2 cases of patients with SCCHN who received multimodal treatment including palliative therapy with cetuximab. Both patients developed severe thoracic and cervicothoracic pain following treatment. In both cases, extensive paraspinal abscess formation proved to be the underlying cause. One patient was treated conservatively; the other one had to undergo surgical intervention. Awareness of multifaceted therapy-related complications is mandatory when patients receive multimodal treatment including targeted therapies. Unexplained pain syndromes in this context should raise suspicions concerning possible infectious complications and should lead to early use of magnetic resonance imaging. © 2018 S. Karger GmbH, Freiburg.

Comparison of multi-modal early oral nutrition for the tolerance of oral nutrition with conventional care after major abdominal surgery: a prospective, randomized, single-blind trial.

PubMed

Sun, Da-Li; Li, Wei-Ming; Li, Shu-Min; Cen, Yun-Yun; Xu, Qing-Wen; Li, Yi-Jun; Sun, Yan-Bo; Qi, Yu-Xing; Lin, Yue-Ying; Yang, Ting; Lu, Qi-Ping; Xu, Peng-Yuan

2017-02-10

Early oral nutrition (EON) has been shown to improve recovery of gastrointestinal function, length of stay and mortality after abdominal surgery; however, early oral nutrition often fails during the first week after surgery. Here, a multi-modal early oral nutrition program is introduced to promote recovery of gastrointestinal function and tolerance of oral nutrition. Consecutive patients scheduled for abdominal surgery were randomized to the multimodal EON group or a group receiving conventional care. The primary endpoint was the time of first defecation. The secondary endpoints were outcomes and the cost-effectiveness ratio in treating infectious complications. The rate of infectious-free patients was regarded as the index of effectiveness. One hundred seven patients were randomly assigned to groups. Baseline characteristics were similar for both groups. In intention-to-treat analysis, the success rate of oral nutrition during the first week after surgery in the multimodal EON group was 44 (83.0%) versus 31 (57.4%) in the conventional care group (P = 0.004). Time to first defecation, time to flatus, recovery time of bowel sounds, and prolonged postoperative ileus were all less in the multimodal EON group (P < 0.05). The median postoperative length of stay in the multimodal EON group was 8 days (6, 12) versus 10 days (7, 18) in the conventional care group (P < 0.001). The total cost of treatment and nutritional support were also less in the multi-modal early oral nutrition group (P < 0.001). The effectiveness was 84.9 and 79.9% in the multimodal EON and conventional care group, respectively (P = 0.475). However, the cost-effectiveness ratio was USD 537.6 (506.1, 589.3) and USD 637.8 (593.9, 710.3), respectively (P < 0.001). The multi-modal early oral nutrition program was an effective way to improve tolerance of oral nutrition during the first week after surgery, decrease the length of stay and improve cost-effectiveness after abdominal surgery. Registration number: ChiCTR-TRC-14004395 . Registered 15 March 2014.

Multimodal Children's E-Books Help Young Learners in Reading

ERIC Educational Resources Information Center

Morgan, Hani

2013-01-01

Many children struggle with reading and are seldom engaged in this process when teachers assign them to read. Young learners may lack motivation to read an dislike this activity because they have had frequently have unpleasant experiences with reading. If educators fail to provide support for struggling readers, these pupils will likely experience…

"It's That Easy": Designing Assignments That Blend Old and New Literacies

ERIC Educational Resources Information Center

Connors, Sean P.; Sullivan, Racheal

2012-01-01

This article recounts what happened when one of the authors, a pre-service teacher, introduced a digital multimodal composition project in her 9th-grade inclusion English classes to support junior high students as they read the novel "To Kill a Mockingbird". Rather than regard new literacies as competing with print literacy for attention, the…

Randomized Trial of Three Child/Parent Training Groups for ADHD Children.

ERIC Educational Resources Information Center

Reddy, Linda; Braunstein, Dania; Springer, Craig; Bartik, Celina; Hauch, Yvonne; Hall, Tara; Benisz, Becky; Gioia, Lauren

The present study examined the effectiveness of a multimodal intervention for young children with ADHD. Fifty families were randomly assigned to three treatment conditions: (1) child group training only (N=18); (2) child and parent group training only (N=14); and (3) child and parent group training and parent/teacher consultation (N=18). Child,…

Study on the New Model of College English Teaching under the Setting of Multimodality

ERIC Educational Resources Information Center

Wang, Qian

2015-01-01

Currently, the application of the network resources and various means of teaching such as multimedia into the classroom has led to the demonstration of multimodality in college English teaching. This paper analyzes the current status of college English teaching and the existing problems, elaborates the research trends of the theory of multimodal…

Constructing and Using Multimodal Narratives to Research in Science Education: Contributions Based on Practical Classroom

ERIC Educational Resources Information Center

Lopes, J. B.; Silva, A. A.; Cravino, J. P.; Santos, C. A.; Cunha, A.; Pinto, A.; Silva, A.; Viegas, C.; Saraiva, E.; Branco, M. J.

2014-01-01

This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of…

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

Multimodal infiltration of local anaesthetic in total knee arthroplasty; is posterior capsular infiltration worth the risk? a prospective, double-blind, randomised controlled trial.

PubMed

Pinsornsak, P; Nangnual, S; Boontanapibul, K

2017-04-01

Multimodal infiltration of local anaesthetic provides effective control of pain in patients undergoing total knee arthroplasty (TKA). There is little information about the added benefits of posterior capsular infiltration (PCI) using different combinations of local anaesthetic agents. Our aim was to investigate the effectiveness of the control of pain using multimodal infiltration with and without infiltration of the posterior capsule of the knee. In a double-blind, randomised controlled trial of patients scheduled for unilateral primary TKA, 86 were assigned to be treated with multimodal infiltration with (Group I) or without (Group II) PCI. Routine associated analgesia included the use of bupivacaine, morphine, ketorolac and epinephrine. All patients had spinal anaesthesia and patient-controlled analgesia (PCA) post-operatively. A visual analogue scale (VAS) for pain and the use of morphine were recorded 24 hours post-operatively. Side effects of the infiltration, blood loss, and length of stay in hospital were recorded. There were no statistically significant differences between the groups in relation to: VAS pain scores in the first 24 hours post-operatively (p = 0.693), the use of morphine in the PCA (p = 0.647), blood loss (p = 0.625), and length of stay (p = 0.17). There were no neurovascular complications in either group. The multimodal infiltration of local anaesthetic with infiltration of the posterior capsule did not provide significant added analgesic benefits or reduce the use of morphine after TKA. Multimodal infiltration is a satisfactory technique for the management of pain in these patients without the attendant risks of PCI. Cite this article: Bone Joint J 2017; 99-B:483-8. ©2017 The British Editorial Society of Bone & Joint Surgery.

A 10-Week Multimodal Nutrition Education Intervention Improves Dietary Intake among University Students: Cluster Randomised Controlled Trial

PubMed Central

Wan Dali, Wan Putri Elena; Lua, Pei Lin

2013-01-01

The aim of the study was to evaluate the effectiveness of implementing multimodal nutrition education intervention (NEI) to improve dietary intake among university students. The design of study used was cluster randomised controlled design at four public universities in East Coast of Malaysia. A total of 417 university students participated in the study. They were randomly selected and assigned into two arms, that is, intervention group (IG) or control group (CG) according to their cluster. The IG received 10-week multimodal intervention using three modes (conventional lecture, brochures, and text messages) while CG did not receive any intervention. Dietary intake was assessed before and after intervention and outcomes reported as nutrient intakes as well as average daily servings of food intake. Analysis of covariance (ANCOVA) and adjusted effect size were used to determine difference in dietary changes between groups and time. Results showed that, compared to CG, participants in IG significantly improved their dietary intake by increasing their energy intake, carbohydrate, calcium, vitamin C and thiamine, fruits and 100% fruit juice, fish, egg, milk, and dairy products while at the same time significantly decreased their processed food intake. In conclusion, multimodal NEI focusing on healthy eating promotion is an effective approach to improve dietary intakes among university students. PMID:24069535

Intravenous Acetaminophen in Multimodal Pain Management for Patients Undergoing Total Knee Arthroplasty: A Randomized, Double-Blind, Placebo-Controlled Trial.

PubMed

Murata-Ooiwa, Minako; Tsukada, Sachiyuki; Wakui, Motohiro

2017-10-01

Although multimodal pain management including periarticular multidrug injection can provide excellent pain relief in the early postoperative period after total knee arthroplasty (TKA), rebounding pain remains an important challenge. A randomized, double-blind, placebo-controlled trial was performed to investigate the efficacy of adding intravenous acetaminophen to multimodal pain management for TKA. We enrolled 67 patients scheduled for unilateral TKA. Patients were randomly assigned to receive either 1000 mg of intravenous acetaminophen at 6-hour intervals or normal saline at the same intervals. All patients were treated with intraoperative periarticular multidrug injection and intravenous and oral nonsteroidal anti-inflammatory drugs. The primary outcome was the postoperative 100-mm visual analog pain scale at the time of administration of study drugs. In the intention-to-treat analysis, the pain score was significantly better in the intravenous acetaminophen group than the placebo group at 17:00 one day after TKA (15.3 ± 17.0 mm vs 26.8 ± 19.0 mm; P = .013). There were no significant differences in terms of the rate of complications between groups. Even in the setting of multimodal pain management including periarticular multidrug injection, intravenous acetaminophen provided better pain relief for patients undergoing unilateral TKA. Copyright © 2017 Elsevier Inc. All rights reserved.

Delinquent Behavior and Emerging Substance Use in the MTA at 36 Months: Prevalence, Course, and Treatment Effects

ERIC Educational Resources Information Center

Molina, Brooke S. G.; Flory, Kate; Hinshaw, Stephen P.; Greiner, Andrew R.; Arnold, L. Eugene; Swanson, James M.; Hechtman, Lily; Jensen, Peter S.; Vitiello, Benedetto; Hoza, Betsy; Pelham, William E.; Elliott, Glen R.; Wells, Karen C.; Abikoff, Howard B.; Gibbons, Robert D.; Marcus, Sue; Conners, C. Keith; Epstein, Jeffery N.; Greenhill, Laurence L.; March, John S.; Newcorn, Jeffrey H.; Severe, Joanne B.; Wigal, Timothy

2007-01-01

Objective: To compare delinquent behavior and early substance use between the children in the Multimodal Treatment Study of Children With ADHD (MTA; N = 487) and those in a local normative comparison group (n = 272) at 24 and 36 months postrandomization and to test whether these outcomes were predicted by the randomly assigned treatments and…

Ships/Trains/Planes/Automobiles: A Renaissance of their Interface

NASA Technical Reports Server (NTRS)

Allan, Stanley N.

1974-01-01

This paper highlights some of the major multi-modal interface problems created by technological advances, socio-political individualism and the flexibility of choices we expect from our transportation modes. The emphasis is on the need for a comprehensive national network of multi-modal priorities to enhance the movement of people and goods within the changing physical shape of our cities.

Multimodal Estimation of Distribution Algorithms.

PubMed

Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun

2016-02-15

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.

Event-Based Media Enrichment Using an Adaptive Probabilistic Hypergraph Model.

PubMed

Liu, Xueliang; Wang, Meng; Yin, Bao-Cai; Huet, Benoit; Li, Xuelong

2015-11-01

Nowadays, with the continual development of digital capture technologies and social media services, a vast number of media documents are captured and shared online to help attendees record their experience during events. In this paper, we present a method combining semantic inference and multimodal analysis for automatically finding media content to illustrate events using an adaptive probabilistic hypergraph model. In this model, media items are taken as vertices in the weighted hypergraph and the task of enriching media to illustrate events is formulated as a ranking problem. In our method, each hyperedge is constructed using the K-nearest neighbors of a given media document. We also employ a probabilistic representation, which assigns each vertex to a hyperedge in a probabilistic way, to further exploit the correlation among media data. Furthermore, we optimize the hypergraph weights in a regularization framework, which is solved as a second-order cone problem. The approach is initiated by seed media and then used to rank the media documents using a transductive inference process. The results obtained from validating the approach on an event dataset collected from EventMedia demonstrate the effectiveness of the proposed approach.

Offspring Generation Method for interactive Genetic Algorithm considering Multimodal Preference

NASA Astrophysics Data System (ADS)

Ito, Fuyuko; Hiroyasu, Tomoyuki; Miki, Mitsunori; Yokouchi, Hisatake

In interactive genetic algorithms (iGAs), computer simulations prepare design candidates that are then evaluated by the user. Therefore, iGA can predict a user's preferences. Conventional iGA problems involve a search for a single optimum solution, and iGA were developed to find this single optimum. On the other hand, our target problems have several peaks in a function and there are small differences among these peaks. For such problems, it is better to show all the peaks to the user. Product recommendation in shopping sites on the web is one example of such problems. Several types of preference trend should be prepared for users in shopping sites. Exploitation and exploration are important mechanisms in GA search. To perform effective exploitation, the offspring generation method (crossover) is very important. Here, we introduced a new offspring generation method for iGA in multimodal problems. In the proposed method, individuals are clustered into subgroups and offspring are generated in each group. The proposed method was applied to an experimental iGA system to examine its effectiveness. In the experimental iGA system, users can decide on preferable t-shirts to buy. The results of the subjective experiment confirmed that the proposed method enables offspring generation with consideration of multimodal preferences, and the proposed mechanism was also shown not to adversely affect the performance of preference prediction.

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

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

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less

Information Graphic Classification, Decomposition and Alternative Representation

ERIC Educational Resources Information Center

Gao, Jinglun

2012-01-01

This thesis work is mainly focused on two problems related to improving accessibility of information graphics for visually impaired users. The first problem is automated analysis of information graphics for information extraction and the second problem is multi-modal representations for accessibility. Information graphics are graphical…

A Closer Look at Bilingual Students' Use of Multimodality in the Context of an Area Comparison Problem from a Large-Scale Assessment

ERIC Educational Resources Information Center

Fernandes, Anthony; Kahn, Leslie H.; Civil, Marta

2017-01-01

In this article, we use multimodality to examine how bilingual students interact with an area task from the National Assessment of Educational Progress in task-based interviews. Using vignettes, we demonstrate how some of these students manipulate the concrete materials, and use gestures, as a primary form of structuring their explanations and…

Internet-Based Self-Help with Therapist Feedback and in Vivo Group Exposure for Social Phobia: A Randomized Controlled Trial

ERIC Educational Resources Information Center

Andersson, Gerhard; Carlbring, Per; Holmstrom, Annelie; Sparthan, Elisabeth; Furmark, Tomas; Nilsson-Ihrfelt, Elisabeth; Buhrman, Monica; Ekselius, Lisa

2006-01-01

Sixty-four individuals with social phobia (social anxiety disorder) were assigned to a multimodal cognitive-behavioral treatment package or to a waiting list control group. Treatment consisted of a 9-week, Internet-delivered, self-help program that was combined with 2 group exposure sessions in real life and minimal therapist contact via e-mail.…

Long-Term Improvements After Multimodal Rehabilitation in Late Phase After Stroke: A Randomized Controlled Trial.

PubMed

Bunketorp-Käll, Lina; Lundgren-Nilsson, Åsa; Samuelsson, Hans; Pekny, Tulen; Blomvé, Karin; Pekna, Marcela; Pekny, Milos; Blomstrand, Christian; Nilsson, Michael

2017-07-01

Treatments that improve function in late phase after stroke are urgently needed. We assessed whether multimodal interventions based on rhythm-and-music therapy or horse-riding therapy could lead to increased perceived recovery and functional improvement in a mixed population of individuals in late phase after stroke. Participants were assigned to rhythm-and-music therapy, horse-riding therapy, or control using concealed randomization, stratified with respect to sex and stroke laterality. Therapy was given twice a week for 12 weeks. The primary outcome was change in participants' perception of stroke recovery as assessed by the Stroke Impact Scale with an intention-to-treat analysis. Secondary objective outcome measures were changes in balance, gait, grip strength, and cognition. Blinded assessments were performed at baseline, postintervention, and at 3- and 6-month follow-up. One hundred twenty-three participants were assigned to rhythm-and-music therapy (n=41), horse-riding therapy (n=41), or control (n=41). Post-intervention, the perception of stroke recovery (mean change from baseline on a scale ranging from 1 to 100) was higher among rhythm-and-music therapy (5.2 [95% confidence interval, 0.79-9.61]) and horse-riding therapy participants (9.8 [95% confidence interval, 6.00-13.66]), compared with controls (-0.5 [-3.20 to 2.28]); P =0.001 (1-way ANOVA). The improvements were sustained in both intervention groups 6 months later, and corresponding gains were observed for the secondary outcomes. Multimodal interventions can improve long-term perception of recovery, as well as balance, gait, grip strength, and working memory in a mixed population of individuals in late phase after stroke. URL: http//www.ClinicalTrials.gov. Unique identifier: NCT01372059. © 2017 American Heart Association, Inc.

Multidimensional Functional Behaviour Assessment within a Problem Analysis Framework.

ERIC Educational Resources Information Center

Ryba, Ken; Annan, Jean

This paper presents a new approach to contextualized problem analysis developed for use with multimodal Functional Behaviour Assessment (FBA) at Massey University in Auckland, New Zealand. The aim of problem analysis is to simplify complex problems that are difficult to understand. It accomplishes this by providing a high order framework that can…

Joint sparse representation for robust multimodal biometrics recognition.

PubMed

Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama

2014-01-01

Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.

A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

NASA Astrophysics Data System (ADS)

Tian, Wenli; Cao, Chengxuan

2017-03-01

A generalized interval fuzzy mixed integer programming model is proposed for the multimodal freight transportation problem under uncertainty, in which the optimal mode of transport and the optimal amount of each type of freight transported through each path need to be decided. For practical purposes, three mathematical methods, i.e. the interval ranking method, fuzzy linear programming method and linear weighted summation method, are applied to obtain equivalents of constraints and parameters, and then a fuzzy expected value model is presented. A heuristic algorithm based on a greedy criterion and the linear relaxation algorithm are designed to solve the model.

[Mini-KiSS--a multimodal group therapy intervention for parents of young children with sleep disorders: a pilot study].

PubMed

Schlarb, Angelika Anita; Brandhorst, Isabel; Hautzinger, Martin

2011-05-01

Sleep disorders in early childhood tend to be chronic and almost always a burden for the parents. This study developed and evaluated a multimodal parent training program for children 0.5 to 4 years of age suffering from sleep disorders (Mini-KiSS). We hypothesized that there would be specific improvements following the structured group training (reduction of sleep problems, improvement of parental well-being). The pilot study consisted of a pre-post test design without control group. Participants were n = 17 parents of children 0.5 to 4 years of age with sleep disorders determined according to the ICSD-II. Each of the six sessions was evaluated, and changes were assessed by sleep diary and CBCL. Behavioral and emotional problems of the child were assessed by CBCL, parental well-being, and SCL-90-R. The results showed high acceptance of Mini-KiSS and satisfactory feasibility. Children showed significant improvements of the sleep disturbances such as nightly awakenings as well as sleeping in parents' bed. Furthermore, improvements were found for children's emotional and behavioral problems and for parental well-being, in particular for the depression scale of the mother. This pilot study shows a high acceptance and good feasibility of the multimodal short-time parent-training program Mini-KiSS. Sleep problems were significantly reduced.

Assignment Choice, Effort, and Assignment Completion: Does Work Ethic Predict Those Who Choose Higher-Effort Assignments?

ERIC Educational Resources Information Center

Parkhurst, John T.; Fleisher, Matthew S.; Skinner, Christopher H.; Woehr, David J.; Hawthorn-Embree, Meredith L.

2011-01-01

After completing the Multidimensional Work-Ethic Profile (MWEP), 98 college students were given a 20-problem math computation assignment and instructed to stop working on the assignment after completing 10 problems. Next, they were allowed to choose to finish either the partially completed assignment that had 10 problems remaining or a new…

A hybrid multimodal non-rigid registration of MR images based on diffeomorphic demons.

PubMed

Lu, Huanxiang; Cattin, Philippe C; Reyes, Mauricio

2010-01-01

In this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Study on multimodal transport route under low carbon background

NASA Astrophysics Data System (ADS)

Liu, Lele; Liu, Jie

2018-06-01

Low-carbon environmental protection is the focus of attention around the world, scientists are constantly researching on production of carbon emissions and living carbon emissions. However, there is little literature about multimodal transportation based on carbon emission at home and abroad. Firstly, this paper introduces the theory of multimodal transportation, the multimodal transport models that didn't consider carbon emissions and consider carbon emissions are analyzed. On this basis, a multi-objective programming 0-1 programming model with minimum total transportation cost and minimum total carbon emission is proposed. The idea of weight is applied to Ideal point method for solving problem, multi-objective programming is transformed into a single objective function. The optimal solution of carbon emission to transportation cost under different weights is determined by a single objective function with variable weights. Based on the model and algorithm, an example is given and the results are analyzed.

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Simulated annealing algorithm for solving chambering student-case assignment problem

NASA Astrophysics Data System (ADS)

Ghazali, Saadiah; Abdul-Rahman, Syariza

2015-12-01

The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.

Application of integral equation theory to analyze stability of electric field in multimode microwave heating cavity

NASA Astrophysics Data System (ADS)

Tang, Zhengming; Hong, Tao; Chen, Fangyuan; Zhu, Huacheng; Huang, Kama

2017-10-01

Microwave heating uniformity is mainly dependent on and affected by electric field. However, little study has paid attention to its stability characteristics in multimode cavity. In this paper, this problem is studied by the theory of Freedholm integral equation. Firstly, Helmholtz equation and the electric dyadic Green's function are used to derive the electric field integral equation. Then, the stability of electric field is demonstrated as the characteristics of solutions to Freedholm integral equation. Finally, the stability characteristics are obtained and verified by finite element calculation. This study not only can provide a comprehensive interpretation of electric field in multimode cavity but also help us make better use of microwave energy.

A multimodal interface to resolve the Midas-Touch problem in gaze controlled wheelchair.

PubMed

Meena, Yogesh Kumar; Cecotti, Hubert; Wong-Lin, KongFatt; Prasad, Girijesh

2017-07-01

Human-computer interaction (HCI) research has been playing an essential role in the field of rehabilitation. The usability of the gaze controlled powered wheelchair is limited due to Midas-Touch problem. In this work, we propose a multimodal graphical user interface (GUI) to control a powered wheelchair that aims to help upper-limb mobility impaired people in daily living activities. The GUI was designed to include a portable and low-cost eye-tracker and a soft-switch wherein the wheelchair can be controlled in three different ways: 1) with a touchpad 2) with an eye-tracker only, and 3) eye-tracker with soft-switch. The interface includes nine different commands (eight directions and stop) and integrated within a powered wheelchair system. We evaluated the performance of the multimodal interface in terms of lap-completion time, the number of commands, and the information transfer rate (ITR) with eight healthy participants. The analysis of the results showed that the eye-tracker with soft-switch provides superior performance with an ITR of 37.77 bits/min among the three different conditions (p<;0.05). Thus, the proposed system provides an effective and economical solution to the Midas-Touch problem and extended usability for the large population of disabled users.

Multimodal exercise intervention improves frontal cognitive functions and gait in Alzheimer's disease: a controlled trial.

PubMed

Coelho, Flávia Gomes de Melo; Andrade, Larissa Pires; Pedroso, Renata Valle; Santos-Galduroz, Ruth Ferreira; Gobbi, Sebastião; Costa, José Luiz Riani; Gobbi, Lilian Teresa Bucken

2013-01-01

The objective of the present study was to investigate the effect of a multimodal exercise intervention on frontal cognitive functions and kinematic gait parameters in patients with Alzheimer's disease. A sample of elderly patients with Alzheimer's disease (n=27) were assigned to a training group (n=14; aged 78.0±7.3 years) and a control group (n=13; aged 77.1±7.4 years). Multimodal exercise intervention includes motor activities and cognitive tasks simultaneously. The participants attended a 1-h session three times a week for 16 weeks, and the control participants maintained their regular daily activities during the same period. The frontal cognitive functions were evaluated using the Frontal Assessment Battery, the Clock Drawing Test and the Symbol Search Subtest. The kinematic parameters of gait-cadence, stride length and stride speed were analyzed under two conditions: (i) free gait (single task); and (ii) gait with frontal cognitive task (walking and counting down from 20--dual task). The patients in the intervention group significantly increased the scores in frontal cognitive variables, Frontal Assessment Battery (P<0.001) and Symbol Search Subtest (P<0.001) after the 16-week period. The control group decreased the scores in the Clock Drawing Test (P=0.001) and increased the number of counting errors during the dual task (P=0.008) after the same period. The multimodal exercise intervention improved the frontal cognitive functions in patients with Alzheimer's disease. © 2012 Japan Geriatrics Society.

Counseling Latinos with Substance Abuse Problems

ERIC Educational Resources Information Center

Torres-Rivera, Edil; Wilbur, Michael P.; Phan, Loan T.; Maddux, Cleborne D.; Roberts-Wilbur, Janice

2004-01-01

This article introduces a combination of approaches based on multicultural interventions and sociopolitical themes that provide interventions for working with Latinos with substance abuse problems. The purpose of the article is to view multimodal interventions, multicultural approaches, and humanistic counseling from a genetic perspective. It is…

A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

NASA Astrophysics Data System (ADS)

Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan

2015-02-01

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.

Hybrid genetic algorithm with an adaptive penalty function for fitting multimodal experimental data: application to exchange-coupled non-Kramers binuclear iron active sites.

PubMed

Beaser, Eric; Schwartz, Jennifer K; Bell, Caleb B; Solomon, Edward I

2011-09-26

A Genetic Algorithm (GA) is a stochastic optimization technique based on the mechanisms of biological evolution. These algorithms have been successfully applied in many fields to solve a variety of complex nonlinear problems. While they have been used with some success in chemical problems such as fitting spectroscopic and kinetic data, many have avoided their use due to the unconstrained nature of the fitting process. In engineering, this problem is now being addressed through incorporation of adaptive penalty functions, but their transfer to other fields has been slow. This study updates the Nanakorrn Adaptive Penalty function theory, expanding its validity beyond maximization problems to minimization as well. The expanded theory, using a hybrid genetic algorithm with an adaptive penalty function, was applied to analyze variable temperature variable field magnetic circular dichroism (VTVH MCD) spectroscopic data collected on exchange coupled Fe(II)Fe(II) enzyme active sites. The data obtained are described by a complex nonlinear multimodal solution space with at least 6 to 13 interdependent variables and are costly to search efficiently. The use of the hybrid GA is shown to improve the probability of detecting the global optimum. It also provides large gains in computational and user efficiency. This method allows a full search of a multimodal solution space, greatly improving the quality and confidence in the final solution obtained, and can be applied to other complex systems such as fitting of other spectroscopic or kinetics data.

APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies.

PubMed

Kanbar, Lara J; Shalish, Wissam; Precup, Doina; Brown, Karen; Sant'Anna, Guilherme M; Kearney, Robert E

2017-07-01

In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.

Facilitating role of 3D multimodal visualization and learning rehearsal in memory recall.

PubMed

Do, Phuong T; Moreland, John R

2014-04-01

The present study investigated the influence of 3D multimodal visualization and learning rehearsal on memory recall. Participants (N = 175 college students ranging from 21 to 25 years) were assigned to different training conditions and rehearsal processes to learn a list of 14 terms associated with construction of a wood-frame house. They then completed a memory test determining their cognitive ability to free recall the definitions of the 14 studied terms immediately after training and rehearsal. The audiovisual modality training condition was associated with the highest accuracy, and the visual- and auditory-modality conditions with lower accuracy rates. The no-training condition indicated little learning acquisition. A statistically significant increase in performance accuracy for the audiovisual condition as a function of rehearsal suggested the relative importance of rehearsal strategies in 3D observational learning. Findings revealed the potential application of integrating virtual reality and cognitive sciences to enhance learning and teaching effectiveness.

TDRSS multimode transponder program. Phase 2: Equipment development

NASA Technical Reports Server (NTRS)

Cnossen, R. S.

1974-01-01

This report contains a complete description of the TDRS Multimode Transponder and its associated ground support equipment. The transponder will demonstrate candidate modulation techniques to provide the required information for the design of an eventual VHF/UHF transponder suitable for installation in a user satellite, capable of operating as part of a Tracking and Data Relay Satellite (TDRS) systems. Use of geosynchronous TDRS which can serve both low data rate users at VHF and high data rate users at other frequencies has been considered. The effects of radio frequency interference from the earth and of multipath propagation due to reflections from the earth are expected to pose problems for the TDRS system at VHF. Investigations have suggested several modulation techniques that offer promise to overcome these problems.

Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks

DTIC Science & Technology

2012-09-30

transportation system to losses in es - tablished routes or assets? That is, what is the nature and length of system capability degradation due to these...Multimodal Rough-Cut Capacity Planning is mod- eled using the Resource Constrained Shortest Path Problem. We demonstrate how this approach supports...of non-zero ele - ments and the 0 entries depict appropriately dimensioned blocks of 0 entries.∣∣∣∣∑ k Ck ∣∣∣∣ Σ 0 0 0 0 Σ 0 0

A Multimodal Search Engine for Medical Imaging Studies.

PubMed

Pinho, Eduardo; Godinho, Tiago; Valente, Frederico; Costa, Carlos

2017-02-01

The use of digital medical imaging systems in healthcare institutions has increased significantly, and the large amounts of data in these systems have led to the conception of powerful support tools: recent studies on content-based image retrieval (CBIR) and multimodal information retrieval in the field hold great potential in decision support, as well as for addressing multiple challenges in healthcare systems, such as computer-aided diagnosis (CAD). However, the subject is still under heavy research, and very few solutions have become part of Picture Archiving and Communication Systems (PACS) in hospitals and clinics. This paper proposes an extensible platform for multimodal medical image retrieval, integrated in an open-source PACS software with profile-based CBIR capabilities. In this article, we detail a technical approach to the problem by describing its main architecture and each sub-component, as well as the available web interfaces and the multimodal query techniques applied. Finally, we assess our implementation of the engine with computational performance benchmarks.

Investigation of the bandwidth of multimode optical fibers used with 1550-nm LED and laser sources

NASA Technical Reports Server (NTRS)

White, Preston A., III

1992-01-01

Multimode optical fibers are not intended to be used with 1550-nm sources; however, it is desirable to utilize 1300/1550-nm wavelength division multiplexing (WDM) on some multimode fibers at Kennedy Space Center (KSC). No information from fiber vendors nor from the literature is available to support this use. Preliminary studies at KSC have suggested that these fibers might be usable at 1550-nm if the fibers possessed enough bandwidth when sourced by LEDs. Detailed bandwidth studies were made on 12 multimode fibers using 1300- and 1550-nm lasers and LEDs. The results showed that the modal bandwidth at 1550-nm was about 50 percent of the 1300-nm value and that the chromatic dispersion could be predicted by extrapolating the vendor's specifications for wavelengths outside the 1550-nm region. Utilizing these data, predictions of the fiber's optical bandwidth were accurately made. Problems with launch conditions and possible differential attenuation at connectors was noted at 1300-nm but was less significant at 1550-nm. It appears that the multimode fibers studied will offer adequate performance in the 1550-nm region for a number of current KSC needs. Studies of additional fibers are encouraged to gain more confidence and better understanding of the 1550-nm bandwidth of KSC's multimode optical fibers before committing to 1300/1550-nm WDM.

[Proactive screening for rehabilitation need in type 2 diabetics from an AOK Disease Management Programe: which patients will be identified?].

PubMed

Döbler, A; Pollmann, H; Raspe, H; Mittag, O

2014-02-01

Medical rehabilitation seems suitable for implementing multimodal interventions for the treatment of type 2 diabetes. Rehabilitation in Germany on principle requires that insurees file an application. Proactive screening for rehabilitation need has only been explored in pilot projects so far. It seems a promising attempt to assess rehab need by questionnaire especially in patients with type 2 diabetes. We do not know though how patients who have been screened positive for rehab need differ from other patients with type 2 diabetes as to their health and risk profiles. This could provide an indication of the validity of the proactive approach. Members of an Allgemeine Ortskrankenkasse (AOK) Disease Management Program (DMP) for type 2 diabetes were screened for rehab need by questionnaire. 13 diabetes-specific problem areas were assessed. Problems were assigned to 10 specific treatments (problem-treatment-pairs). Rehab need was presumed if patients needed 3 or more treatments. Patients were then compared to regular rehab patients as well as patients with type 2 diabetes from primary care medical offices. From 5500 DMP-patients 829 returned the questionnaire (return rate: 15.5%). From these 94% met the criteria for rehab need; of these 55% needed 6 or more treatments (complex problems). Patients who screened positive for rehab suffered from more health problems and had worse risk profiles as compared to patients from medical offices, and disease burden was comparable or worse as compared to regular rehab patients. This indicates that proactive screening for rehab need in patients with type 2 diabetes leads to reasonable (valid) results. The very low return rate suggests that the sample may be considerably biased, though. Possibly, mainly patients with greater impairment to health responded to the screening. © Georg Thieme Verlag KG Stuttgart · New York.

Wave envelope technique for multimode wave guide problems

NASA Technical Reports Server (NTRS)

Hariharan, S. I.; Sudharsanan, S. I.

1986-01-01

A fast method for solving wave guide problems is proposed. In particular, the guide is considered to be inhomogeneous allowing propagation of waves of higher order modes. Such problems have been handled successfully for acoustic wave propagation problems with single mode and finite length. This paper extends this concept to electromagnetic wave guides with several modes and infinite length. The method is described and results of computations are presented.

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

Adaptive Annealed Importance Sampling for Multimodal Posterior Exploration and Model Selection with Application to Extrasolar Planet Detection

NASA Astrophysics Data System (ADS)

Liu, Bin

2014-07-01

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior. To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.

Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

PubMed

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.

Impact of complete response to chemotherapy on overall survival in advanced colorectal cancer: results from Intergroup N9741.

PubMed

Dy, Grace K; Krook, James E; Green, Erin M; Sargent, Daniel J; Delaunoit, Thierry; Morton, Roscoe F; Fuchs, Charles S; Ramanathan, Ramesh K; Williamson, Stephen K; Findlay, Brian P; Pockaj, Barbara A; Sticca, Robert P; Alberts, Steven R; Pitot, Henry C; Goldberg, Richard M

2007-08-10

To evaluate clinical characteristics and survival outcomes among patients with locally advanced or metastatic colorectal cancer who achieve a complete response (CR) to systemic treatment either alone or with multimodality approach. Data were collected retrospectively from CRC patients enrolled onto the phase III trial N9741, a National Cancer Institute-funded and Gastrointestinal Cancer Intergroup-sponsored study coordinated by the North Central Cancer Treatment Group. Patients were randomly assigned to combinations of oxaliplatin, fluorouracil (FU)/leucovorin (LV) and irinotecan. The three treatment arms consist of IFL (irinotecan + FU/LV), FOLFOX4 (oxaliplatin + FU/LV), and IROX (irinotecan + oxaliplatin). Median follow-up was 42.6 months. Sixty-two (4%) of 1,508 patients had a CR to chemotherapy alone, and an additional 32 (2%) had a CR after multimodality treatment. Factors associated with achieving CR with systemic chemotherapy alone included FOLFOX4 treatment, patients with assessable disease, or a single site of metastasis. Continuing protocol treatment beyond two cycles after documentation of CR was not associated with improved survival. The rate of curative intent resection was significantly higher for patients treated with oxaliplatin-containing regimens (P = .02). Median survival was similar between patients with CR after chemotherapy alone (44.3 months) or after multimodality approach (47.4 months; P = .81). FOLFOX4 was more likely to produce a CR than were IFL or IROX. Oxaliplatin regimens were more likely to result in successful surgical resections. Patients who have CR to systemic chemotherapy alone can achieve impressive survival outcomes similar to those seen among patients who attained a CR status after multimodality treatment.

ADHD, Multimodal Treatment, and Longitudinal Outcome: Evidence, Paradox, and Challenge.

PubMed

Hinshaw, Stephen P; Arnold, L Eugene

2015-01-01

Given major increases in the diagnosis of attention-deficit hyperactivity disorder (ADHD) and in rates of medication for this condition, we carefully examine evidence for effects of single versus multimodal (i.e., combined medication and psychosocial/behavioral) interventions for ADHD. Our primary data source is the Multimodal Treatment Study of Children with ADHD (MTA), a 14-month, randomized clinical trial in which intensive behavioral, medication, and multimodal treatment arms were contrasted with one another and with community intervention (treatment-as-usual), regarding outcome domains of ADHD symptoms, comorbidities, and core functional impairments. Although initial reports emphasized the superiority of well-monitored medication for symptomatic improvement, reanalyses and reappraisals have highlighted (a) the superiority of combination treatment for composite outcomes and for domains of functional impairment (e.g., academic achievement, social skills, parenting practices); (b) the importance of considering moderator and mediator processes underlying differential patterns of outcome, including comorbid subgroups and improvements in family discipline style during the intervention period; (c) the emergence of side effects (e.g., mild growth suppression) in youth treated with long-term medication; and (d) the diminution of medication's initial superiority once the randomly assigned treatment phase turned into naturalistic follow-up. The key paradox is that whereas ADHD clearly responds to medication and behavioral treatment in the short term, evidence for long-term effectiveness remains elusive. We close with discussion of future directions and a call for greater understanding of relevant developmental processes in the attempt to promote optimal, generalized, and lasting treatments for this important and impairing neurodevelopmental disorder.

Attention-deficit hyperactivity disorder, multimodal treatment, and longitudinal outcome: evidence, paradox, and challenge.

PubMed

Hinshaw, Stephen P; Arnold, L Eugene

2015-01-01

Given major increases in the diagnosis of attention-deficit hyperactivity disorder (ADHD) and in rates of medication for this condition, we carefully examine evidence for effects of single versus multimodal (i.e., combined medication and psychosocial/behavioral) interventions for ADHD. Our primary data source is the Multimodal Treatment Study of Children with ADHD (MTA), a 14-month, randomized clinical trial in which intensive behavioral, medication, and multimodal treatment arms were contrasted with one another and with community intervention (treatment-as-usual), regarding outcome domains of ADHD symptoms, comorbidities, and core functional impairments. Although initial reports emphasized the superiority of well-monitored medication for symptomatic improvement, reanalyses and reappraisals have highlighted (1) the superiority of combination treatment for composite outcomes and for domains of functional impairment (e.g., academic achievement, social skills, parenting practices); (2) the importance of considering moderator and mediator processes underlying differential patterns of outcome, including comorbid subgroups and improvements in family discipline style during the intervention period; (3) the emergence of side effects (e.g., mild growth suppression) in youth treated with long-term medication; and (4) the diminution of medication's initial superiority once the randomly assigned treatment phase turned into naturalistic follow-up. The key paradox is that while ADHD clearly responds to medication and behavioral treatment in the short term, evidence for long-term effectiveness remains elusive. We close with discussion of future directions and a call for greater understanding of relevant developmental processes in the attempt to promote optimal, generalized, and lasting treatments for this important and impairing neurodevelopmental disorder. © 2014 John Wiley & Sons, Ltd.

TDRS multimode transponder program. Phase 1: Design

NASA Technical Reports Server (NTRS)

Cnossen, R. S.

1972-01-01

The use of geosynchronous tracking and data relay satellites (TDRS) which can serve both low data rate users at VHF and high data rate users at other frequencies is considered. The effects of radio frequency interference from the earth and of multipath propagation due to reflections from the earth are expected to pose problems for the TDRS system at VHF. Investigations suggest several modulation techniques that offer promise to overcome these problems. This report provides a complete design of a VHF/UHF multimode transponder and its associated ground support equipment. The transponder is designed for installation aboard an aircraft and will demonstrate candidate modulation techniques to provide the required information for the design of an eventual VHF/UHF transponder suitable for installation in a user satellite, capable of operating as part of a TDRS system.

Problem-Based Learning in Multimodal Learning Environments: Learners' Technology Adoption Experiences

ERIC Educational Resources Information Center

Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis

2016-01-01

In this study, we enhanced a problem-based learning (PBL) environment with affordable, everyday technologies that can be found in most university classrooms (e.g., projectors, tablets, students' own smartphones, traditional paper-pencil, and Facebook). The study was conducted over a 3-year period, with 60 postgraduate learners in a human-computer…

Multimode squeezing, biphotons and uncertainty relations in polarization quantum optics

NASA Technical Reports Server (NTRS)

Karassiov, V. P.

1994-01-01

The concept of squeezing and uncertainty relations are discussed for multimode quantum light with the consideration of polarization. Using the polarization gauge SU(2) invariance of free electromagnetic fields, we separate the polarization and biphoton degrees of freedom from other ones, and consider uncertainty relations characterizing polarization and biphoton observables. As a consequence, we obtain a new classification of states of unpolarized (and partially polarized) light within quantum optics. We also discuss briefly some interrelations of our analysis with experiments connected with solving some fundamental problems of physics.

NaGdF4:Nd3+/Yb3+ Nanoparticles as Multimodal Imaging Agents

NASA Astrophysics Data System (ADS)

Pedraza, Francisco; Rightsell, Chris; Kumar, Ga; Giuliani, Jason; Monton, Car; Sardar, Dhiraj

Medical imaging is a fundamental tool used for the diagnosis of numerous ailments. Each imaging modality has unique advantages; however, they possess intrinsic limitations. Some of which include low spatial resolution, sensitivity, penetration depth, and radiation damage. To circumvent this problem, the combination of imaging modalities, or multimodal imaging, has been proposed, such as Near Infrared Fluorescence imaging (NIRF) and Magnetic Resonance Imaging (MRI). Combining individual advantages, specificity and selectivity of NIRF with the deep penetration and high spatial resolution of MRI, it is possible to circumvent their shortcomings for a more robust imaging technique. In addition, both imaging modalities are very safe and minimally invasive. Fluorescent nanoparticles, such as NaGdF4:Nd3 +/Yb3 +, are excellent candidates for NIRF/MRI multimodal imaging. The dopants, Nd and Yb, absorb and emit within the biological window; where near infrared light is less attenuated by soft tissue. This results in less tissue damage and deeper tissue penetration making it a viable candidate in biological imaging. In addition, the inclusion of Gd results in paramagnetic properties, allowing their use as contrast agents in multimodal imaging. The work presented will include crystallographic results, as well as full optical and magnetic characterization to determine the nanoparticle's viability in multimodal imaging.

Unifying Temporal and Structural Credit Assignment Problems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2004-01-01

Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions. Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these two forms of the credit assignment problem are equivalent. In this unified frame-work, a single-agent Markov decision process can be broken down into a single-time-step multi-agent process. Furthermore we show that Monte-Carlo estimation or Q-learning (depending on whether the values of resulting actions in the episode are known at the time of learning) are equivalent to different agent utility functions in a multi-agent system. This equivalence shows how an often neglected issue in multi-agent systems is equivalent to a well-known deficiency in multi-time-step learning and lays the basis for solving time-extended multi-agent problems, where both credit assignment problems are present.

A Scenario-Based Parametric Analysis of Stable Marriage Approaches to the Army Officer Assignment Problem

DTIC Science & Technology

2017-03-23

solutions obtained through their proposed method to comparative instances of a generalized assignment problem with either ordinal cost components or... method flag: Designates the method by which the changed/ new assignment problem instance is solved. methodFlag = 0:SMAWarmstart Returns a matching...of randomized perturbations. We examine the contrasts between these methods in the context of assigning Army Officers among a set of identified

Optimal processor assignment for pipeline computations

NASA Technical Reports Server (NTRS)

Nicol, David M.; Simha, Rahul; Choudhury, Alok N.; Narahari, Bhagirath

1991-01-01

The availability of large scale multitasked parallel architectures introduces the following processor assignment problem for pipelined computations. Given a set of tasks and their precedence constraints, along with their experimentally determined individual responses times for different processor sizes, find an assignment of processor to tasks. Two objectives are of interest: minimal response given a throughput requirement, and maximal throughput given a response time requirement. These assignment problems differ considerably from the classical mapping problem in which several tasks share a processor; instead, it is assumed that a large number of processors are to be assigned to a relatively small number of tasks. Efficient assignment algorithms were developed for different classes of task structures. For a p processor system and a series parallel precedence graph with n constituent tasks, an O(np2) algorithm is provided that finds the optimal assignment for the response time optimization problem; it was found that the assignment optimizing the constrained throughput in O(np2log p) time. Special cases of linear, independent, and tree graphs are also considered.

A robust probabilistic collaborative representation based classification for multimodal biometrics

NASA Astrophysics Data System (ADS)

Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

2018-04-01

Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

A Multiple Ant Colony Metahuristic for the Air Refueling Tanker Assignment Problem

DTIC Science & Technology

2002-03-01

Problem The tanker assignment problem can be modeled as a job shop scheduling problem ( JSSP ). The JSSP is made up of n jobs, composed of m ordered...points) to be processed on all the machines (tankers). The problem with using JSSP is that the tanker assignment problem has multiple objectives... JSSP will minimize the time it takes for all jobs, but this may take an inordinate number of tankers. Thus using JSSP alone is not necessarily a good

Achieving spectrum conservation for the minimum-span and minimum-order frequency assignment problems

NASA Technical Reports Server (NTRS)

Heyward, Ann O.

1992-01-01

Effective and efficient solutions of frequency assignment problems assumes increasing importance as the radiofrequency spectrum experiences ever increasing utilization by diverse communications services, requiring that the most efficient use of this resource be achieved. The research presented explores a general approach to the frequency assignment problem, in which such problems are categorized by the appropriate spectrum conserving objective function, and are each treated as an N-job, M-machine scheduling problem appropriate for the objective. Results obtained and presented illustrate that such an approach presents an effective means of achieving spectrum conserving frequency assignments for communications systems in a variety of environments.

Multimode ergometer system

NASA Technical Reports Server (NTRS)

Bynum, B. G.; Gause, R. L.; Spier, R. A.

1971-01-01

System overcomes previous ergometer design and calibration problems including inaccurate measurements, large weight, size, and input power requirements, poor heat dissipation, high flammability, and inaccurate calibration. Device consists of lightweight, accurately controlled ergometer, restraint system, and calibration system.

The sixth generation robot in space

NASA Technical Reports Server (NTRS)

Butcher, A.; Das, A.; Reddy, Y. V.; Singh, H.

1990-01-01

The knowledge based simulator developed in the artificial intelligence laboratory has become a working test bed for experimenting with intelligent reasoning architectures. With this simulator, recently, small experiments have been done with an aim to simulate robot behavior to avoid colliding paths. An automatic extension of such experiments to intelligently planning robots in space demands advanced reasoning architectures. One such architecture for general purpose problem solving is explored. The robot, seen as a knowledge base machine, goes via predesigned abstraction mechanism for problem understanding and response generation. The three phases in one such abstraction scheme are: abstraction for representation, abstraction for evaluation, and abstraction for resolution. Such abstractions require multimodality. This multimodality requires the use of intensional variables to deal with beliefs in the system. Abstraction mechanisms help in synthesizing possible propagating lattices for such beliefs. The machine controller enters into a sixth generation paradigm.

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets.

PubMed

Scharfe, Michael; Pielot, Rainer; Schreiber, Falk

2010-01-11

Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics.

Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

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

Tajaldini, Mehdi; Young Researchers and Elite Club, Baft Branch, Islamic Azad University, Baft; Jafri, Mohd Zubir Mat

2015-04-24

We propose an ultra-compact multimode interference (MMI) power splitter based on nonlinear effects from simulations using nonlinear modal propagation analysis (NMPA) cooperation with finite difference Method (FDM) to access free choice of splitting ratio. Conventional multimode interference power splitter could only obtain a few discrete ratios. The power splitting ratio may be adjusted continuously while the input set power is varying by a tunable laser. In fact, using an ultra- compact MMI with a simple structure that is launched by a tunable nonlinear input fulfills the problem of arbitrary-ratio in integrated photonics circuits. Silicon on insulator (SOI) is used asmore » the offered material due to the high contrast refractive index and Centro symmetric properties. The high-resolution images at the end of the multimode waveguide in the simulated power splitter have a high power balance, whereas access to a free choice of splitting ratio is not possible under the linear regime in the proposed length range except changes in the dimension for any ratio. The compact dimensions and ideal performance of the device are established according to optimized parameters. The proposed regime can be extended to the design of M×N arbitrary power splitters ratio for programmable logic devices in all optical digital signal processing. The results of this study indicate that nonlinear modal propagation analysis solves the miniaturization problem for all-optical devices based on MMI couplers to achieve multiple functions in a compact planar integrated circuit and also overcomes the limitations of previously proposed methods for nonlinear MMI.« less

ADAPTIVE ANNEALED IMPORTANCE SAMPLING FOR MULTIMODAL POSTERIOR EXPLORATION AND MODEL SELECTION WITH APPLICATION TO EXTRASOLAR PLANET DETECTION

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

Liu, Bin, E-mail: bins@ieee.org

2014-07-01

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior.more » To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.« less

Effectiveness of core stability exercises and recovery myofascial release massage on fatigue in breast cancer survivors: a randomized controlled clinical trial.

PubMed

Cantarero-Villanueva, Irene; Fernández-Lao, Carolina; Del Moral-Avila, Rosario; Fernández-de-Las-Peñas, César; Feriche-Fernández-Castanys, María Belén; Arroyo-Morales, Manuel

2012-01-01

The purpose of the present paper was to evaluate the effects of an 8-week multimodal program focused on core stability exercises and recovery massage with DVD support for a 6-month period in physical and psychological outcomes in breast cancer survivors. A randomized controlled clinical trial was performed. Seventy-eight (n = 78) breast cancer survivors were assigned to experimental (core stability exercises plus massage-myofascial release) and control (usual health care) groups. The intervention period was 8 weeks. Mood state, fatigue, trunk curl endurance, and leg strength were determined at baseline, after the last treatment session, and at 6 months of followup. Immediately after treatment and at 6 months, fatigue, mood state, trunk curl endurance, and leg strength exhibited greater improvement within the experimental group compared to placebo group. This paper showed that a multimodal program focused on core stability exercises and massage reduced fatigue, tension, depression, and improved vigor and muscle strength after intervention and 6 months after discharge.

A randomized controlled trial of multimodal music therapy for children with anxiety disorders.

PubMed

Goldbeck, Lutz; Ellerkamp, Thomas

2012-01-01

Music therapy has been shown to be effective for children with psychopathology, providing an alternative nonverbal approach to the treatment of children with anxiety disorders. This pilot study investigates the efficacy of Multimodal Music Therapy (MMT), a combination of music therapy and cognitive-behavioral therapy, compared to treatment as usual (TAU). Thirty-six children aged 8-12 years with a primary diagnosis of an anxiety disorder were randomly assigned to 15 sessions of MMT or to TAU. Diagnostic status and dimensional outcome variables were assessed at the end of treatment and 4 months later. MMT was superior compared to TAU according to the remission rates after treatment (MMT 67%; TAU 33%; chi2 = 4.0; p = 0.046) and remissions persisted until four months post-treatment. Dimensional measures showed equivalent improvement after either MMT or TAU. The results regarding the efficacy of MMT are promising for children with anxiety disorders. Further evaluation with larger samples and comparisons to pure CBT are recommended.

System and method for ultrasonic tomography

DOEpatents

Haddad, Waleed Sami

2002-01-01

A system and method for doing both transmission mode and reflection mode three-dimensional ultrasonic imagining. The multimode imaging capability may be used to provide enhanced detectability of cancer tumors within human breast, however, similar imaging systems are applicable to a number of other medical problems as well as a variety of non-medical problems in non-destructive evaluation (NDE).

Multimodal exercise training in multiple sclerosis: A randomized controlled trial in persons with substantial mobility disability.

PubMed

Sandroff, Brian M; Bollaert, Rachel E; Pilutti, Lara A; Peterson, Melissa L; Baynard, Tracy; Fernhall, Bo; McAuley, Edward; Motl, Robert W

2017-10-01

Mobility disability is a common, debilitating feature of multiple sclerosis (MS). Exercise training has been identified as an approach to improve MS-related mobility disability. However, exercise randomized controlled trials (RCTs) on mobility in MS have generally not selectively targeted those with the onset of irreversible mobility disability. The current multi-site RCT compared the efficacy of 6-months of supervised, multimodal exercise training with an active control condition for improving mobility, gait, physical fitness, and cognitive outcomes in persons with substantial MS-related mobility disability. 83 participants with substantial MS-related mobility disability underwent initial mobility, gait, fitness, and cognitive processing speed assessments and were randomly assigned to 6-months of supervised multimodal (progressive aerobic, resistance, and balance) exercise training (intervention condition) or stretching-and-toning activities (control condition). Participants completed the same outcome assessments halfway through and immediately following the 6-month study period. There were statistically significant improvements in six-minute walk performance (F(2158)=3.12, p=0.05, η p 2 =0.04), peak power output (F(2150)=8.16, p<0.01, η p 2 =0.10), and Paced Auditory Serial Addition Test performance (F(2162)=4.67, p=0.01, η p 2 =0.05), but not gait outcomes, for those who underwent the intervention compared with those who underwent the control condition. This RCT provides novel, preliminary evidence that multimodal exercise training may improve endurance walking performance and cognitive processing speed, perhaps based on improvements in cardiorespiratory capacity, in persons with MS with substantial mobility disability. This is critical for informing the development of multi-site exercise rehabilitation programs in larger samples of persons with MS-related mobility disability. Copyright © 2017 Elsevier Inc. All rights reserved.

A 3-week multimodal intervention involving high-intensity interval training in female cancer survivors: a randomized controlled trial.

PubMed

Schmitt, Joachim; Lindner, Nathalie; Reuss-Borst, Monika; Holmberg, Hans-Christer; Sperlich, Billy

2016-02-01

To compare the effects of a 3-week multimodal rehabilitation involving supervised high-intensity interval training (HIIT) on female breast cancer survivors with respect to key variables of aerobic fitness, body composition, energy expenditure, cancer-related fatigue, and quality of life to those of a standard multimodal rehabilitation program. A randomized controlled trial design was administered. Twenty-eight women, who had been treated for cancer were randomly assigned to either a group performing exercise of low-to-moderate intensity (LMIE; n = 14) or a group performing high-intensity interval training (HIIT; n = 14) as part of a 3-week multimodal rehabilitation program. No adverse events related to the exercise were reported. Work economy improved following both HIIT and LMIE, with improved peak oxygen uptake following LMIE. HIIT reduced mean total body fat mass with no change in body mass, muscle or fat-free mass (best P < 0.06). LMIE increased muscle and total fat-free body mass. Total energy expenditure (P = 0.45) did not change between the groups, whereas both improved quality of life to a similar high extent and lessened cancer-related fatigue. This randomized controlled study demonstrates that HIIT can be performed by female cancer survivors without adverse health effects. Here, HIIT and LMIE both improved work economy, quality of life and cancer-related fatigue, body composition or energy expenditure. Since the outcomes were similar, but HIIT takes less time, this may be a time-efficient strategy for improving certain aspects of the health of female cancer survivors. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

PubMed Central

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970

Improving Access to Transit Through Crowdsourced Information

DOT National Transportation Integrated Search

2017-11-01

The purpose of this research was to facilitate the ongoing collection of information from the public about potential areas of multimodal service and infrastructure improvements and easily share these problems with transit agencies, departments of tra...

An Efficacy Study of Interleaved Mathematics Practice. Revised

ERIC Educational Resources Information Center

Rohrer, Doug; Dedrick, Robert F.; Burgess, Kaleena

2013-01-01

In a typical mathematics course, the material is divided into many lessons, and each lesson is followed by an assignment consisting of practice problems. Most commonly, each assignment consists solely of problems on the preceding lesson. For example, a lesson on ratios might be followed by an assignment with 12 problems on ratios. In other words,…

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiple-mode reconfigurable electro-optic switching network for optical fiber sensor array

NASA Technical Reports Server (NTRS)

Chen, Ray T.; Wang, Michael R.; Jannson, Tomasz; Baumbick, Robert

1991-01-01

This paper reports the first switching network compatible with multimode fibers. A one-to-many cascaded reconfigurable interconnection was built. A thin glass substrate was used as the guiding medium which provides not only higher coupling efficiency from multimode fiber to waveguide but also better tolerance of phase-matching conditions. Involvement of a total-internal-reflection hologram and multimode waveguide eliminates interface problems between fibers and waveguides. The DCG polymer graft has proven to be reliable from -180 C to +200 C. Survivability of such an electrooptic system in harsh environments is further ensured. LiNbO3 was chosen as the E-O material because of its stability at high temperatures (phase-transition temperature of more than 1000 C) and maturity of E-O device technology. Further theoretical calculation was conducted to provide the optimal interaction length and device capacitance.

Degradation of Multimode Adhesive System Bond Strength to Artificial Caries-Affected Dentin Due to Water Storage.

PubMed

Follak, A C; Miotti, L L; Lenzi, T L; Rocha, R O; Soares, F Z

The purpose of this study was to evaluate the influence of water storage on bond strength of multimode adhesive systems to artificially induced caries-affected dentin. One hundred twelve sound bovine incisors were randomly assigned to 16 groups (n=7) according to the dentin condition (sound; SND, artificially induced caries-affected dentin; CAD, cariogenic challenge by pH cycling for 14 days); the adhesive system (SU, Scotchbond Universal Adhesive; AB, All-Bond Universal; PB, Prime & Bond Elect; SB, Adper Single Bond 2; and CS, Clearfil SE Bond), and the etching strategy (etch-and-rinse and self-etch). All adhesive systems were applied under manufacturer's instructions to flat dentin surfaces, and a composite block was built up on each dentin surface. After 24 hours of water storage, the specimens were sectioned into stick-shaped specimens (0.8 mm 2 ) and submitted to a microtensile test immediately (24 hours) or after six months of water storage. Bond strength data (MPa) were analyzed using three-way repeated-measures analysis of variance and post hoc Tukey test (α=5%), considering each substrate separately (SND and CAD). The etching strategy did not influence the bond strength of multimode adhesives, irrespective of the dentin condition. Water storage only reduced significantly the bond strength to CAD. The degradation of bond strength due to water storage was more pronounced in CAD, regardless of the etching strategy.

Quantum teleportation of nonclassical wave packets: An effective multimode theory

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

Benichi, Hugo; Takeda, Shuntaro; Lee, Noriyuki

2011-07-15

We develop a simple and efficient theoretical model to understand the quantum properties of broadband continuous variable quantum teleportation. We show that, if stated properly, the problem of multimode teleportation can be simplified to teleportation of a single effective mode that describes the input state temporal characteristic. Using that model, we show how the finite bandwidth of squeezing and external noise in the classical channel affect the output teleported quantum field. We choose an approach that is especially relevant for the case of non-Gaussian nonclassical quantum states and we finally back-test our model with recent experimental results.

Single Machine Scheduling and Due Date Assignment with Past-Sequence-Dependent Setup Time and Position-Dependent Processing Time

PubMed Central

Zhao, Chuan-Li; Hsu, Hua-Feng

2014-01-01

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved in O(n 4) time. For the model with job-independent position effects, we proved that the problems can be solved in O(n 3) time by providing a dynamic programming algorithm. PMID:25258727

Single machine scheduling and due date assignment with past-sequence-dependent setup time and position-dependent processing time.

PubMed

Zhao, Chuan-Li; Hsu, Chou-Jung; Hsu, Hua-Feng

2014-01-01

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved in O(n(4)) time. For the model with job-independent position effects, we proved that the problems can be solved in O(n(3)) time by providing a dynamic programming algorithm.

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

DOE PAGES

Li, Weixuan; Lin, Guang

2015-03-21

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes’ rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle thesemore » challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.« less

Multimodal optical imager for inner ear hearing loss diagnosis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Park, Jesung; Maguluri, Gopi N.; Zhao, Youbo; Iftimia, Nicusor V.

2017-02-01

Sensorineural hearing loss (SNHL), which typically originates in the cochlea, is the most common otologic problem caused by aging and noise trauma. The cochlea, a delicate and complex biological mechanosensory transducer in the inner ear, has been extensively studied with the goal of improving diagnosis of SNHL. However, the difficulty associated with accessing the cochlea and resolving the microstructures that facilitate hearing within it in a minimally-invasive way has prevented us from being able to assess the pathology underlying SNHL in humans. To address this problem we investigated the ability of a multimodal optical system that combines optical coherence tomography (OCT) and single photon autofluorescence imaging (AFI) to enable visualization and evaluation of microstructures in the cochlea. A laboratory OCT/AFI imager was built to acquire high resolution OCT and single photon fluorescence images of the cochlea. The imager's ability to resolve diagnostically-relevant details was evaluated in ears extracted from normal and noise-exposed mice. A prototype endoscopic OCT/AFI imager was developed based on a double-clad fiber approach. Our measurements show that the multimodal OCT/AFI imager can be used to evaluate structural integrity in the mouse cochlea. Therefore, we believe that this technology is promising as a potential clinical evaluation tool, and as a technique for guiding otologic surgeries such as cochlear implant surgery.

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

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

Li, Weixuan; Lin, Guang, E-mail: guanglin@purdue.edu

2015-08-01

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes' rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle thesemore » challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.« less

QUICR-learning for Multi-Agent Coordination

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2006-01-01

Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit must be assigned for an action taken at time step t that results in a reward at time step t > t. Second, credit must be assigned for the contribution of agent i to the overall system performance. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning. The second credit assignment problem is typically addressed by creating custom reward functions. To address both credit assignment problems simultaneously, we propose the "Q Updates with Immediate Counterfactual Rewards-learning" (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. QUICR-learning is based on previous work on single-time-step counterfactual rewards described by the collectives framework. Results on a traffic congestion problem shows that QUICR-learning is significantly better than a Q-learner using collectives-based (single-time-step counterfactual) rewards. In addition QUICR-learning provides significant gains over conventional and local Q-learning. Additional results on a multi-agent grid-world problem show that the improvements due to QUICR-learning are not domain specific and can provide up to a ten fold increase in performance over existing methods.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing.

PubMed

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-10-23

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

Measuring Conceptual Gains and Benefits of Student Problem Designs

NASA Astrophysics Data System (ADS)

Mandell, Eric; Snyder, Rachel; Oswald, Wayne

2011-10-01

Writing assignments can be an effective way of getting students to practice higher-order learning skills in physics. One example of such an assignment is that of problem design. One version of the problem design assignment asks the student to evaluate the material from a chapter, after all instruction and other activities are complete. The student is to decide what concepts and ideas are most central, or critical in the chapter, and construct a problem that he or she feels best encompasses the major themes. Here, we use two concept surveys (FCI and EMCS) to measure conceptual gains for students completing the problem design assignment and present the preliminary results, comparing across several categories including gender, age, degree program, and class standing.

Implementation of a rehabilitation model for employees on long-term sick leave in the public sector: difficulties, counter-measures, and outcomes.

PubMed

Heijbel, Bodil; Josephson, Malin; Vingård, Eva

2013-01-01

The aim was threefold: 1) to describe the experiences of driving and implementing a workplace-based rehabilitation intervention in cooperation with the occupational health service (OHS); 2) to investigate which people received multimodal and/or vocational rehabilitation measures; 3) to find predictors of return to work (RTW). Altogether 779 employees on sick leave for 90 days or more with mainly musculoskeletal or psychological/stress-related problems, 90% women. The HAKuL model was introduced, implying an early team assessment at the OHS and good access to rehabilitation measures. The study is a prospective three-year study with a two-year follow-up. The rehabilitation intervention encountered challenges. Counter-measures were taken to facilitate coordination and communication. People with musculoskeletal problems often received both multimodal and vocational rehabilitation. Vocational rehabilitation was advocated for people who were under 55 years of age, and for those with stress-related problems. The strongest predictive factors for RTW were: having received only vocational rehabilitation and being under 45 years of age. The HAKuL model can be used in a wider context, but the study shows the need for coordination between multiple stakeholders. Supervisors should pay attention to people who have musculoskeletal problems and are older, as soon as problems emerge.

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism

PubMed Central

Cox, Benjamin L; Mackie, Thomas R; Eliceiri, Kevin W

2015-01-01

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with 18F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents. PMID:25625022

Towards an ultra-thin medical endoscope: multimode fibre as a wide-field image transferring medium

NASA Astrophysics Data System (ADS)

Duriš, Miroslav; Bradu, Adrian; Podoleanu, Adrian; Hughes, Michael

2018-03-01

Multimode optical fibres are attractive for biomedical and industrial applications such as endoscopes because of the small cross section and imaging resolution they can provide in comparison to widely-used fibre bundles. However, the image is randomly scrambled by propagation through a multimode fibre. Even though the scrambling is unpredictable, it is deterministic, and therefore the scrambling can be reversed. To unscramble the image, we treat the multimode fibre as a linear, disordered scattering medium. To calibrate, we scan a focused beam of coherent light over thousands of different beam positions at the distal end and record complex fields at the proximal end of the fibre. This way, the inputoutput response of the system is determined, which then allows computational reconstruction of reflection-mode images. However, there remains the problem of illuminating the tissue via the fibre while avoiding back reflections from the proximal face. To avoid this drawback, we provide here the first preliminary confirmation that an image can be transferred through a 2x2 fibre coupler, with the sample at its distal port interrogated in reflection. Light is injected into one port for illumination and then collected from a second port for imaging.

Multi-mode ultra-strong coupling (I): spectroscopic experiments using a vacuum-gap transmon circuit architecture

NASA Astrophysics Data System (ADS)

Bosman, Sal J.; Gely, Mario F.; Singh, Vibhor; Bruno, Alessandro; Bothner, Daniel; Steele, Gary A.

In circuit QED, multi-mode extensions of the quantum Rabi model suffer from divergence problems. Here, we spectroscopically study multi-mode ultra-strong coupling using a transmon circuit architecture, which provides no clear guidelines on how many modes play a role in the dynamics of the system. As our transmon qubit, we employ a suspended island above the voltage anti-node of a λ / 4 coplanar microwave resonator, thereby realising a circuit where 88% of the qubit capacitance is formed by a vacuum-gap capacitor with the center conductor of the resonator. We measure vacuum Rabi splitting over multiple modes up to 2 GHz, reaching coupling ratios of g / ω = 0 . 18 , well within the ultra-strong coupling regime. We observe a qubit-mediated mode coupling, measurable up to the fifth mode at 38 GHz. Using a novel analytical quantum circuit model of this architecture, which includes all modes without introducing divergencies, we are able to fit the full spectrum and extract a vacuum fluctuations induced Bloch-Siegert shift of up to 62 MHz. This circuit architecture expands the versatility of the transmon technology platform and opens many possibilities in multi-mode physics in the ultra-strong coupling regime.

The airport gate assignment problem: a survey.

PubMed

Bouras, Abdelghani; Ghaleb, Mageed A; Suryahatmaja, Umar S; Salem, Ahmed M

2014-01-01

The airport gate assignment problem (AGAP) is one of the most important problems operations managers face daily. Many researches have been done to solve this problem and tackle its complexity. The objective of the task is assigning each flight (aircraft) to an available gate while maximizing both conveniences to passengers and the operational efficiency of airport. This objective requires a solution that provides the ability to change and update the gate assignment data on a real time basis. In this paper, we survey the state of the art of these problems and the various methods to obtain the solution. Our survey covers both theoretical and real AGAP with the description of mathematical formulations and resolution methods such as exact algorithms, heuristic algorithms, and metaheuristic algorithms. We also provide a research trend that can inspire researchers about new problems in this area.

The Airport Gate Assignment Problem: A Survey

PubMed Central

Ghaleb, Mageed A.; Salem, Ahmed M.

2014-01-01

The airport gate assignment problem (AGAP) is one of the most important problems operations managers face daily. Many researches have been done to solve this problem and tackle its complexity. The objective of the task is assigning each flight (aircraft) to an available gate while maximizing both conveniences to passengers and the operational efficiency of airport. This objective requires a solution that provides the ability to change and update the gate assignment data on a real time basis. In this paper, we survey the state of the art of these problems and the various methods to obtain the solution. Our survey covers both theoretical and real AGAP with the description of mathematical formulations and resolution methods such as exact algorithms, heuristic algorithms, and metaheuristic algorithms. We also provide a research trend that can inspire researchers about new problems in this area. PMID:25506074

Some problems associated with the analysis and interpretation of mixed carbonate and quartz beach sands, illustrated by examples from North-West Ireland

NASA Astrophysics Data System (ADS)

Carter, R. W. G.

1982-09-01

Mixes of carbonate and quartz sands, which are commonly encountered in Recent coastal sediments, require careful analysis if they are to be correctly interpreted. Grain-size data fall into multimodal or segmented zig-zag distributions which may require some kind of component separation if they are to be summarised by conventional statistics, and before they can be assigned to a particular hydrodynamic depositional process or environment. Unfortunately, separation techniques are only spasmodically applied, usually without due regard to the consequences. Such artificially filtered or truncated distributions are of little subsequent use. Using a range of samples from two beaches in NW Ireland, where carbonate proportions range from nearly zero to over sixty percent, the interrelationships of the two dominant components were examined. Where only a small carbonate proportion is incorporated into a large quartz one, predictable modifications of the size-curve are apparent. However, the components are more independent if mixtures are near equal. The occurrence of a number of distinctive combinations of simple straight lines and complex zig-zag curves probably reflects the relatively dynamic nature of the carbonate fraction.

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets

PubMed Central

2010-01-01

Background Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. Results We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. Conclusions The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics. PMID:20064262

Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2014-11-01

For the last decade, it has been shown that neuroimaging can be a potential tool for the diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), and also fusion of different modalities can further provide the complementary information to enhance diagnostic accuracy. Here, we focus on the problems of both feature representation and fusion of multimodal information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). To our best knowledge, the previous methods in the literature mostly used hand-crafted features such as cortical thickness, gray matter densities from MRI, or voxel intensities from PET, and then combined these multimodal features by simply concatenating into a long vector or transforming into a higher-dimensional kernel space. In this paper, we propose a novel method for a high-level latent and shared feature representation from neuroimaging modalities via deep learning. Specifically, we use Deep Boltzmann Machine (DBM)(2), a deep network with a restricted Boltzmann machine as a building block, to find a latent hierarchical feature representation from a 3D patch, and then devise a systematic method for a joint feature representation from the paired patches of MRI and PET with a multimodal DBM. To validate the effectiveness of the proposed method, we performed experiments on ADNI dataset and compared with the state-of-the-art methods. In three binary classification problems of AD vs. healthy Normal Control (NC), MCI vs. NC, and MCI converter vs. MCI non-converter, we obtained the maximal accuracies of 95.35%, 85.67%, and 74.58%, respectively, outperforming the competing methods. By visual inspection of the trained model, we observed that the proposed method could hierarchically discover the complex latent patterns inherent in both MRI and PET. Copyright © 2014 Elsevier Inc. All rights reserved.

Hierarchical Feature Representation and Multimodal Fusion with Deep Learning for AD/MCI Diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2014-01-01

For the last decade, it has been shown that neuroimaging can be a potential tool for the diagnosis of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), and also fusion of different modalities can further provide the complementary information to enhance diagnostic accuracy. Here, we focus on the problems of both feature representation and fusion of multimodal information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). To our best knowledge, the previous methods in the literature mostly used hand-crafted features such as cortical thickness, gray matter densities from MRI, or voxel intensities from PET, and then combined these multimodal features by simply concatenating into a long vector or transforming into a higher-dimensional kernel space. In this paper, we propose a novel method for a high-level latent and shared feature representation from neuroimaging modalities via deep learning. Specifically, we use Deep Boltzmann Machine (DBM)1, a deep network with a restricted Boltzmann machine as a building block, to find a latent hierarchical feature representation from a 3D patch, and then devise a systematic method for a joint feature representation from the paired patches of MRI and PET with a multimodal DBM. To validate the effectiveness of the proposed method, we performed experiments on ADNI dataset and compared with the state-of-the-art methods. In three binary classification problems of AD vs. healthy Normal Control (NC), MCI vs. NC, and MCI converter vs. MCI non-converter, we obtained the maximal accuracies of 95.35%, 85.67%, and 74.58%, respectively, outperforming the competing methods. By visual inspection of the trained model, we observed that the proposed method could hierarchically discover the complex latent patterns inherent in both MRI and PET. PMID:25042445

Advanced Public Transportation Systems (Apts) Project Summaries, June 1996, Office Of Mobility

DOT National Transportation Integrated Search

1996-06-01

ITS APPLIES STATE-OF-THE-ART AND EMERGING TECHNOLOGIES TO PROVIDE MORE EFFICIENT AND EFFECTIVE SOLUTIONS TO CURRENT MULTIMODAL TRANSPORTATION PROBLEMS, AS WELL AS ANTICIPATE AND ADDRESS FUTURE TRANSPORTATION DEMANDS THROUGH AN INTERMODAL, STRATEGIC A...

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

PubMed Central

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-01-01

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650

Linguistic Challenges in the Mathematical Register for EFL Learners: Linguistic and Multimodal Strategies to Help Learners Tackle Mathematics Word Problems

ERIC Educational Resources Information Center

Chan, Simon

2015-01-01

In learning mathematics through English, one of the major challenges facing English as a Foreign Language (EFL) learners is understanding the language used to present word problems in mathematics texts. Without comprehending such language, learners are not able to carry out the targeted calculations no matter how familiar they are with the…

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

The mobility and safety of walk-and-ride systems.

DOT National Transportation Integrated Search

2015-03-01

In this project we investigate the effect of traffic calming measures, such as crosswalks and sidewalks on the overall cost and safety of a multimodal transportation network system design. Our design problem includes auto, transit, and walking as mod...

Decision Making In Assignment Problem With Multiple Attributes Under Intuitionistic Fuzzy Environment

NASA Astrophysics Data System (ADS)

Mukherjee, Sathi; Basu, Kajla

2010-10-01

In this paper we develop a methodology to solve the multiple attribute assignment problems where the attributes are considered to be Intuitionistic Fuzzy Sets (IFS). We apply the concept of similarity measures of IFS to solve the Intuitionistic Fuzzy Multi-Attribute Assignment Problem (IFMAAP). The weights of the attributes are determined from expert opinion. An illustrative example is solved to verify the developed approach and to demonstrate its practicality.

The addition of upper cervical manipulative therapy in the treatment of patients with fibromyalgia: a randomized controlled trial.

PubMed

Moustafa, Ibrahim M; Diab, Aliaa A

2015-07-01

The aim of this study was to investigate the immediate and long-term effects of a one-year multimodal program, with the addition of upper cervical manipulative therapy, on fibromyalgia management outcomes in addition to three-dimensional (3D) postural measures. This randomized clinical trial with one-year follow-up was completed at the research laboratory of our university. A total of 120 (52 female) patients with fibromyalgia syndrome (FMS) and definite C1-2 joint dysfunction were randomly assigned to the control or an experimental group. Both groups received a multimodal program; additionally, the experimental group received upper cervical manipulative therapy. Primary outcomes were the Fibromyalgia Impact Questionnaire (FIQ), whereas secondary outcomes included Pain Catastrophizing Scale (PCS), algometric score, Pittsburgh Sleep Quality Index (PSQI), Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), and 3D postural measures. Measures were assessed at three time intervals: baseline, 12 weeks, and 1 year after the 12-week follow-up. The general linear model with repeated measures indicated a significant group × time effect in favor of the experimental group on the measures of 3D postural parameters (P < .0005), FIQ (P < .0005), PCS (P < .0005), algometric score (F = P < .0005), PSQI (P < .0005), BAI (P < .0005), and BDI (P < .0005). The addition of the upper cervical manipulative therapy to a multimodal program is beneficial in treating patients with FMS.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

NASA Astrophysics Data System (ADS)

Ismail, M. A.; Said, M. N.

2014-06-01

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis.

Multimodal correlation and intraoperative matching of virtual models in neurosurgery

NASA Technical Reports Server (NTRS)

Ceresole, Enrico; Dalsasso, Michele; Rossi, Aldo

1994-01-01

The multimodal correlation between different diagnostic exams, the intraoperative calibration of pointing tools and the correlation of the patient's virtual models with the patient himself, are some examples, taken from the biomedical field, of a unique problem: determine the relationship linking representation of the same object in different reference frames. Several methods have been developed in order to determine this relationship, among them, the surface matching method is one that gives the patient minimum discomfort and the errors occurring are compatible with the required precision. The surface matching method has been successfully applied to the multimodal correlation of diagnostic exams such as CT, MR, PET and SPECT. Algorithms for automatic segmentation of diagnostic images have been developed to extract the reference surfaces from the diagnostic exams, whereas the surface of the patient's skull has been monitored, in our approach, by means of a laser sensor mounted on the end effector of an industrial robot. An integrated system for virtual planning and real time execution of surgical procedures has been realized.

Robust QRS peak detection by multimodal information fusion of ECG and blood pressure signals.

PubMed

Ding, Quan; Bai, Yong; Erol, Yusuf Bugra; Salas-Boni, Rebeca; Zhang, Xiaorong; Hu, Xiao

2016-11-01

QRS peak detection is a challenging problem when ECG signal is corrupted. However, additional physiological signals may also provide information about the QRS position. In this study, we focus on a unique benchmark provided by PhysioNet/Computing in Cardiology Challenge 2014 and Physiological Measurement focus issue: robust detection of heart beats in multimodal data, which aimed to explore robust methods for QRS detection in multimodal physiological signals. A dataset of 200 training and 210 testing records are used, where the testing records are hidden for evaluating the performance only. An information fusion framework for robust QRS detection is proposed by leveraging existing ECG and ABP analysis tools and combining heart beats derived from different sources. Results show that our approach achieves an overall accuracy of 90.94% and 88.66% on the training and testing datasets, respectively. Furthermore, we observe expected performance at each step of the proposed approach, as an evidence of the effectiveness of our approach. Discussion on the limitations of our approach is also provided.

Projective filtering of the fundamental eigenmode from spatially multimode radiation

NASA Astrophysics Data System (ADS)

Pérez, A. M.; Sharapova, P. R.; Straupe, S. S.; Miatto, F. M.; Tikhonova, O. V.; Leuchs, G.; Chekhova, M. V.

2015-11-01

Lossless filtering of a single coherent (Schmidt) mode from spatially multimode radiation is a problem crucial for optics in general and for quantum optics in particular. It becomes especially important in the case of nonclassical light that is fragile to optical losses. An example is bright squeezed vacuum generated via high-gain parametric down conversion or four-wave mixing. Its highly multiphoton and multimode structure offers a huge increase in the information capacity provided that each mode can be addressed separately. However, the nonclassical signature of bright squeezed vacuum, photon-number correlations, are highly susceptible to losses. Here we demonstrate lossless filtering of a single spatial Schmidt mode by projecting the spatial spectrum of bright squeezed vacuum on the eigenmode of a single-mode fiber. Moreover, we show that the first Schmidt mode can be captured by simply maximizing the fiber-coupled intensity. Importantly, the projection operation does not affect the targeted mode and leaves it usable for further applications.

A pricing approach for mitigating congestion in multimodal transportation systems.

DOT National Transportation Integrated Search

2010-02-19

The problem addressed in this research is to determine usage prices for a system with : multiple modes of transportation with the objective of reducing congestion. With multiple : modes, these prices can take on several forms. On road networks, the u...

Improvement in cognitive and psychosocial functioning and self image among adolescent inpatient suicide attempters.

PubMed

Hintikka, Ulla; Marttunen, Mauri; Pelkonen, Mirjami; Laukkanen, Eila; Viinamäki, Heimo; Lehtonen, Johannes

2006-12-29

Psychiatric treatment of suicidal youths is often difficult and non-compliance in treatment is a significant problem. This prospective study compared characteristics and changes in cognitive functioning, self image and psychosocial functioning among 13 to 18 year-old adolescent psychiatric inpatients with suicide attempts (n = 16) and with no suicidality (n = 39) The two-group pre-post test prospective study design included assessments by a psychiatrist, a psychologist and medical staff members as well as self-rated measures. DSM-III-R diagnoses were assigned using the SCID and thereafter transformed to DSM-IV diagnoses. Staff members assessed psychosocial functioning using the Global Assessment Scale (GAS). Cognitive performance was assessed using the Wechsler Adult Intelligence Scale, while the Offer Self-Image Questionnaire (OSIQ) was used to assess the subjects' self-image. ANCOVA with repeated measures was used to test changes from entry to discharge among the suicide attempters and non suicidal patients. Logistic regression modeling was used to assess variables associated with an improvement of 10 points or more in the GAS score. Among suicide attempter patients, psychosocial functioning, cognitive performance and both the psychological self and body-image improved during treatment and their treatment compliance and outcome were as good as that of the non-suicidal patients. Suicidal ideation and hopelessness declined, and psychosocial functioning improved. Changes in verbal cognitive performance were more pronounced among the suicide attempters. Having an improved body-image associated with a higher probability of improvement in psychosocial functioning while higher GAS score at entry was associated with lower probability of functional improvement in both patient groups. These findings illustrate that a multimodal treatment program seems to improve psychosocial functioning and self-image among severely disordered suicidal adolescent inpatients. There were no changes in familial relationships, possibly indicating a need for more intensive family interventions when treating suicidal youths. Multimodal inpatient treatment including an individual therapeutic relationship seems recommendable for severely impaired psychiatric inpatients tailored to the suicidal adolescent's needs.

Evaluation of a Brief Homework Assignment Designed to Reduce Citation Problems

ERIC Educational Resources Information Center

Schuetze, Pamela

2004-01-01

I evaluated a brief homework assignment designed to reduce citation problems in research-based term papers. Students in 2 developmental psychology classes received a brief presentation and handout defining plagiarism with tips on how to cite sources to avoid plagiarizing. In addition, students in 1 class completed 2 brief homework assignments in…

Absolute Points for Multiple Assignment Problems

ERIC Educational Resources Information Center

Adlakha, V.; Kowalski, K.

2006-01-01

An algorithm is presented to solve multiple assignment problems in which a cost is incurred only when an assignment is made at a given cell. The proposed method recursively searches for single/group absolute points to identify cells that must be loaded in any optimal solution. Unlike other methods, the first solution is the optimal solution. The…

Computing Role Assignments of Proper Interval Graphs in Polynomial Time

NASA Astrophysics Data System (ADS)

Heggernes, Pinar; van't Hof, Pim; Paulusma, Daniël

A homomorphism from a graph G to a graph R is locally surjective if its restriction to the neighborhood of each vertex of G is surjective. Such a homomorphism is also called an R-role assignment of G. Role assignments have applications in distributed computing, social network theory, and topological graph theory. The Role Assignment problem has as input a pair of graphs (G,R) and asks whether G has an R-role assignment. This problem is NP-complete already on input pairs (G,R) where R is a path on three vertices. So far, the only known non-trivial tractable case consists of input pairs (G,R) where G is a tree. We present a polynomial time algorithm that solves Role Assignment on all input pairs (G,R) where G is a proper interval graph. Thus we identify the first graph class other than trees on which the problem is tractable. As a complementary result, we show that the problem is Graph Isomorphism-hard on chordal graphs, a superclass of proper interval graphs and trees.

Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

Multimodal user interfaces to improve social integration of elderly and mobility impaired.

PubMed

Dias, Miguel Sales; Pires, Carlos Galinho; Pinto, Fernando Miguel; Teixeira, Vítor Duarte; Freitas, João

2012-01-01

Technologies for Human-Computer Interaction (HCI) and Communication have evolved tremendously over the past decades. However, citizens such as mobility impaired or elderly or others, still face many difficulties interacting with communication services, either due to HCI issues or intrinsic design problems with the services. In this paper we start by presenting the results of two user studies, the first one conducted with a group of mobility impaired users, comprising paraplegic and quadriplegic individuals; and the second one with elderly. The study participants carried out a set of tasks with a multimodal (speech, touch, gesture, keyboard and mouse) and multi-platform (mobile, desktop) system, offering an integrated access to communication and entertainment services, such as email, agenda, conferencing, instant messaging and social media, referred to as LHC - Living Home Center. The system was designed to take into account the requirements captured from these users, with the objective of evaluating if the adoption of multimodal interfaces for audio-visual communication and social media services, could improve the interaction with such services. Our study revealed that a multimodal prototype system, offering natural interaction modalities, especially supporting speech and touch, can in fact improve access to the presented services, contributing to the reduction of social isolation of mobility impaired, as well as elderly, and improving their digital inclusion.

Web-Based Problem-Solving Assignment and Grading System

NASA Astrophysics Data System (ADS)

Brereton, Giles; Rosenberg, Ronald

2014-11-01

In engineering courses with very specific learning objectives, such as fluid mechanics and thermodynamics, it is conventional to reinforce concepts and principles with problem-solving assignments and to measure success in problem solving as an indicator of student achievement. While the modern-day ease of copying and searching for online solutions can undermine the value of traditional assignments, web-based technologies also provide opportunities to generate individualized well-posed problems with an infinite number of different combinations of initial/final/boundary conditions, so that the probability of any two students being assigned identical problems in a course is vanishingly small. Such problems can be designed and programmed to be: single or multiple-step, self-grading, allow students single or multiple attempts; provide feedback when incorrect; selectable according to difficulty; incorporated within gaming packages; etc. In this talk, we discuss the use of a homework/exam generating program of this kind in a single-semester course, within a web-based client-server system that ensures secure operation.

Bi-orthogonality relations for fluid-filled elastic cylindrical shells: Theory, generalisations and application to construct tailored Green's matrices

NASA Astrophysics Data System (ADS)

Ledet, Lasse S.; Sorokin, Sergey V.

2018-03-01

The paper addresses the classical problem of time-harmonic forced vibrations of a fluid-filled cylindrical shell considered as a multi-modal waveguide carrying infinitely many waves. The forced vibration problem is solved using tailored Green's matrices formulated in terms of eigenfunction expansions. The formulation of Green's matrix is based on special (bi-)orthogonality relations between the eigenfunctions, which are derived here for the fluid-filled shell. Further, the relations are generalised to any multi-modal symmetric waveguide. Using the orthogonality relations the transcendental equation system is converted into algebraic modal equations that can be solved analytically. Upon formulation of Green's matrices the solution space is studied in terms of completeness and convergence (uniformity and rate). Special features and findings exposed only through this modal decomposition method are elaborated and the physical interpretation of the bi-orthogonality relation is discussed in relation to the total energy flow which leads to derivation of simplified equations for the energy flow components.

A hardware and software architecture to deal with multimodal and collaborative interactions in multiuser virtual reality environments

NASA Astrophysics Data System (ADS)

Martin, P.; Tseu, A.; Férey, N.; Touraine, D.; Bourdot, P.

2014-02-01

Most advanced immersive devices provide collaborative environment within several users have their distinct head-tracked stereoscopic point of view. Combining with common used interactive features such as voice and gesture recognition, 3D mouse, haptic feedback, and spatialized audio rendering, these environments should faithfully reproduce a real context. However, even if many studies have been carried out on multimodal systems, we are far to definitively solve the issue of multimodal fusion, which consists in merging multimodal events coming from users and devices, into interpretable commands performed by the application. Multimodality and collaboration was often studied separately, despite of the fact that these two aspects share interesting similarities. We discuss how we address this problem, thought the design and implementation of a supervisor that is able to deal with both multimodal fusion and collaborative aspects. The aim of this supervisor is to ensure the merge of user's input from virtual reality devices in order to control immersive multi-user applications. We deal with this problem according to a practical point of view, because the main requirements of this supervisor was defined according to a industrial task proposed by our automotive partner, that as to be performed with multimodal and collaborative interactions in a co-located multi-user environment. In this task, two co-located workers of a virtual assembly chain has to cooperate to insert a seat into the bodywork of a car, using haptic devices to feel collision and to manipulate objects, combining speech recognition and two hands gesture recognition as multimodal instructions. Besides the architectural aspect of this supervisor, we described how we ensure the modularity of our solution that could apply on different virtual reality platforms, interactive contexts and virtual contents. A virtual context observer included in this supervisor in was especially designed to be independent to the content of the virtual scene of targeted application, and is use to report high-level interactive and collaborative events. This context observer allows the supervisor to merge these interactive and collaborative events, but is also used to deal with new issues coming from our observation of two co-located users in an immersive device performing this assembly task. We highlight the fact that when speech recognition features are provided to the two users, it is required to automatically detect according to the interactive context, whether the vocal instructions must be translated into commands that have to be performed by the machine, or whether they take a part of the natural communication necessary for collaboration. Information coming from this context observer that indicates a user is looking at its collaborator, is important to detect if the user is talking to its partner. Moreover, as the users are physically co-localised and head-tracking is used to provide high fidelity stereoscopic rendering, and natural walking navigation in the virtual scene, we have to deals with collision and screen occlusion between the co-located users in the physical work space. Working area and focus of each user, computed and reported by the context observer is necessary to prevent or avoid these situations.

A Memetic Algorithm for Global Optimization of Multimodal Nonseparable Problems.

PubMed

Zhang, Geng; Li, Yangmin

2016-06-01

It is a big challenging issue of avoiding falling into local optimum especially when facing high-dimensional nonseparable problems where the interdependencies among vector elements are unknown. In order to improve the performance of optimization algorithm, a novel memetic algorithm (MA) called cooperative particle swarm optimizer-modified harmony search (CPSO-MHS) is proposed in this paper, where the CPSO is used for local search and the MHS for global search. The CPSO, as a local search method, uses 1-D swarm to search each dimension separately and thus converges fast. Besides, it can obtain global optimum elements according to our experimental results and analyses. MHS implements the global search by recombining different vector elements and extracting global optimum elements. The interaction between local search and global search creates a set of local search zones, where global optimum elements reside within the search space. The CPSO-MHS algorithm is tested and compared with seven other optimization algorithms on a set of 28 standard benchmarks. Meanwhile, some MAs are also compared according to the results derived directly from their corresponding references. The experimental results demonstrate a good performance of the proposed CPSO-MHS algorithm in solving multimodal nonseparable problems.

Change in self-esteem predicts depressive symptoms at follow-up after intensive multimodal psychotherapy for major depression.

PubMed

Dinger, Ulrike; Ehrenthal, Johannes C; Nikendei, Christoph; Schauenburg, Henning

2017-09-01

Reduced self-esteem is a core symptom of depression, but few studies have investigated within-treatment change of self-esteem as a predictor of long-term outcome in depression. This study investigated change in self-esteem during 8 weeks of multimodal, psychodynamically oriented psychotherapy for 40 depressed patients and tested whether it would predict outcome 6 months after termination. Data was drawn from a randomized clinical pilot trial on day-clinic versus inpatient psychotherapy for depression. Findings supported the association between change in self-esteem and follow-up depression severity, even when controlling for within-treatment symptom change. Change in self-esteem was not related to overall symptoms and interpersonal problems at follow-up. Thus, change in self-esteem may be an important variable in preventing relapse for depression. Self-esteem is related to depressive symptoms and interpersonal problems. Improvement of self-esteem during psychotherapy correlates with improvements of symptoms and interpersonal problems. Change of self-esteem during psychotherapy predicts depressive symptoms 6 months after termination of therapy. When treating depressed patients, psychotherapists should work towards an improvement of self-esteem in order to prevent relapse. Copyright © 2017 John Wiley & Sons, Ltd.

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

An Adaptive Niching Genetic Algorithm using a niche size equalization mechanism

NASA Astrophysics Data System (ADS)

Nagata, Yuichi

Niching GAs have been widely investigated to apply genetic algorithms (GAs) to multimodal function optimization problems. In this paper, we suggest a new niching GA that attempts to form niches, each consisting of an equal number of individuals. The proposed GA can be applied also to combinatorial optimization problems by defining a distance metric in the search space. We apply the proposed GA to the job-shop scheduling problem (JSP) and demonstrate that the proposed niching method enhances the ability to maintain niches and improve the performance of GAs.

Ten Years of Entrepreneurship Education at Chinese Universities: Evolution, Problems, and System Building

ERIC Educational Resources Information Center

Weiming, Li; Chunyan, Li; Xiaohua, Du

2016-01-01

Entrepreneurship education has experienced four stages of development in Chinese universities, shifting from entrepreneurship show to entrepreneurship education, from teacher training to student education, from classroom teaching to multimodal teaching, and from imparting knowledge to cultivating skills. Currently, the weak links in…

Single-machine common/slack due window assignment problems with linear decreasing processing times

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Lin, Win-Chin; Wu, Wen-Hsiang; Wu, Chin-Chia

2017-08-01

This paper studies linear non-increasing processing times and the common/slack due window assignment problems on a single machine, where the actual processing time of a job is a linear non-increasing function of its starting time. The aim is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Some optimality results are discussed for the common/slack due window assignment problems and two O(n log n) time algorithms are presented to solve the two problems. Finally, two examples are provided to illustrate the correctness of the corresponding algorithms.

Learning graph matching.

PubMed

Caetano, Tibério S; McAuley, Julian J; Cheng, Li; Le, Quoc V; Smola, Alex J

2009-06-01

As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. Many formulations of this problem can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility and a quadratic term encodes edge compatibility. The main research focus in this theme is about designing efficient algorithms for approximately solving the quadratic assignment problem, since it is NP-hard. In this paper we turn our attention to a different question: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the 'labels' are matches between them. Our experimental results reveal that learning can substantially improve the performance of standard graph matching algorithms. In particular, we find that simple linear assignment with such a learning scheme outperforms Graduated Assignment with bistochastic normalisation, a state-of-the-art quadratic assignment relaxation algorithm.

a New Multimodal Multi-Criteria Route Planning Model by Integrating a Fuzzy-Ahp Weighting Method and a Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Ghaderi, F.; Pahlavani, P.

2015-12-01

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user's bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.

More reliable protein NMR peak assignment via improved 2-interval scheduling.

PubMed

Chen, Zhi-Zhong; Lin, Guohui; Rizzi, Romeo; Wen, Jianjun; Xu, Dong; Xu, Ying; Jiang, Tao

2005-03-01

Protein NMR peak assignment refers to the process of assigning a group of "spin systems" obtained experimentally to a protein sequence of amino acids. The automation of this process is still an unsolved and challenging problem in NMR protein structure determination. Recently, protein NMR peak assignment has been formulated as an interval scheduling problem (ISP), where a protein sequence P of amino acids is viewed as a discrete time interval I (the amino acids on P one-to-one correspond to the time units of I), each subset S of spin systems that are known to originate from consecutive amino acids from P is viewed as a "job" j(s), the preference of assigning S to a subsequence P of consecutive amino acids on P is viewed as the profit of executing job j(s) in the subinterval of I corresponding to P, and the goal is to maximize the total profit of executing the jobs (on a single machine) during I. The interval scheduling problem is max SNP-hard in general; but in the real practice of protein NMR peak assignment, each job j(s) usually requires at most 10 consecutive time units, and typically the jobs that require one or two consecutive time units are the most difficult to assign/schedule. In order to solve these most difficult assignments, we present an efficient 13/7-approximation algorithm for the special case of the interval scheduling problem where each job takes one or two consecutive time units. Combining this algorithm with a greedy filtering strategy for handling long jobs (i.e., jobs that need more than two consecutive time units), we obtain a new efficient heuristic for protein NMR peak assignment. Our experimental study shows that the new heuristic produces the best peak assignment in most of the cases, compared with the NMR peak assignment algorithms in the recent literature. The above algorithm is also the first approximation algorithm for a nontrivial case of the well-known interval scheduling problem that breaks the ratio 2 barrier.

Single machine scheduling with slack due dates assignment

NASA Astrophysics Data System (ADS)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.

A Stochastic Employment Problem

ERIC Educational Resources Information Center

Wu, Teng

2013-01-01

The Stochastic Employment Problem(SEP) is a variation of the Stochastic Assignment Problem which analyzes the scenario that one assigns balls into boxes. Balls arrive sequentially with each one having a binary vector X = (X[subscript 1], X[subscript 2],...,X[subscript n]) attached, with the interpretation being that if X[subscript i] = 1 the ball…

A General Chemistry Assignment Analyzing Environmental Contamination for the Depue, IL, National Superfund Site

ERIC Educational Resources Information Center

Saslow Gomez, Sarah A.; Faurie-Wisniewski, Danielle; Parsa, Arlen; Spitz, Jeff; Spitz, Jennifer Amdur; Loeb, Nancy C.; Geiger, Franz M.

2015-01-01

The classroom exercise outlined here is a self-directed assignment that connects students to the environmental contamination problem surrounding the DePue Superfund site. By connecting chemistry knowledge gained in the classroom with a real-world problem, students are encouraged to personally connect with the problem while simultaneously…

Modality-Driven Classification and Visualization of Ensemble Variance

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

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no informationmore » about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.« less

Internet-Based Assessment of Oncology Health Care Professional Learning Style and Optimization of Materials for Web-Based Learning: Controlled Trial With Concealed Allocation

PubMed Central

Micheel, Christine M; Anderson, Ingrid A; Lee, Patricia; Chen, Sheau-Chiann; Justiss, Katy; Giuse, Nunzia B; Ye, Fei; Kusnoor, Sheila V

2017-01-01

Background Precision medicine has resulted in increasing complexity in the treatment of cancer. Web-based educational materials can help address the needs of oncology health care professionals seeking to understand up-to-date treatment strategies. Objective This study aimed to assess learning styles of oncology health care professionals and to determine whether learning style-tailored educational materials lead to enhanced learning. Methods In all, 21,465 oncology health care professionals were invited by email to participate in the fully automated, parallel group study. Enrollment and follow-up occurred between July 13 and September 7, 2015. Self-enrolled participants took a learning style survey and were assigned to the intervention or control arm using concealed alternating allocation. Participants in the intervention group viewed educational materials consistent with their preferences for learning (reading, listening, and/or watching); participants in the control group viewed educational materials typical of the My Cancer Genome website. Educational materials covered the topic of treatment of metastatic estrogen receptor-positive (ER+) breast cancer using cyclin-dependent kinases 4/6 (CDK4/6) inhibitors. Participant knowledge was assessed immediately before (pretest), immediately after (posttest), and 2 weeks after (follow-up test) review of the educational materials. Study statisticians were blinded to group assignment. Results A total of 751 participants enrolled in the study. Of these, 367 (48.9%) were allocated to the intervention arm and 384 (51.1%) were allocated to the control arm. Of those allocated to the intervention arm, 256 (69.8%) completed all assessments. Of those allocated to the control arm, 296 (77.1%) completed all assessments. An additional 12 participants were deemed ineligible and one withdrew. Of the 552 participants, 438 (79.3%) self-identified as multimodal learners. The intervention arm showed greater improvement in posttest score compared to the control group (0.4 points or 4.0% more improvement on average; P=.004) and a higher follow-up test score than the control group (0.3 points or 3.3% more improvement on average; P=.02). Conclusions Although the study demonstrated more learning with learning style-tailored educational materials, the magnitude of increased learning and the largely multimodal learning styles preferred by the study participants lead us to conclude that future content-creation efforts should focus on multimodal educational materials rather than learning style-tailored content. PMID:28743680

Sensory Aids for the Blind.

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC. Committee on Prosthetics Research and Development.

The problems of providing sensory aids for the blind are presented and a report on the present status of aids discusses direct translation and recognition reading machines as well as mobility aids. Aspects of required research considered are the following: assessment of needs; vision, audition, taction, and multimodal communication; reading aids,…

Peer-Mediated Reading and Writing in a Digital, Multimodal Environment

ERIC Educational Resources Information Center

Fitzgerald, Miranda S.; Palincsar, Annemarie Sullivan

2017-01-01

The goals for engaging students in peer learning range from positioning students as knowledgeable others to promoting social-emotional learning goals to providing contexts in which students can articulate and compare their thinking to supporting opportunities to cogenerate solutions to complex problems. There are a number of complexities…

The Joint Organization of Interaction within a Multimodal CSCL Medium

ERIC Educational Resources Information Center

Cakir, Murat Perit; Zemel, Alan; Stahl, Gerry

2009-01-01

In order to collaborate effectively in group discourse on a topic like mathematical patterns, group participants must organize their activities in ways that share the significance of their utterances, inscriptions, and behaviors. Here, we report the results of a ethnomethodological case study of collaborative math problem-solving activities…

Pre-service teachers’ challenges in presenting mathematical problems

NASA Astrophysics Data System (ADS)

Desfitri, R.

2018-01-01

The purpose of this study was to analyzed how pre-service teachers prepare and assigned tasks or assignments in teaching practice situations. This study was also intended to discuss about kind of tasks or assignments they gave to students. Participants of this study were 15 selected pre-service mathematics teachers from mathematics education department who took part on microteaching class as part of teaching preparation program. Based on data obtained, it was occasionally found that there were hidden errors on questions or tasks assigned by pre-service teachers which might lead their students not to be able to reach a logical or correct answer. Although some answers might seem to be true, they were illogical or unfavourable. It is strongly recommended that pre-service teachers be more careful when posing mathematical problems so that students do not misunderstand the problems or the concepts, since both teachers and students were sometimes unaware of errors in problems being worked on.

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

PubMed

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-04-01

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or stop the progression of AD. There is converging belief that disease-modifying treatments should focus on early stages of the disease, that is, the mild cognitive impairment (MCI) and preclinical stages. Making a diagnosis of AD and offering a prognosis (likelihood of converting to AD) at these early stages are challenging tasks but possible with the help of multimodality imaging, such as magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG)-positron emission topography (PET), amyloid-PET, and recently introduced tau-PET, which provides different but complementary information. This article is a focused review of existing research in the recent decade that used statistical machine learning and artificial intelligence methods to perform quantitative analysis of multimodality image data for diagnosis and prognosis of AD at the MCI or preclinical stages. We review the existing work in 3 subareas: diagnosis, prognosis, and methods for handling modality-wise missing data-a commonly encountered problem when using multimodality imaging for prediction or classification. Factors contributing to missing data include lack of imaging equipment, cost, difficulty of obtaining patient consent, and patient drop-off (in longitudinal studies). Finally, we summarize our major findings and provide some recommendations for potential future research directions. Copyright © 2018 Elsevier Inc. All rights reserved.

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Multiple Objective Evolution Strategies (MOES): A User’s Guide to Running the Software

DTIC Science & Technology

2014-11-01

L2-norm distance is computed in parameter space between each pair of solutions in the elite population and tested against the tolerance Dclone, which...the most efficient solutions to the test problems in the Input_Files directory. The developers recommend using mu,kappa,lambda. The mu,kappa,lambda...be used as a sanity test for complicated multimodal problems. Whenever the optimum cannot be reached by a local search, the evolutionary results

New optimization model for routing and spectrum assignment with nodes insecurity

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-04-01

By adopting the orthogonal frequency division multiplexing technology, elastic optical networks can provide the flexible and variable bandwidth allocation to each connection request and get higher spectrum utilization. The routing and spectrum assignment problem in elastic optical network is a well-known NP-hard problem. In addition, information security has received worldwide attention. We combine these two problems to investigate the routing and spectrum assignment problem with the guaranteed security in elastic optical network, and establish a new optimization model to minimize the maximum index of the used frequency slots, which is used to determine an optimal routing and spectrum assignment schemes. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. The heuristic algorithm is first used to sort the connection requests and then the genetic algorithm is designed to look for an optimal routing and spectrum assignment scheme. In the genetic algorithm, tailor-made crossover, mutation and local search operators are designed. Moreover, simulation experiments are conducted with three heuristic strategies, and the experimental results indicate that the effectiveness of the proposed model and algorithm framework.

Non-responders to cardiac resynchronization therapy: Insights from multimodality imaging and electrocardiography. A brief review.

PubMed

Carità, Patrizia; Corrado, Egle; Pontone, Gianluca; Curnis, Antonio; Bontempi, Luca; Novo, Giuseppina; Guglielmo, Marco; Ciaramitaro, Gianfranco; Assennato, Pasquale; Novo, Salvatore; Coppola, Giuseppe

2016-12-15

Cardiac resynchronization therapy (CRT) is a successful strategy for heart failure (HF) patients. The pre-requisite for the response is the evidence of electrical dyssynchrony on the surface electrocardiogram usually as left bundle branch block (LBBB). Non-response to CRT is a significant problem in clinical practice. Patient selection, inadequate delivery and sub-optimal left ventricle lead position may be important causes. In an effort to improve CRT response multimodality imaging (especially echocardiography, computed tomography and cardiac magnetic resonance) could play a decisive role and extensive literature has been published on the matter. However, we are so far from routinary use in clinical practice. Electrocardiography (with respect to left ventricle capture and QRS narrowing) may represent a simple and low cost approach for early prediction of potential non-responder, with immediate practical implications. This brief review covers the current recommendations for CRT in HF patients with particular attention to the potential benefits of multimodality imaging and electrocardiography in improving response rate. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Kearney, Robert E.; Galiana, Henrietta L.

2005-01-01

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

A multimodal MRI dataset of professional chess players.

PubMed

Li, Kaiming; Jiang, Jing; Qiu, Lihua; Yang, Xun; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2015-01-01

Chess is a good model to study high-level human brain functions such as spatial cognition, memory, planning, learning and problem solving. Recent studies have demonstrated that non-invasive MRI techniques are valuable for researchers to investigate the underlying neural mechanism of playing chess. For professional chess players (e.g., chess grand masters and masters or GM/Ms), what are the structural and functional alterations due to long-term professional practice, and how these alterations relate to behavior, are largely veiled. Here, we report a multimodal MRI dataset from 29 professional Chinese chess players (most of whom are GM/Ms), and 29 age matched novices. We hope that this dataset will provide researchers with new materials to further explore high-level human brain functions.

Problem-Based Assignments as a Trigger for Developing Ethical and Reflective Competencies

ERIC Educational Resources Information Center

Euler, Dieter; Kühner, Patrizia

2017-01-01

The following research question serves as the starting point of this research and development project: How, in the context of a didactic design, can problem-based assignments trigger learning activities for the development of ethical and reflective competencies in students in economics courses? This paper focuses on the design of problem-based…

Investigation of the Effect of Assignment Projects on Mathematical Activity of Graduating Junior High School Students.

ERIC Educational Resources Information Center

Zehavi, Nurit

This study explored student mathematical activity in open problem-solving situations, derived from the work of Polya on problem solving and Skemp on intelligent learning and teaching. Assignment projects with problems for ninth-grade students were developed, whether they elicit the desired cognitive and cogno-affective goals was investigated, and…

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

Evaluation of Genetic Algorithm Concepts using Model Problems. Part 1; Single-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

Integrated femtosecond stimulated Raman scattering and two-photon fluorescence imaging of subcellular lipid and vesicular structures

NASA Astrophysics Data System (ADS)

Li, Xuesong; Lam, Wen Jiun; Cao, Zhe; Hao, Yan; Sun, Qiqi; He, Sicong; Mak, Ho Yi; Qu, Jianan Y.

2015-11-01

The primary goal of this study is to demonstrate that stimulated Raman scattering (SRS) as a new imaging modality can be integrated into a femtosecond (fs) nonlinear optical (NLO) microscope system. The fs sources of high pulse peak power are routinely used in multimodal nonlinear microscopy to enable efficient excitation of multiple NLO signals. However, with fs excitations, the SRS imaging of subcellular lipid and vesicular structures encounters significant interference from proteins due to poor spectral resolution and a lack of chemical specificity, respectively. We developed a unique NLO microscope of fs excitation that enables rapid acquisition of SRS and multiple two-photon excited fluorescence (TPEF) signals. In the in vivo imaging of transgenic C. elegans animals, we discovered that by cross-filtering false positive lipid signals based on the TPEF signals from tryptophan-bearing endogenous proteins and lysosome-related organelles, the imaging system produced highly accurate assignment of SRS signals to lipid. Furthermore, we demonstrated that the multimodal NLO microscope system could sequentially image lipid structure/content and organelles, such as mitochondria, lysosomes, and the endoplasmic reticulum, which are intricately linked to lipid metabolism.

Supervised multimedia categorization

NASA Astrophysics Data System (ADS)

Aldershoff, Frank; Salden, Alfons H.; Iacob, Sorin M.; Kempen, Masja

2003-01-01

Static multimedia on the Web can already be hardly structured manually. Although unavoidable and necessary, manual annotation of dynamic multimedia becomes even less feasible when multimedia quickly changes in complexity, i.e. in volume, modality, and usage context. The latter context could be set by learning or other purposes of the multimedia material. This multimedia dynamics calls for categorisation systems that index, query and retrieve multimedia objects on the fly in a similar way as a human expert would. We present and demonstrate such a supervised dynamic multimedia object categorisation system. Our categorisation system comes about by continuously gauging it to a group of human experts who annotate raw multimedia for a certain domain ontology given a usage context. Thus effectively our system learns the categorisation behaviour of human experts. By inducing supervised multi-modal content and context-dependent potentials our categorisation system associates field strengths of raw dynamic multimedia object categorisations with those human experts would assign. After a sufficient long period of supervised machine learning we arrive at automated robust and discriminative multimedia categorisation. We demonstrate the usefulness and effectiveness of our multimedia categorisation system in retrieving semantically meaningful soccer-video fragments, in particular by taking advantage of multimodal and domain specific information and knowledge supplied by human experts.

Analgesic effects of tramadol, carprofen or multimodal analgesia in rats undergoing ventral laparotomy.

PubMed

Zegre Cannon, Coralie; Kissling, Grace E; Goulding, David R; King-Herbert, Angela P; Blankenship-Paris, Terry

2011-03-01

In this study, the authors evaluated the analgesic efficacy of tramadol (an opioid-like analgesic), carprofen (a nonsteroidal anti-inflammatory drug) and a combination of both drugs (multimodal therapy) in a rat laparotomy model. The authors randomly assigned rats to undergo either surgery (abdominal laparotomy with visceral manipulation and anesthesia) or anesthesia only. Rats in each group were treated with tramadol (12.5 mg per kg body weight), carprofen (5 mg per kg body weight), a combination of tramadol and carprofen (12.5 mg per kg body weight and 5 mg per kg body weight, respectively) or saline (anesthesia control group only; 5 mg per kg body weight). The authors administered analgesia 10 min before anesthesia, 4 h after surgery or (for the rats that received anesthesia only) anesthesia and 24 h after surgery or anesthesia. They measured locomotor activity, running wheel activity, feed and water consumption, body weight and fecal corticosterone concentration of each animal before and after surgery. Clinical observations were made after surgery or anesthesia to evaluate signs of pain and distress. The authors found that carprofen, tramadol and a combination of carprofen and tramadol were all acceptable analgesia regimens for a rat laparotomy model.

Comparing Looping Teacher-Assigned and Traditional Teacher-Assigned Student Achievement Scores

ERIC Educational Resources Information Center

Lloyd, Melissa C.

2014-01-01

A problem in many elementary schools is determining which teacher assignment strategy best promotes the academic progress of students. To find and implement educational practices that address the academic needs of all learners, schools need research-based data focusing on the 2 teacher assignment strategies: looping assignment (LA) and traditional…

Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming

NASA Astrophysics Data System (ADS)

Gutin, Gregory; Kim, Eun Jung; Soleimanfallah, Arezou; Szeider, Stefan; Yeo, Anders

The NP-hard general factor problem asks, given a graph and for each vertex a list of integers, whether the graph has a spanning subgraph where each vertex has a degree that belongs to its assigned list. The problem remains NP-hard even if the given graph is bipartite with partition U ⊎ V, and each vertex in U is assigned the list {1}; this subproblem appears in the context of constraint programming as the consistency problem for the extended global cardinality constraint. We show that this subproblem is fixed-parameter tractable when parameterized by the size of the second partite set V. More generally, we show that the general factor problem for bipartite graphs, parameterized by |V |, is fixed-parameter tractable as long as all vertices in U are assigned lists of length 1, but becomes W[1]-hard if vertices in U are assigned lists of length at most 2. We establish fixed-parameter tractability by reducing the problem instance to a bounded number of acyclic instances, each of which can be solved in polynomial time by dynamic programming.

A Multimodal Approach to Emotion Recognition Ability in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Jones, Catherine R. G.; Pickles, Andrew; Falcaro, Milena; Marsden, Anita J. S.; Happe, Francesca; Scott, Sophie K.; Sauter, Disa; Tregay, Jenifer; Phillips, Rebecca J.; Baird, Gillian; Simonoff, Emily; Charman, Tony

2011-01-01

Background: Autism spectrum disorders (ASD) are characterised by social and communication difficulties in day-to-day life, including problems in recognising emotions. However, experimental investigations of emotion recognition ability in ASD have been equivocal, hampered by small sample sizes, narrow IQ range and over-focus on the visual modality.…

Manipulatives and Problem Situations as Escalators for Students' Geometric Understanding: A Semiotic Analysis

ERIC Educational Resources Information Center

Daher, Wajeeh M.

2014-01-01

Mathematical learning and teaching are increasingly seen as a multimodal experience involved in cultural and social semiotic registers and means, and as such social-cultural semiotic analysis is expected to shed light on learning and teaching processes occurring in the mathematics classroom. In this research, three social-cultural semiotic…

Creating Meaning through Multimodality: Multiliteracies Assessment and Photo Projects for Online Portfolios

ERIC Educational Resources Information Center

Schmerbeck, Nicola; Lucht, Felecia

2017-01-01

Actively engaged in online media, learners today are surrounded by texts overtly and covertly transmitted by visual images, sound effects, and voices as well as the written word. Language learning portfolios can engage students in the literacy-oriented learning processes of interpretation, collaboration, and problem solving as outlined by Kern…

Final report for LDRD project 11-0029 : high-interest event detection in large-scale multi-modal data sets : proof of concept.

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

Rohrer, Brandon Robinson

2011-09-01

Events of interest to data analysts are sometimes difficult to characterize in detail. Rather, they consist of anomalies, events that are unpredicted, unusual, or otherwise incongruent. The purpose of this LDRD was to test the hypothesis that a biologically-inspired anomaly detection algorithm could be used to detect contextual, multi-modal anomalies. There currently is no other solution to this problem, but the existence of a solution would have a great national security impact. The technical focus of this research was the application of a brain-emulating cognition and control architecture (BECCA) to the problem of anomaly detection. One aspect of BECCA inmore » particular was discovered to be critical to improved anomaly detection capabilities: it's feature creator. During the course of this project the feature creator was developed and tested against multiple data types. Development direction was drawn from psychological and neurophysiological measurements. Major technical achievements include the creation of hierarchical feature sets created from both audio and imagery data.« less

Quicker Q-Learning in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2005-01-01

Multi-agent learning in Markov Decisions Problems is challenging because of the presence ot two credit assignment problems: 1) How to credit an action taken at time step t for rewards received at t' greater than t; and 2) How to credit an action taken by agent i considering the system reward is a function of the actions of all the agents. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning OK TD(lambda) The second credit assi,onment problem is typically addressed either by hand-crafting reward functions that assign proper credit to an agent, or by making certain independence assumptions about an agent's state-space and reward function. To address both credit assignment problems simultaneously, we propose the Q Updates with Immediate Counterfactual Rewards-learning (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. Instead of assuming that an agent s value function can be made independent of other agents, this method suppresses the impact of other agents using counterfactual rewards. Results on multi-agent grid-world problems over multiple topologies show that QUICR-learning can achieve up to thirty fold improvements in performance over both conventional and local Q-learning in the largest tested systems.

A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

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

Li, Weixuan; Zhang, Dongxiao; Lin, Guang

A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a samplemore » of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching problem is captured and are used to give a reliable production prediction with uncertainty quantification. The new algorithm reveals a great improvement in terms of computational efficiency comparing previously studied approaches for the sample problem.« less

Meta-cognitive student reflections

NASA Astrophysics Data System (ADS)

Barquist, Britt; Stewart, Jim

2009-05-01

We have recently concluded a project testing the effectiveness of a weekly assignment designed to encourage awareness and improvement of meta-cognitive skills. The project is based on the idea that successful problem solvers implement a meta-cognitive process in which they identify the specific concept they are struggling with, and then identify what they understand, what they don't understand, and what they need to know in order to resolve their problem. The assignment required the students to write an email assessing the level of completion of a weekly workbook assignment and to examine in detail their experiences regarding a specific topic they struggled with. The assignment guidelines were designed to coach them through this meta-cognitive process. We responded to most emails with advice for next week's assignment. Our data follow 12 students through a quarter consisting of 11 email assignments which were scored using a rubric based on the assignment guidelines. We found no correlation between rubric scores and final grades. We do have anecdotal evidence that the assignment was beneficial.

Determining the relationship between students' scores using traditional homework assignments to those who used assignments on a non-traditional interactive CD with tutor helps

NASA Astrophysics Data System (ADS)

Tinney, Charles Evan

2007-12-01

By using the book "Physics for Scientists and Engineers" by Raymond A. Serway as a guide, CD problem sets for teaching a calculus-based physics course were developed, programmed, and evaluated for homework assignments during the 2003-2004 academic year at Utah State University. These CD sets were used to replace the traditionally handwritten and submitted homework sets. They included a research-based format that guided the students through problem-solving techniques using responseactivated helps and suggestions. The CD contents were designed to help the student improve his/her physics problem-solving skills. The analyzed score results showed a direct correlation between the scores obtained on the homework and the students' time spent per problem, as well as the number of helps used per problem.

Increasing knowledge of best practices for occupational therapists treating post-stroke unilateral spatial neglect: results of a knowledge-translation intervention study.

PubMed

Petzold, Anita; Korner-Bitensky, Nicol; Salbach, Nancy M; Ahmed, Sara; Menon, Anita; Ogourtsova, Tatiana

2012-02-01

The aim of this study was to investigate: (i) the feasibility of delivering a multi-modal knowledge translation intervention specific to the management of acute post-stroke unilateral spatial neglect; and (ii) the impact of the knowledge translation intervention on occupational therapists' knowledge of evidence-based unilateral spatial neglect problem identification, assessment and treatment, and self-efficacy related to evidence-based practice implementation. A 3-period (pre-post) repeated measures design. Acute care occupational therapists treating patients with post-stroke unilateral spatial neglect were recruited from two major Canadian cities. Participants completed two pre-intervention assessments, took part in a day-long interactive multi-modal knowledge translation intervention and a subsequent 8-week follow-up, and completed a post-intervention assessment. Knowledge of evidence-based problem identification, assessment and treatment of unilateral spatial neglect, and self-efficacy to perform evidence-based practice activities were measured using standard scales. The intervention was tested on 20 occupational therapists. Results indicate a significant improvement in knowledge of best practice unilateral spatial neglect management (p < 0.000) and evidence-based practice self-efficacy in carrying out evidence-based practice activities (p < 0.045) post-intervention. Use of a multi-modal knowledge translation intervention is feasible and can significantly improve occupational therapists' knowledge of unilateral spatial neglect best practices and self-efficacy. The findings should help advance best practices specific to the management of post-stroke unilateral spatial neglect as well as informing knowledge translation studies in other areas of practice.

The Intersection of Multimodality and Critical Perspective: Multimodality as Subversion

ERIC Educational Resources Information Center

Huang, Shin-ying

2015-01-01

This study explores the relevance of multimodality to critical media literacy. It is based on the understanding that communication is intrinsically multimodal and multimodal communication is inherently social and ideological. By analysing two English-language learners' multimodal ensembles, the study reports on how multimodality contributes to a…

Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics

NASA Astrophysics Data System (ADS)

Franck, I. M.; Koutsourelakis, P. S.

2017-01-01

This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of unknown (latent) variables is high. This is the setting in many problems in computational physics where forward models with nonlinear PDEs are used and the parameters to be calibrated involve spatio-temporarily varying coefficients, which upon discretization give rise to a high-dimensional vector of unknowns. One of the consequences of the well-documented ill-posedness of inverse problems is the possibility of multiple solutions. While such information is contained in the posterior density in Bayesian formulations, the discovery of a single mode, let alone multiple, poses a formidable computational task. The goal of the present paper is two-fold. On one hand, we propose approximate, adaptive inference strategies using mixture densities to capture multi-modal posteriors. On the other, we extend our work in [1] with regard to effective dimensionality reduction techniques that reveal low-dimensional subspaces where the posterior variance is mostly concentrated. We validate the proposed model by employing Importance Sampling which confirms that the bias introduced is small and can be efficiently corrected if the analyst wishes to do so. We demonstrate the performance of the proposed strategy in nonlinear elastography where the identification of the mechanical properties of biological materials can inform non-invasive, medical diagnosis. The discovery of multiple modes (solutions) in such problems is critical in achieving the diagnostic objectives.

Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions

PubMed Central

Qualls, Joseph; Russomanno, David J.

2011-01-01

The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions. PMID:22164081

A multi-modal approach for activity classification and fall detection

NASA Astrophysics Data System (ADS)

Castillo, José Carlos; Carneiro, Davide; Serrano-Cuerda, Juan; Novais, Paulo; Fernández-Caballero, Antonio; Neves, José

2014-04-01

The society is changing towards a new paradigm in which an increasing number of old adults live alone. In parallel, the incidence of conditions that affect mobility and independence is also rising as a consequence of a longer life expectancy. In this paper, the specific problem of falls of old adults is addressed by devising a technological solution for monitoring these users. Video cameras, accelerometers and GPS sensors are combined in a multi-modal approach to monitor humans inside and outside the domestic environment. Machine learning techniques are used to detect falls and classify activities from accelerometer data. Video feeds and GPS are used to provide location inside and outside the domestic environment. It results in a monitoring solution that does not imply the confinement of the users to a closed environment.

BNU-LSVED: a multimodal spontaneous expression database in educational environment

NASA Astrophysics Data System (ADS)

Sun, Bo; Wei, Qinglan; He, Jun; Yu, Lejun; Zhu, Xiaoming

2016-09-01

In the field of pedagogy or educational psychology, emotions are treated as very important factors, which are closely associated with cognitive processes. Hence, it is meaningful for teachers to analyze students' emotions in classrooms, thus adjusting their teaching activities and improving students ' individual development. To provide a benchmark for different expression recognition algorithms, a large collection of training and test data in classroom environment has become an acute problem that needs to be resolved. In this paper, we present a multimodal spontaneous database in real learning environment. To collect the data, students watched seven kinds of teaching videos and were simultaneously filmed by a camera. Trained coders made one of the five learning expression labels for each image sequence extracted from the captured videos. This subset consists of 554 multimodal spontaneous expression image sequences (22,160 frames) recorded in real classrooms. There are four main advantages in this database. 1) Due to recorded in the real classroom environment, viewer's distance from the camera and the lighting of the database varies considerably between image sequences. 2) All the data presented are natural spontaneous responses to teaching videos. 3) The multimodal database also contains nonverbal behavior including eye movement, head posture and gestures to infer a student ' s affective state during the courses. 4) In the video sequences, there are different kinds of temporal activation patterns. In addition, we have demonstrated the labels for the image sequences are in high reliability through Cronbach's alpha method.

Multimode-Optical-Fiber Imaging Probe

NASA Technical Reports Server (NTRS)

Jackson, Deborah

2000-01-01

Currently, endoscopic surgery uses single-mode fiber-bundles to obtain in vivo image information inside orifices of the body. This limits their use to the larger natural bodily orifices and to surgical procedures where there is plenty of room for manipulation. The knee joint, for example can be easily viewed with a fiber optic viewer, but joints in the finger cannot. However, there are a host of smaller orifices where fiber endoscopy would play an important role if a cost effective fiber probe were developed with small enough dimensions (< 250 microns). Examples of beneficiaries of micro-endoscopes are the treatment of the Eustatian tube of the middle ear, the breast ducts, tear ducts, coronary arteries, fallopian tubes, as well as the treatment of salivary duct parotid disease, and the neuro endoscopy of the ventricles and spinal canal. To solve this problem, this work describes an approach for recovering images from. tightly confined spaces using multimode fibers and analytically demonstrates that the concept is sound. The proof of concept draws upon earlier works that concentrated on image recovery after two-way transmission through a multimode fiber as well as work that demonstrated the recovery of images after one-way transmission through a multimode fiber. Both relied on generating a phase conjugated wavefront which was predistorted with the characteristics of the fiber. The described approach also relies on generating a phase conjugated wavefront, but utilizes two fibers to capture the image at some intermediate point (accessible by the fibers, but which is otherwise visually unaccessible).

Multimodal control of sensors on multiple simulated unmanned vehicles.

PubMed

Baber, C; Morin, C; Parekh, M; Cahillane, M; Houghton, R J

2011-09-01

The use of multimodal (speech plus manual) control of the sensors on combinations of one, two, three or five simulated unmanned vehicles (UVs) is explored. Novice controllers of simulated UVs complete a series of target checking tasks. Two experiments compare speech and gamepad control for one, two, three or five UVs in a simulated environment. Increasing the number of UVs has an impact on subjective rating of workload (measured by NASA-Task Load Index), particularly when moving from one to three UVs. Objective measures of performance showed that the participants tended to issue fewer commands as the number of vehicles increased (when using the gamepad control), but, while performance with a single UV was superior to that of multiple UVs, there was little difference across two, three or five UVs. Participants with low spatial ability (measured by the Object Perspectives Test) showed an increase in time to respond to warnings when controlling five UVs. Combining speech with gamepad control of sensors on UVs leads to superior performance on a secondary (respond-to-warnings) task (implying a reduction in demand) and use of fewer commands on primary (move-sensors and classify-target) tasks (implying more efficient operation). STATEMENT OF RELEVANCE: Benefits of multimodal control for unmanned vehicles are demonstrated. When controlling sensors on multiple UVs, participants with low spatial orientation scores have problems. It is proposed that the findings of these studies have implications for selection of UV operators and suggests that future UV workstations could benefit from multimodal control.

Generalised Assignment Matrix Methodology in Linear Programming

ERIC Educational Resources Information Center

Jerome, Lawrence

2012-01-01

Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

PubMed

Chambon, Stanislas; Galtier, Mathieu N; Arnal, Pierrick J; Wainrib, Gilles; Gramfort, Alexandre

2018-04-01

Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEGs), electrooculograms (EOGs), electrocardiograms, and electromyograms (EMGs). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or extracting handcrafted features, that exploits all multivariate and multimodal polysomnography (PSG) signals (EEG, EMG, and EOG), and that can exploit the temporal context of each 30-s window of data. For each modality, the first layer learns linear spatial filters that exploit the array of sensors to increase the signal-to-noise ratio, and the last layer feeds the learnt representation to a softmax classifier. Our model is compared to alternative automatic approaches based on convolutional networks or decisions trees. Results obtained on 61 publicly available PSG records with up to 20 EEG channels demonstrate that our network architecture yields the state-of-the-art performance. Our study reveals a number of insights on the spatiotemporal distribution of the signal of interest: a good tradeoff for optimal classification performance measured with balanced accuracy is to use 6 EEG with 2 EOG (left and right) and 3 EMG chin channels. Also exploiting 1 min of data before and after each data segment offers the strongest improvement when a limited number of channels are available. As sleep experts, our system exploits the multivariate and multimodal nature of PSG signals in order to deliver the state-of-the-art classification performance with a small computational cost.

Influence of blood contamination during multimode adhesive application on the microtensile bond strength to dentin.

PubMed

Kucukyilmaz, E; Celik, E U; Akcay, M; Yasa, B

2017-12-01

The present study evaluated the effects of blood contamination performed at different steps of bonding on the microtensile bond strength (μTBS) of multimode adhesives to dentin when using the self-etch approach. Seventy-five molars were randomly assigned to three adhesive groups comprising 25 specimens each: two multimode adhesives [Single Bond Universal (SBU) and All-Bond Universal (ABU)] and a conventional one-step self-etch adhesive [Clearfil S3 Bond Plus (CSBP)]. Each group was subdivided as follows: (1) uncontaminated (control): bonding application/light curing as a positive control; (2) contamination-1 (cont-1): bonding application/light curing/blood contamination/dry as a negative control; (3) contamination-2 (cont-2): bonding application/light curing/blood contamination/rinse/dry; (4) contamination-3 (cont-3): bonding application/blood contamination/dry/bonding re-application/light curing; and (5) contamination-4 (cont-4): bonding application/blood contamination/rinse/dry/bonding re-application/light curing. Dentin specimens were prepared for μTBS testing after the composite resin application. Data were analyzed with two-way ANOVA and post-hoc tests (α = 0.05). μTBS values were similar in cont-3 groups, and ABU/cont-4 and corresponding control groups, but were significantly lower in the other groups than in their control groups (P < 0.05). Cont-1 groups showed the lowest μTBS values (P < 0.05). Neither decontamination method prevented the decrease in μTBS when contamination occurred after light curing. Drying the blood contaminants and reapplying the adhesive may regain the dentin adhesion when contamination occurs before light curing. Alternatively, rinsing and drying contaminants followed by adhesive re-application may be effective depending on adhesive type.

Topological numbering of features on a mesh

NASA Technical Reports Server (NTRS)

Atallah, Mikhail J.; Hambrusch, Susanne E.; Tewinkel, Lynn E.

1988-01-01

Assume a nxn binary image is given containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. The problem of assigning topological numbers to such features is considered; i.e., assign a number to every feature f so that all features to the left of f have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. A parallel algorithm to solve the topological numbering problem in O(n) time on an nxn mesh of processors is presented. The key idea of the solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.

Multidisciplinary pain facility treatment outcome for pain-associated fatigue.

PubMed

Fishbain, David A; Lewis, John; Cole, Brandly; Cutler, Brian; Smets, Eve; Rosomoff, Hubert; Rosomoff, Rennee Steele

2005-01-01

Fatigue is frequently found in chronic pain patients (CPPs) and may be etiologically related to the presence of pain. Fishbain et al. have recently demonstrated that chronic low back pain (LBP) and chronic neck pain patients are more fatigued than controls. The purpose of this study was to determine whether chronic LBP- and chronic neck pain-associated fatigue responded to multidisciplinary multimodal treatment not specifically targeted to the treatment of fatigue. A total of 85 chronic LBP and 33 chronic neck pain patients completed the Multidimensional Fatigue Inventory (MFI), Neuropathic Pain Scale (NPS), and Beck Depression Inventory on admission. In addition, an information tool was completed on each CPP by the senior author. This tool listed demographic information, primary and secondary pain diagnoses, Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) psychiatric diagnoses assigned, pain location, pain precipitating event, type of injury, years in pain, number of surgeries, type of surgery, type of pain pattern, opioids consumed per day in morphine equivalents, worker compensation status, and whether, according to the clinical examination, the CPP had a neuropathic pain component. At completion of the multidisciplinary multimodal treatment, each CPP again completed the MFI. Student's t-test was utilized to test for statistical changes on the MFI five scales from pre- to post-treatment. Pearson and point-biserial correlations were utilized to determine which variables significantly correlated with MFI change scores. Variables found significant at less than or equal to 0.01 were utilized in a stepwise aggression analysis to find variables predictive of change in MFI scores. Multidisciplinary pain facility. Chronic LBP and chronic neck pain patients. Multidisciplinary multimodal treatment significantly improved CPP fatigue as measured by the MFI. The available variables utilized to predict fatigue best explained only a small percentage (28.9%) of the variance. Improvement in fatigue was related to NPS-10 scale scores (neuropathic pain) and a previous diagnosis of fibromyalgia. Multidisciplinary multimodal pain facility treatment improves chronic LBP- and neck pain-associated fatigue. At the present time we cannot predict this improvement with significant accuracy.

The Cafeteria as Contact Zone: Developing a Multicultural Perspective through Multilingual and Multimodal Literacies

ERIC Educational Resources Information Center

Kelly, Courtney

2013-01-01

This article describes the inaugural year of a cross-cultural after-school program that used a problem-solving, project-based pedagogy to promote meaningful interactions between immigrant middle school students and their urban, low-income peers. The program relied on the students' local knowledge as they worked together to create social maps of…

Student Perceptions of Asynchronous Multimodal Instructor Feedback: A Multiple Case Study

ERIC Educational Resources Information Center

Lenards, Nishele Dyan

2017-01-01

Student dissatisfaction has been a problem in higher education with regard to the provision of assessment-related feedback. Due to the distant nature of online learning, instructors are faced with many challenges in delivering quality feedback because the communication is asynchronous and lacks social cues that are present in a F2F environment.…

Information Systems for Subject Specialists: A Multi-Modal Approach to Indexing and Classification.

ERIC Educational Resources Information Center

Swift, D.F.; And Others

A fundamental problem in the two broad approaches to indexing in the social sciences--providing structure using preferred terms, cross references, and groupings of sets of materials, or compiling a concordance of an author's terms based on occurrence, leaving users free to impose their own structure--is that different indexers and users focus on…

The Shape of Joy, the Colour of Fear: Multimodal Abduction in the Foreign Language Classroom

ERIC Educational Resources Information Center

Nelson, Mark Evan; Johnson, Neil H.

2014-01-01

In this article, we describe a programme of qualitative research and interpretive analysis around an approach to foreign language pedagogy that aimed to develop learners' symbolic competence through experience with and examination of the signs in acts of communication. Learners were presented with the problem of visually representing the abstract…

Mandarin Students' Perceptions of Multimodal Interaction in a Web Conferencing Environment: A Satisfaction Survey

ERIC Educational Resources Information Center

Tseng, Jun-Jie

2015-01-01

A major indicator of whether online courses have been effective and successful is student satisfaction. Copious research points to lack of interaction as the most cited reason for student dissatisfaction. To improve this problem, new Computer-Mediated Communication (CMC) technology could be considered as an option to enhance the online learning…

Approaching the Grammatical Count/Mass Distinction from a Multimodal Perspective

ERIC Educational Resources Information Center

Brown, Derek J.

2015-01-01

The way in which the count/mass distinction (CMD) is realized in English can cause serious problems for learners. Cognitive theories of language propose that it is based on the speaker's conceptualization of the world. It has also been argued that this conceptualization is socially constructed, as social semiotic resources influence what a speaker…

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

PubMed Central

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-01-01

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

PubMed

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-09-15

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

PubMed Central

Zhang, Meiyan; Zheng, Yahong Rosa

2017-01-01

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X−Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem. PMID:28696377

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

PubMed

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Multimodal Interfaces: Literature Review of Ecological Interface Design, Multimodal Perception and Attention, and Intelligent Adaptive Multimodal Interfaces

DTIC Science & Technology

2010-05-01

Multimodal Interfaces Literature Review of Ecological Interface Design , Multimodal Perception and Attention, and Intelligent... Design , Multimodal Perception and Attention, and Intelligent Adaptive Multimodal Interfaces Wayne Giang, Sathya Santhakumaran, Ehsan Masnavi, Doug...Advanced Interface Design Laboratory, E2-1303N 200 University Avenue West Waterloo, Ontario Canada N2L 3G1 Contract Project Manager: Dr. Catherine

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

NASA Technical Reports Server (NTRS)

Englander, Arnold C.; Englander, Jacob A.

2017-01-01

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Show, Don't Tell: Using Photographic "Snapsignments" to Advance and Assess Creative Problem Solving

ERIC Educational Resources Information Center

Machin, Jane E.

2016-01-01

Traditional assignments that aim to develop and evaluate creative problem solving skills are frequently foregone in large marketing classes due to the daunting grading prospect they present. Here, a new assessment method is introduced: the "snapsignment." Through photography, individual projects can be assigned that promote higher order…

Comorbid Obsessive-Compulsive Symptoms in Schizophrenia: Insight into Pathomechanisms Facilitates Treatment

PubMed Central

Zink, Mathias

2014-01-01

Insight into the biological pathomechanism of a clinical syndrome facilitates the development of effective interventions. This paper applies this perspective to the important clinical problem of obsessive-compulsive symptoms (OCS) occurring during the lifetime diagnosis of schizophrenia. Up to 25% of schizophrenia patients suffer from OCS and about 12% fulfil the diagnostic criteria of obsessive-compulsive disorder (OCD). This is accompanied by marked subjective burden of disease, high levels of anxiety, depression and suicidality, increased neurocognitive impairment, less favourable levels of social and vocational functioning, and greater service utilization. Comorbid patients can be assigned to heterogeneous subgroups. It is assumed that second generation antipsychotics (SGAs), most importantly clozapine, might aggravate or even induce second-onset OCS. Several epidemiological and pharmacological arguments support this assumption. Specific genetic risk factors seem to dispose patients with schizophrenia to develop OCS and risk-conferring polymorphisms has been defined in SLC1A1, BDNF, DLGAP3, and GRIN2B and in interactions between these individual genes. Further research is needed with detailed characterization of large samples. In particular interactions between genetic risk constellations, pharmacological and psychosocial factors should be analysed. Results will further define homogeneous subgroups, which are in need for differential causative interventions. In clinical practise, schizophrenia patients should be carefully monitored for OCS, starting with at-risk mental states of psychosis and longitudinal follow-ups, hopefully leading to the development of multimodal therapeutic interventions. PMID:26556409

Laughter and the Management of Divergent Positions in Peer Review Interactions

PubMed Central

Raclaw, Joshua; Ford, Cecilia E.

2017-01-01

In this paper we focus on how participants in peer review interactions use laughter as a resource as they publicly report divergence of evaluative positions, divergence that is typical in the give and take of joint grant evaluation. Using the framework of conversation analysis, we examine the infusion of laughter and multimodal laugh-relevant practices into sequences of talk in meetings of grant reviewers deliberating on the evaluation and scoring of high-level scientific grant applications. We focus on a recurrent sequence in these meetings, what we call the score-reporting sequence, in which the assigned reviewers first announce the preliminary scores they have assigned to the grant. We demonstrate that such sequences are routine sites for the use of laugh practices to navigate the initial moments in which divergence of opinion is made explicit. In the context of meetings convened for the purposes of peer review, laughter thus serves as a valuable resource for managing the socially delicate but institutionally required reporting of divergence and disagreement that is endemic to meetings where these types of evaluative tasks are a focal activity. PMID:29170594

Autonomous Guidance Strategy for Spacecraft Formations and Reconfiguration Maneuvers

NASA Astrophysics Data System (ADS)

Wahl, Theodore P.

A guidance strategy for autonomous spacecraft formation reconfiguration maneuvers is presented. The guidance strategy is presented as an algorithm that solves the linked assignment and delivery problems. The assignment problem is the task of assigning the member spacecraft of the formation to their new positions in the desired formation geometry. The guidance algorithm uses an auction process (also called an "auction algorithm''), presented in the dissertation, to solve the assignment problem. The auction uses the estimated maneuver and time of flight costs between the spacecraft and targets to create assignments which minimize a specific "expense'' function for the formation. The delivery problem is the task of delivering the spacecraft to their assigned positions, and it is addressed through one of two guidance schemes described in this work. The first is a delivery scheme based on artificial potential function (APF) guidance. APF guidance uses the relative distances between the spacecraft, targets, and any obstacles to design maneuvers based on gradients of potential fields. The second delivery scheme is based on model predictive control (MPC); this method uses a model of the system dynamics to plan a series of maneuvers designed to minimize a unique cost function. The guidance algorithm uses an analytic linearized approximation of the relative orbital dynamics, the Yamanaka-Ankersen state transition matrix, in the auction process and in both delivery methods. The proposed guidance strategy is successful, in simulations, in autonomously assigning the members of the formation to new positions and in delivering the spacecraft to these new positions safely using both delivery methods. This guidance algorithm can serve as the basis for future autonomous guidance strategies for spacecraft formation missions.

The impact of artificially caries-affected dentin on bond strength of multi-mode adhesives

PubMed Central

Follak, Andressa Cargnelutti; Miotti, Leonardo Lamberti; Lenzi, Tathiane Larissa; Rocha, Rachel de Oliveira; Maxnuck Soares, Fabio Zovico

2018-01-01

Aim: The aim of this study is to evaluate the impact of dentin condition on bond strength of multi-mode adhesive systems (MMAS) to sound and artificially induced caries-affected dentin (CAD). Methods: Flat dentin surfaces of 112 bovine incisors were assigned to 16 subgroups (n = 7) according to the substrate condition (sound and CAD– pH-cycling for 14 days); adhesive systems (Scotchbond Universal, All-Bond Universal, Prime and Bond Elect, Adper Single Bond Plus and Clearfil SE Bond) and etching strategy (etch-and-rinse and self-etch). All systems were applied according to the manufacturer's instructions, and resin composite restorations were built. After 24 h of water storage, specimens were sectioned (0.8 mm2) and submitted to the microtensile test. Statistical Analysis: Data (MPa) were analyzed using three-way analysis of variance and Tukey's test (α = 0.05). Results: MMAS presented similar bond strength values, regardless etching strategy in each substrate condition. Bond strength values were lower when MMAS were applied to CAD in the etch-and-rinse strategy. Conclusion: The etching strategy did not influence the bond strength of MMAS to sound or CAD, considering each substrate separately. However, CAD impact negatively on bond strength of MMAS in etch-and rinse mode. PMID:29674813

Mediators of Change in the Child/Adolescent Anxiety Multimodal Treatment Study

PubMed Central

Kendall, Philip C.; Cummings, Colleen M.; Villabø, Marianne A.; Narayanan, Martina K.; Treadwell, Kimberli; Birmaher, Boris; Compton, Scott; Piacentini, John; Sherrill, Joel; Walkup, John; Gosch, Elizabeth; Keeton, Courtney; Ginsburg, Golda; Suveg, Cindy; Albano, Anne Marie

2015-01-01

Objective Test changes in (a) coping efficacy and (b) anxious self-talk as potential mediators of treatment gains at 3-month follow-up in the Child/Adolescent Anxiety Multimodal Treatment Study (CAMS). Method Participants were 488 youth (ages 7-17; 50.4% male) randomized to cognitive-behavioral therapy (CBT; Coping cat program), pharmacotherapy (sertraline), their combination, or pill placebo. Participants met DSM-IV criteria for generalized anxiety disorder, social phobia, and/or separation anxiety disorder. Coping efficacy (reported ability to manage anxiety provoking situations) was measured by youth and parent reports on the Coping Questionnaire, and anxious self-talk was measured by youth report on the Negative Affectivity Self-Statement Questionnaire. Outcome was measured using the Pediatric Anxiety Rating Scale (completed by Independent Evaluators blind to condition). For temporal precedence, residualized treatment gains were assessed at 3-month follow-up. Results Residualized gains in coping efficacy mediated gains in the CBT, sertraline, and combination conditions. In the combination condition, some unique effect of treatment remained. Treatment assignment was not associated with a reduction in anxious self-talk, nor did anxious self-talk predict changes in anxiety symptoms. Conclusions The findings suggest that improvements in coping efficacy are a mediator of treatment gains. Anxious self-talk did not emerge as a mediator. PMID:26460572

Hyperspectral tomography based on multi-mode absorption spectroscopy (MUMAS)

NASA Astrophysics Data System (ADS)

Dai, Jinghang; O'Hagan, Seamus; Liu, Hecong; Cai, Weiwei; Ewart, Paul

2017-10-01

This paper demonstrates a hyperspectral tomographic technique that can recover the temperature and concentration field of gas flows based on multi-mode absorption spectroscopy (MUMAS). This method relies on the recently proposed concept of nonlinear tomography, which can take full advantage of the nonlinear dependency of MUMAS signals on temperature and enables 2D spatial resolution of MUMAS which is naturally a line-of-sight technique. The principles of MUMAS and nonlinear tomography, as well as the mathematical formulation of the inversion problem, are introduced. Proof-of-concept numerical demonstrations are presented using representative flame phantoms and assuming typical laser parameters. The results show that faithful reconstruction of temperature distribution is achievable when a signal-to-noise ratio of 20 is assumed. This method can potentially be extended to simultaneously reconstructing distributions of temperature and the concentration of multiple flame species.

New adhesives and bonding techniques. Why and when?

PubMed

Scotti, Nicola; Cavalli, Giovanni; Gagliani, Massimo; Breschi, Lorenzo

Nowadays, adhesive dentistry is a fundamental part of daily clinical work. The evolution of adhesive materials and techniques has been based on the need for simplicity in the step-by-step procedures to obtain long-lasting direct and indirect restorations. For this reason, recently introduced universal multimode adhesives represent a simple option for creating a hybrid layer, with or without the use of phosphoric acid application. However, it is important to understand the limitations of this latest generation of adhesive systems as well as how to use them on coronal and radicular dentin. Based on the findings in the literature, universal multimode adhesives have shown promising results, even if the problem of hybrid layer degradation due to the hydrolytic activity of matrix metalloproteinases (MMPs) still exists. Studies are therefore required to help us understand how to reduce this degradation.

Superfocusing of mutimode semiconductor lasers and light-emitting diodes

NASA Astrophysics Data System (ADS)

Sokolovskii, G. S.; Dudelev, V. V.; Losev, S. N.; Deryagin, A. G.; Kuchinskii, V. I.; Sibbett, W.; Rafailov, E. U.

2012-05-01

The problem of focusing multimode radiation of high-power semiconductor lasers and light-emitting diodes (LEDs) has been studied. In these sources, low spatial quality of the output beam determines theoretical limit of the focal spot size (one to two orders of magnitude exceeding the diffraction limit), thus restricting the possibility of increasing power density and creating optical field gradients that are necessary in many practical applications. In order to overcome this limitation, we have developed a method of superfocusing of multimode radiation with the aid of interference. It is shown that, using this method, the focal spot size of high-power semiconductor lasers and LEDs can be reduced to a level unachievable by means of traditional focusing. An approach to exceed the theoretical limit of power density for focusing of radiation with high propagation parameter M 2 is proposed.

Quality dependent fusion of intramodal and multimodal biometric experts

NASA Astrophysics Data System (ADS)

Kittler, J.; Poh, N.; Fatukasi, O.; Messer, K.; Kryszczuk, K.; Richiardi, J.; Drygajlo, A.

2007-04-01

We address the problem of score level fusion of intramodal and multimodal experts in the context of biometric identity verification. We investigate the merits of confidence based weighting of component experts. In contrast to the conventional approach where confidence values are derived from scores, we use instead raw measures of biometric data quality to control the influence of each expert on the final fused score. We show that quality based fusion gives better performance than quality free fusion. The use of quality weighted scores as features in the definition of the fusion functions leads to further improvements. We demonstrate that the achievable performance gain is also affected by the choice of fusion architecture. The evaluation of the proposed methodology involves 6 face and one speech verification experts. It is carried out on the XM2VTS data base.

Multimodal homesickness prevention in boys spending 2 weeks at a residential summer camp.

PubMed

Thurber, Christopher A

2005-06-01

Homesickness is the distress or impairment caused by an actual or anticipated separation from home. It is characterized by preoccupying thoughts of home and attachment objects. In its severe form, homesickness is subjectively distressing and has clinically significant cognitive, emotional, and behavioral sequelae. This study provided 75 boys who ranged in age from 8 to 16 years and who were 1st-year campers at an overnight summer camp with an inexpensive, multimodal homesickness prevention package. Results suggest that combining environmental information, psychoeducation, social support, explicit coping instruction, caregiver education, practice time away from home, and surrogate caregiver training can reduce homesickness and associated behavior problems. These data support the theory that novelty reduction, attitudinal shifts, preseparation coping enhancement, and supportive social environments diminish the negative emotional intensity of homesickness. (c) 2005 APA, all rights reserved.

It's NOT New; It's NOT Different: The Psycholinguistics of Digital Literacy

ERIC Educational Resources Information Center

Horning, Alice S.

2014-01-01

Teachers of reading and writing have been getting a lot of criticism recently, mostly derived from studies showing that students and the population at large lack essential literacy skills to be successful. The move to multimodal literacy only complicates the problems already present. While some new skills are needed in order to engage in…

Intertextuality and Multimodal Meanings in High School Physics: Written and Spoken Language in Computer-Supported Collaborative Student Discourse

ERIC Educational Resources Information Center

Tang, Kok-Sing; Tan, Seng-Chee

2017-01-01

The study in this article examines and illustrates the intertextual meanings made by a group of high school science students as they embarked on a knowledge building discourse to solve a physics problem. This study is situated in a computer-supported collaborative learning (CSCL) environment designed to support student learning through a science…

Multimodal Retrospective and Prospective Unit-Level Analysis of Military Workplace Violence

DTIC Science & Technology

2015-10-01

Disciplinary infractions, minor crimes, PTSD and other mental problems, and substance abuse will increase MWV; 3. Treatment and social support will...Disorder Risk Taking Behaviors Risk Factors Protective Factors Social Support Mental Health Substance Abuse 2 3. OVERALL PROJECT SUMMARY The...potential predictors of MWV. These intervening outcomes include PTSD and other mental health issues, substance abuse , disciplinary infractions, and

Game Design Narrative for Learning: Appropriating Adventure Game Design Narrative Devices and Techniques for the Design of Interactive Learning Environments

ERIC Educational Resources Information Center

Dickey, Michele D.

2006-01-01

The purpose of this conceptual analysis is to investigate how contemporary video and computer games might inform instructional design by looking at how narrative devices and techniques support problem solving within complex, multimodal environments. Specifically, this analysis presents a brief overview of game genres and the role of narrative in…

A Preliminary Analysis of the Linguistic Complexity of Numeracy Skills Test Items for Pre Service Teachers

ERIC Educational Resources Information Center

O'Keeffe, Lisa

2016-01-01

Language is frequently discussed as barrier to mathematics word problems. Hence this paper presents the initial findings of a linguistic analysis of numeracy skills test sample items. The theoretical perspective of multi-modal text analysis underpinned this study, in which data was extracted from the ten sample numeracy test items released by the…

Real-time dynamic display of registered 4D cardiac MR and ultrasound images using a GPU

NASA Astrophysics Data System (ADS)

Zhang, Q.; Huang, X.; Eagleson, R.; Guiraudon, G.; Peters, T. M.

2007-03-01

In minimally invasive image-guided surgical interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and real-time three-dimensional (3D) ultrasound (US), can provide complementary, multi-spectral image information. Multimodality dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac procedures, it would be valuable to register dynamic MRI or CT with intraoperative US. However, in practice, either the high computational cost prohibits such real-time visualization of volumetric multimodal images in a real-world medical environment, or else the resulting image quality is not satisfactory for accurate guidance during the intervention. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to begin to address this problem. In this work, we first outline our research on dynamic 3D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Then we describe image processing and optimization techniques for 4D (3D + time) cardiac image real-time rendering. We also present our multimodality 4D medical image visualization engine, which directly runs on a GPU in real-time by exploiting the advantages of the graphics hardware. In addition, techniques such as multiple transfer functions for different imaging modalities, dynamic texture binding, advanced texture sampling and multimodality image compositing are employed to facilitate the real-time display and manipulation of the registered dual-modality dynamic 3D MR and US cardiac datasets.

WWC Review of the Report "Effects of Problem Based Economics on High School Economics Instruction"

ERIC Educational Resources Information Center

What Works Clearinghouse, 2012

2012-01-01

The study described in this report included 128 high school economics teachers from 106 schools in Arizona and California, half of whom were randomly assigned to the "Problem Based Economics Instruction" condition and half of whom were randomly assigned to the comparison condition. High levels of teacher attrition occurred after…

Neural Mechanisms of Credit Assignment in a Multicue Environment

PubMed Central

Kolling, Nils; Brown, Joshua W.; Rushworth, Matthew

2016-01-01

In complex environments, many potential cues can guide a decision or be assigned responsibility for the outcome of the decision. We know little, however, about how humans and animals select relevant information sources that should guide behavior. We show that subjects solve this relevance selection and credit assignment problem by selecting one cue and its association with a particular outcome as the main focus of a hypothesis. To do this, we examined learning while using a task design that allowed us to estimate the focus of each subject's hypotheses on a trial-by-trial basis. When a prediction is confirmed by the outcome, then credit for the outcome is assigned to that cue rather than an alternative. Activity in medial frontal cortex is associated with the assignment of credit to the cue that is the main focus of the hypothesis. However, when the outcome disconfirms a prediction, the focus shifts between cues, and the credit for the outcome is assigned to an alternative cue. This process of reselection for credit assignment to an alternative cue is associated with lateral orbitofrontal cortex. SIGNIFICANCE STATEMENT Learners should infer which features of environments are predictive of significant events, such as rewards. This “credit assignment” problem is particularly challenging when any of several cues might be predictive. We show that human subjects solve the credit assignment problem by implicitly “hypothesizing” which cue is relevant for predicting subsequent outcomes, and then credit is assigned according to this hypothesis. This process is associated with a distinctive pattern of activity in a part of medial frontal cortex. By contrast, when unexpected outcomes occur, hypotheses are redirected toward alternative cues, and this process is associated with activity in lateral orbitofrontal cortex. PMID:26818500

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

Supporting services play an important role in health care institutions such as hospitals. This paper presents an application of operations research model for optimal allocation of workers among supporting services in a public hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criterion of the problem is to minimize operations costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problem is formulated as an integer program in the literature known as the assignment problem, where the decision variables represent the assignment of people to various jobs. The results of some computational experiments modeled on a real data from a selected Polish hospital are reported.

A modified generalized extremal optimization algorithm for the quay crane scheduling problem with interference constraints

NASA Astrophysics Data System (ADS)

Guo, Peng; Cheng, Wenming; Wang, Yi

2014-10-01

The quay crane scheduling problem (QCSP) determines the handling sequence of tasks at ship bays by a set of cranes assigned to a container vessel such that the vessel's service time is minimized. A number of heuristics or meta-heuristics have been proposed to obtain the near-optimal solutions to overcome the NP-hardness of the problem. In this article, the idea of generalized extremal optimization (GEO) is adapted to solve the QCSP with respect to various interference constraints. The resulting GEO is termed the modified GEO. A randomized searching method for neighbouring task-to-QC assignments to an incumbent task-to-QC assignment is developed in executing the modified GEO. In addition, a unidirectional search decoding scheme is employed to transform a task-to-QC assignment to an active quay crane schedule. The effectiveness of the developed GEO is tested on a suite of benchmark problems introduced by K.H. Kim and Y.M. Park in 2004 (European Journal of Operational Research, Vol. 156, No. 3). Compared with other well-known existing approaches, the experiment results show that the proposed modified GEO is capable of obtaining the optimal or near-optimal solution in a reasonable time, especially for large-sized problems.

Process-based Assignment-Setting Change for Support of Overcoming Bottlenecks in Learning by Problem-Posing in Arithmetic Word Problems

NASA Astrophysics Data System (ADS)

Supianto, A. A.; Hayashi, Y.; Hirashima, T.

2017-02-01

Problem-posing is well known as an effective activity to learn problem-solving methods. Monsakun is an interactive problem-posing learning environment to facilitate arithmetic word problems learning for one operation of addition and subtraction. The characteristic of Monsakun is problem-posing as sentence-integration that lets learners make a problem of three sentences. Monsakun provides learners with five or six sentences including dummies, which are designed through careful considerations by an expert teacher as a meaningful distraction to the learners in order to learn the structure of arithmetic word problems. The results of the practical use of Monsakun in elementary schools show that many learners have difficulties in arranging the proper answer at the high level of assignments. The analysis of the problem-posing process of such learners found that their misconception of arithmetic word problems causes impasses in their thinking and mislead them to use dummies. This study proposes a method of changing assignments as a support for overcoming bottlenecks of thinking. In Monsakun, the bottlenecks are often detected as a frequently repeated use of a specific dummy. If such dummy can be detected, it is the key factor to support learners to overcome their difficulty. This paper discusses how to detect the bottlenecks and to realize such support in learning by problem-posing.

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation.

PubMed

Li, Yuhong; Jia, Fucang; Qin, Jing

2016-10-01

Accurately segmenting and quantifying brain gliomas from magnetic resonance (MR) images remains a challenging task because of the large spatial and structural variability among brain tumors. To develop a fully automatic and accurate brain tumor segmentation algorithm, we present a probabilistic model of multimodal MR brain tumor segmentation. This model combines sparse representation and the Markov random field (MRF) to solve the spatial and structural variability problem. We formulate the tumor segmentation problem as a multi-classification task by labeling each voxel as the maximum posterior probability. We estimate the maximum a posteriori (MAP) probability by introducing the sparse representation into a likelihood probability and a MRF into the prior probability. Considering the MAP as an NP-hard problem, we convert the maximum posterior probability estimation into a minimum energy optimization problem and employ graph cuts to find the solution to the MAP estimation. Our method is evaluated using the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013) and obtained Dice coefficient metric values of 0.85, 0.75, and 0.69 on the high-grade Challenge data set, 0.73, 0.56, and 0.54 on the high-grade Challenge LeaderBoard data set, and 0.84, 0.54, and 0.57 on the low-grade Challenge data set for the complete, core, and enhancing regions. The experimental results show that the proposed algorithm is valid and ranks 2nd compared with the state-of-the-art tumor segmentation algorithms in the MICCAI BRATS 2013 challenge. Copyright © 2016 Elsevier B.V. All rights reserved.

Fleet Assignment Using Collective Intelligence

NASA Technical Reports Server (NTRS)

Antoine, Nicolas E.; Bieniawski, Stefan R.; Kroo, Ilan M.; Wolpert, David H.

2004-01-01

Product distribution theory is a new collective intelligence-based framework for analyzing and controlling distributed systems. Its usefulness in distributed stochastic optimization is illustrated here through an airline fleet assignment problem. This problem involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of linear and non-linear constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of this new stochastic optimization algorithm to a non-linear objective cold start fleet assignment problem. Results show that the optimizer can successfully solve such highly-constrained problems (130 variables, 184 constraints).

Enhanced performance feedback and patient participation to improve hand hygiene compliance of health-care workers in the setting of established multimodal promotion: a single-centre, cluster randomised controlled trial.

PubMed

Stewardson, Andrew James; Sax, Hugo; Gayet-Ageron, Angèle; Touveneau, Sylvie; Longtin, Yves; Zingg, Walter; Pittet, Didier

2016-12-01

Hand hygiene compliance of health-care workers remains suboptimal despite standard multimodal promotion, and evidence for the effectiveness of novel interventions is urgently needed. We aimed to assess the effect of enhanced performance feedback and patient participation on hand hygiene compliance in the setting of multimodal promotion. We did a single-centre, cluster randomised controlled trial at University of Geneva Hospitals (Geneva, Switzerland). All wards hosting adult, lucid patients, and all health-care workers and patients in these wards, were eligible. After a 15-month baseline period, eligible wards were assigned by computer-generated block randomisation (1:1:1), stratified by the type of ward, to one of three groups: control, enhanced performance feedback, or enhanced performance feedback plus patient participation. Standard multimodal hand hygiene promotion was done hospital-wide throughout the study. The primary outcome was hand hygiene compliance of health-care workers (according to the WHO Five Moments of Hand Hygiene) at the opportunity level, measured by direct observation (20-min sessions) by 12 validated infection control nurses, with each ward audited at least once every 3 months. This trial is registered with ISRCTN, number ISRCTN43599478. We randomly assigned 67 wards to the control group (n=21), enhanced performance feedback (n=24), or enhanced performance feedback plus patient participation (n=22) on May 19, 2010. One ward in the control group became a high-dependency unit and was excluded from analysis. During 1367 observation sessions, 12 579 hand hygiene opportunities were recorded. Between the baseline period (April 1, 2009, to June 30, 2010) and the intervention period (July 1, 2010, to June 30, 2012), mean hand hygiene compliance increased from 66% (95% CI 62-70) to 73% (70-77) in the control group (odds ratio [OR] 1·41, 95% CI 1·21-1·63), from 65% (62-69) to 75% (72-77) in the enhanced performance feedback group (1·61, 1·41-1·84), and from 66% (62-70) to 77% (74-80) in the enhanced performance feedback plus patient participation group (1·73, 1·51-1·98). The absolute difference in compliance attributable to interventions was 3 percentage points (95% CI 0-7; p=0·19) for the enhanced performance feedback group and 4 percentage points (1-8; p=0·048) for the enhanced performance feedback plus patient participation group. Hand hygiene compliance remained significantly higher than baseline in all three groups (OR 1·21 [1·00-1·47] vs 1·38 [1·19-1·60] vs 1·36 [1·18-1·57]) during the post-intervention follow-up (Jan 1, 2013, to Dec 31, 2014). Hand hygiene compliance improved in all study groups, and neither intervention had a clinically significant effect compared with control. Improvement in control wards might reflect cross-contamination, highlighting challenges with randomised trials of behaviour change. Swiss National Science Foundation. Copyright © 2016 Elsevier Ltd. All rights reserved.

An analysis of spectral envelope-reduction via quadratic assignment problems

NASA Technical Reports Server (NTRS)

George, Alan; Pothen, Alex

1994-01-01

A new spectral algorithm for reordering a sparse symmetric matrix to reduce its envelope size was described. The ordering is computed by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. In this paper, we provide an analysis of the spectral envelope reduction algorithm. We described related 1- and 2-sum problems; the former is related to the envelope size, while the latter is related to an upper bound on the work involved in an envelope Cholesky factorization scheme. We formulate the latter two problems as quadratic assignment problems, and then study the 2-sum problem in more detail. We obtain lower bounds on the 2-sum by considering a projected quadratic assignment problem, and then show that finding a permutation matrix closest to an orthogonal matrix attaining one of the lower bounds justifies the spectral envelope reduction algorithm. The lower bound on the 2-sum is seen to be tight for reasonably 'uniform' finite element meshes. We also obtain asymptotically tight lower bounds for the envelope size for certain classes of meshes.

Towards Automated Structure-Based NMR Resonance Assignment

NASA Astrophysics Data System (ADS)

Jang, Richard; Gao, Xin; Li, Ming

We propose a general framework for solving the structure-based NMR backbone resonance assignment problem. The core is a novel 0-1 integer programming model that can start from a complete or partial assignment, generate multiple assignments, and model not only the assignment of spins to residues, but also pairwise dependencies consisting of pairs of spins to pairs of residues. It is still a challenge for automated resonance assignment systems to perform the assignment directly from spectra without any manual intervention. To test the feasibility of this for structure-based assignment, we integrated our system with our automated peak picking and sequence-based resonance assignment system to obtain an assignment for the protein TM1112 with 91% recall and 99% precision without manual intervention. Since using a known structure has the potential to allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data, we work towards the goal of automated structure-based assignment using only such labeled data. Our system reduced the assignment error of Xiong-Pandurangan-Bailey-Kellogg's contact replacement (CR) method, which to our knowledge is the most error-tolerant method for this problem, by 5 folds on average. By using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for Ubiquitin, where the type prediction accuracy is 83%, we achieved 91% assignment accuracy, compared to the 59% accuracy that was obtained without correcting for typing errors.

Developing a feasible neighbourhood search for solving hub location problem in a communication network

NASA Astrophysics Data System (ADS)

Rakhmawati, Fibri; Mawengkang, Herman; Buulolo, F.; Mardiningsih

2018-01-01

The hub location with single assignment is the problem of locating hubs and assigning the terminal nodes to hubs in order to minimize the cost of hub installation and the cost of routing the traffic in the network. There may also be capacity restrictions on the amount of traffic that can transit by hubs. This paper discusses how to model the polyhedral properties of the problems and develop a feasible neighbourhood search method to solve the model.

An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming.

PubMed

Abbas, Ahmed; Guo, Xianrong; Jing, Bing-Yi; Gao, Xin

2014-06-01

Despite significant advances in automated nuclear magnetic resonance-based protein structure determination, the high numbers of false positives and false negatives among the peaks selected by fully automated methods remain a problem. These false positives and negatives impair the performance of resonance assignment methods. One of the main reasons for this problem is that the computational research community often considers peak picking and resonance assignment to be two separate problems, whereas spectroscopists use expert knowledge to pick peaks and assign their resonances at the same time. We propose a novel framework that simultaneously conducts slice picking and spin system forming, an essential step in resonance assignment. Our framework then employs a genetic algorithm, directed by both connectivity information and amino acid typing information from the spin systems, to assign the spin systems to residues. The inputs to our framework can be as few as two commonly used spectra, i.e., CBCA(CO)NH and HNCACB. Different from the existing peak picking and resonance assignment methods that treat peaks as the units, our method is based on 'slices', which are one-dimensional vectors in three-dimensional spectra that correspond to certain ([Formula: see text]) values. Experimental results on both benchmark simulated data sets and four real protein data sets demonstrate that our method significantly outperforms the state-of-the-art methods while using a less number of spectra than those methods. Our method is freely available at http://sfb.kaust.edu.sa/Pages/Software.aspx.

Analysis of labor employment assessment on production machine to minimize time production

NASA Astrophysics Data System (ADS)

Hernawati, Tri; Suliawati; Sari Gumay, Vita

2018-03-01

Every company both in the field of service and manufacturing always trying to pass efficiency of it’s resource use. One resource that has an important role is labor. Labor has different efficiency levels for different jobs anyway. Problems related to the optimal allocation of labor that has different levels of efficiency for different jobs are called assignment problems, which is a special case of linear programming. In this research, Analysis of Labor Employment Assesment on Production Machine to Minimize Time Production, in PT PDM is done by using Hungarian algorithm. The aim of the research is to get the assignment of optimal labor on production machine to minimize time production. The results showed that the assignment of existing labor is not suitable because the time of completion of the assignment is longer than the assignment by using the Hungarian algorithm. By applying the Hungarian algorithm obtained time savings of 16%.

Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms

NASA Astrophysics Data System (ADS)

Kwok, Kwan S.; Driessen, Brian J.; Phillips, Cynthia A.; Tovey, Craig A.

1997-09-01

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a silicon graphics crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of network optimization methods, and we expect this to be a fruitful area for future research.

Protein Side-Chain Resonance Assignment and NOE Assignment Using RDC-Defined Backbones without TOCSY Data3

PubMed Central

Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall

2011-01-01

One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Unfortunately, these TOCSY experiments perform poorly on large proteins. To overcome this deficiency, we present a novel algorithm, called NASCA (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. After casting the assignment problem into a Markov Random Field (MRF), NASCA extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Tests on five proteins show that NASCA assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. The final structures computed using the NOE distance restraints assigned by NASCA have backbone RMSD 0.8 – 1.5 Å from the reference structures determined by traditional NMR approaches. PMID:21706248

Optimization of municipal waste collection scheduling and routing using vehicle assignment problem (case study of Surabaya city waste collection)

NASA Astrophysics Data System (ADS)

Ramdhani, M. N.; Baihaqi, I.; Siswanto, N.

2018-04-01

Waste collection and disposal become a major problem for many metropolitan cities. Growing population, limited vehicles, and increased road traffic make the waste transportation become more complex. Waste collection involves some key considerations, such as vehicle assignment, vehicle routes, and vehicle scheduling. In the scheduling process, each vehicle has a scheduled departure that serve each route. Therefore, vehicle’s assignments should consider the time required to finish one assigment on that route. The objective of this study is to minimize the number of vehicles needed to serve all routes by developing a mathematical model which uses assignment problem approach. The first step is to generated possible routes from the existing routes, followed by vehicle assignments for those certain routes. The result of the model shows fewer vehicles required to perform waste collection asa well as the the number of journeys that the vehicle to collect the waste to the landfill. The comparison of existing conditions with the model result indicates that the latter’s has better condition than the existing condition because each vehicle with certain route has an equal workload, all the result’s model has the maximum of two journeys for each route.

Sign problem and Monte Carlo calculations beyond Lefschetz thimbles

DOE PAGES

Alexandru, Andrei; Basar, Gokce; Bedaque, Paulo F.; ...

2016-05-10

We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action (“Lefschetz thimble”). We describe a family of such manifolds that interpolate between the tangent space at one critical point (where the sign problem is milder compared to the real plane but in some cases still severe) and the union of relevant thimbles (where the sign problem is mild but a multimodal distribution function complicates the Monte Carlo sampling). As a result, we exemplify this approach using amore » simple 0+1 dimensional fermion model previously used on sign problem studies and show that it can solve the model for some parameter values where a solution using Lefschetz thimbles was elusive.« less

A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

PubMed

Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

2016-03-01

Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

In-situ Multimodal Imaging and Spectroscopy of Mg Electrodeposition at Electrode-Electrolyte Interfaces

NASA Astrophysics Data System (ADS)

Wu, Yimin A.; Yin, Zuwei; Farmand, Maryam; Yu, Young-Sang; Shapiro, David A.; Liao, Hong-Gang; Liang, Wen-I.; Chu, Ying-Hao; Zheng, Haimei

2017-02-01

We report the study of Mg cathodic electrochemical deposition on Ti and Au electrode using a multimodal approach by examining the sample area in-situ using liquid cell transmission electron microscopy (TEM), scanning transmission X-ray microscopy (STXM) and X-ray absorption spectroscopy (XAS). Magnesium Aluminum Chloride Complex was synthesized and utilized as electrolyte, where non-reversible features during in situ charging-discharging cycles were observed. During charging, a uniform Mg film was deposited on the electrode, which is consistent with the intrinsic non-dendritic nature of Mg deposition in Mg ion batteries. The Mg thin film was not dissolvable during the following discharge process. We found that such Mg thin film is hexacoordinated Mg compounds by in-situ STXM and XAS. This study provides insights on the non-reversibility issue and failure mechanism of Mg ion batteries. Also, our method provides a novel generic method to understand the in situ battery chemistry without any further sample processing, which can preserve the original nature of battery materials or electrodeposited materials. This multimodal in situ imaging and spectroscopy provides many opportunities to attack complex problems that span orders of magnitude in length and time scale, which can be applied to a broad range of the energy storage systems.

Multi-modal Patient Cohort Identification from EEG Report and Signal Data

PubMed Central

Goodwin, Travis R.; Harabagiu, Sanda M.

2016-01-01

Clinical electroencephalography (EEG) is the most important investigation in the diagnosis and management of epilepsies. An EEG records the electrical activity along the scalp and measures spontaneous electrical activity of the brain. Because the EEG signal is complex, its interpretation is known to produce moderate inter-observer agreement among neurologists. This problem can be addressed by providing clinical experts with the ability to automatically retrieve similar EEG signals and EEG reports through a patient cohort retrieval system operating on a vast archive of EEG data. In this paper, we present a multi-modal EEG patient cohort retrieval system called MERCuRY which leverages the heterogeneous nature of EEG data by processing both the clinical narratives from EEG reports as well as the raw electrode potentials derived from the recorded EEG signal data. At the core of MERCuRY is a novel multimodal clinical indexing scheme which relies on EEG data representations obtained through deep learning. The index is used by two clinical relevance models that we have generated for identifying patient cohorts satisfying the inclusion and exclusion criteria expressed in natural language queries. Evaluations of the MERCuRY system measured the relevance of the patient cohorts, obtaining MAP scores of 69.87% and a NDCG of 83.21%. PMID:28269938

Rotational electrical impedance tomography using electrodes with limited surface coverage provides window for multimodal sensing

NASA Astrophysics Data System (ADS)

Lehti-Polojärvi, Mari; Koskela, Olli; Seppänen, Aku; Figueiras, Edite; Hyttinen, Jari

2018-02-01

Electrical impedance tomography (EIT) is an imaging method that could become a valuable tool in multimodal applications. One challenge in simultaneous multimodal imaging is that typically the EIT electrodes cover a large portion of the object surface. This paper investigates the feasibility of rotational EIT (rEIT) in applications where electrodes cover only a limited angle of the surface of the object. In the studied rEIT, the object is rotated a full 360° during a set of measurements to increase the information content of the data. We call this approach limited angle full revolution rEIT (LAFR-rEIT). We test LAFR-rEIT setups in two-dimensional geometries with computational and experimental data. We use up to 256 rotational measurement positions, which requires a new way to solve the forward and inverse problem of rEIT. For this, we provide a modification, available for EIDORS, in the supplementary material. The computational results demonstrate that LAFR-rEIT with eight electrodes produce the same image quality as conventional 16-electrode rEIT, when data from an adequate number of rotational measurement positions are used. Both computational and experimental results indicate that the novel LAFR-rEIT provides good EIT with setups with limited surface coverage and a small number of electrodes.

Sparse Representation Based Frequency Detection and Uncertainty Reduction in Blade Tip Timing Measurement for Multi-Mode Blade Vibration Monitoring

PubMed Central

Pan, Minghao; Yang, Yongmin; Guan, Fengjiao; Hu, Haifeng; Xu, Hailong

2017-01-01

The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number. PMID:28758952

In-situ Multimodal Imaging and Spectroscopy of Mg Electrodeposition at Electrode-Electrolyte Interfaces

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

Wu, Yimin A.; Yin, Zuwei; Farmand, Maryam

We report the study of Mg cathodic electrochemical deposition on Ti and Au electrode using a multimodal approach by examining the sample area in-situ using liquid cell transmission electron microscopy (TEM), scanning transmission X-ray microscopy (STXM) and X-ray absorption spectroscopy (XAS). Magnesium Aluminum Chloride Complex was synthesized and utilized as electrolyte, where non-reversible features during in situ charging-discharging cycles were observed. During charging, a uniform Mg film was deposited on the electrode, which is consistent with the intrinsic non-dendritic nature of Mg deposition in Mg ion batteries. The Mg thin film was not dissolvable during the following discharge process. Wemore » found that such Mg thin film is hexacoordinated Mg compounds by in-situ STXM and XAS. This study provides insights on the non-reversibility issue and failure mechanism of Mg ion batteries. Also, our method provides a novel generic method to understand the in situ battery chemistry without any further sample processing, which can preserve the original nature of battery materials or electrodeposited materials. This multimodal in situ imaging and spectroscopy provides many opportunities to attack complex problems that span orders of magnitude in length and time scale, which can be applied to a broad range of the energy storage systems.« less

In-situ Multimodal Imaging and Spectroscopy of Mg Electrodeposition at Electrode-Electrolyte Interfaces

DOE PAGES

Wu, Yimin A.; Yin, Zuwei; Farmand, Maryam; ...

2017-02-10

We report the study of Mg cathodic electrochemical deposition on Ti and Au electrode using a multimodal approach by examining the sample area in-situ using liquid cell transmission electron microscopy (TEM), scanning transmission X-ray microscopy (STXM) and X-ray absorption spectroscopy (XAS). Magnesium Aluminum Chloride Complex was synthesized and utilized as electrolyte, where non-reversible features during in situ charging-discharging cycles were observed. During charging, a uniform Mg film was deposited on the electrode, which is consistent with the intrinsic non-dendritic nature of Mg deposition in Mg ion batteries. The Mg thin film was not dissolvable during the following discharge process. Wemore » found that such Mg thin film is hexacoordinated Mg compounds by in-situ STXM and XAS. This study provides insights on the non-reversibility issue and failure mechanism of Mg ion batteries. Also, our method provides a novel generic method to understand the in situ battery chemistry without any further sample processing, which can preserve the original nature of battery materials or electrodeposited materials. This multimodal in situ imaging and spectroscopy provides many opportunities to attack complex problems that span orders of magnitude in length and time scale, which can be applied to a broad range of the energy storage systems.« less

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

In-situ Multimodal Imaging and Spectroscopy of Mg Electrodeposition at Electrode-Electrolyte Interfaces.

PubMed

Wu, Yimin A; Yin, Zuwei; Farmand, Maryam; Yu, Young-Sang; Shapiro, David A; Liao, Hong-Gang; Liang, Wen-I; Chu, Ying-Hao; Zheng, Haimei

2017-02-10

We report the study of Mg cathodic electrochemical deposition on Ti and Au electrode using a multimodal approach by examining the sample area in-situ using liquid cell transmission electron microscopy (TEM), scanning transmission X-ray microscopy (STXM) and X-ray absorption spectroscopy (XAS). Magnesium Aluminum Chloride Complex was synthesized and utilized as electrolyte, where non-reversible features during in situ charging-discharging cycles were observed. During charging, a uniform Mg film was deposited on the electrode, which is consistent with the intrinsic non-dendritic nature of Mg deposition in Mg ion batteries. The Mg thin film was not dissolvable during the following discharge process. We found that such Mg thin film is hexacoordinated Mg compounds by in-situ STXM and XAS. This study provides insights on the non-reversibility issue and failure mechanism of Mg ion batteries. Also, our method provides a novel generic method to understand the in situ battery chemistry without any further sample processing, which can preserve the original nature of battery materials or electrodeposited materials. This multimodal in situ imaging and spectroscopy provides many opportunities to attack complex problems that span orders of magnitude in length and time scale, which can be applied to a broad range of the energy storage systems.

In-situ Multimodal Imaging and Spectroscopy of Mg Electrodeposition at Electrode-Electrolyte Interfaces

PubMed Central

Wu, Yimin A.; Yin, Zuwei; Farmand, Maryam; Yu, Young-Sang; Shapiro, David A.; Liao, Hong-Gang; Liang, Wen-I; Chu, Ying-Hao; Zheng, Haimei

2017-01-01

We report the study of Mg cathodic electrochemical deposition on Ti and Au electrode using a multimodal approach by examining the sample area in-situ using liquid cell transmission electron microscopy (TEM), scanning transmission X-ray microscopy (STXM) and X-ray absorption spectroscopy (XAS). Magnesium Aluminum Chloride Complex was synthesized and utilized as electrolyte, where non-reversible features during in situ charging-discharging cycles were observed. During charging, a uniform Mg film was deposited on the electrode, which is consistent with the intrinsic non-dendritic nature of Mg deposition in Mg ion batteries. The Mg thin film was not dissolvable during the following discharge process. We found that such Mg thin film is hexacoordinated Mg compounds by in-situ STXM and XAS. This study provides insights on the non-reversibility issue and failure mechanism of Mg ion batteries. Also, our method provides a novel generic method to understand the in situ battery chemistry without any further sample processing, which can preserve the original nature of battery materials or electrodeposited materials. This multimodal in situ imaging and spectroscopy provides many opportunities to attack complex problems that span orders of magnitude in length and time scale, which can be applied to a broad range of the energy storage systems. PMID:28186175

Mechatronics in monitoring, simulation, and diagnostics of industrial and biological processes

NASA Astrophysics Data System (ADS)

Golnik, Natalia; Dobosz, Marek; Jakubowska, Małgorzata; Kościelny, Jan M.; Kujawińska, Małgorzata; Pałko, Tadeusz; Putz, Barbara; Sitnik, Robert; Wnuk, Paweł; Woźniak, Adam

2013-10-01

The paper describes a number of research projects of the Faculty of Mechatronics of Warsaw University of Technology in order to illustrate the use of common mechatronics and optomechatronics approach in solving multidisciplinary technical problems. Projects on sensors development, measurement and industrial control systems, multimodal data capture and advance systems for monitoring and diagnostics of industrial processes are presented and discussed.

Joint Sparsity-Based Robust Multimodal Biometrics Recognition

DTIC Science & Technology

2012-10-07

Nasrabadi, Rama Chellappa William Marsh Rice University Office of Sponsored Research William Marsh Rice University Houston, TX 77005 - REPORT...Shekhar1, Vishal M. Patel1, Nasser M. Nasrabadi2, and Rama Chellappa1 1 University of Maryland, College Park, USA 2 Army Research Lab, Adelphi, USA...authentication. Unfortunately these systems often have to deal with some of the following inevitable problems [1]: (a) Noisy data (b) Non- universality

Multimodal Representation Contributes to the Complex Development of Science Literacy in a College Biology Class

ERIC Educational Resources Information Center

Bennett, William Drew

2011-01-01

This study is an investigation into the science literacy of college genetics students who were given a modified curriculum to address specific teaching and learning problems from a previous class. This study arose out of an interest by the professor and researcher to determine how well students in the class Human Genetics in the 21st Century…

3D Data Acquisition Platform for Human Activity Understanding

DTIC Science & Technology

2016-03-02

3D data. The support for the acquisition of such research instrumentation have significantly facilitated our current and future research and educate ...SECURITY CLASSIFICATION OF: In this project, we incorporated motion capture devices, 3D vision sensors, and EMG sensors to cross validate...multimodality data acquisition, and address fundamental research problems of representation and invariant description of 3D data, human motion modeling and

Maternal education preferences moderate the effects of mandatory employment and education programs on child positive and problem behaviors

PubMed Central

Gassman-Pines, Anna; Godfrey, Erin B.; Yoshikawa, Hirokazu

2012-01-01

Grounded in Person-Environment Fit Theory, this study examined whether low-income mothers' preferences for education moderated the effects of employment- and education-focused welfare programs on children's positive and problem behaviors. The sample included 1,365 families with children between ages 3 and 5 at study entry. Results 5 years after random assignment, when children were ages 8 to 10, indicated that mothers' education preferences did moderate program impacts on teacher-reported child behavior problems and positive behavior. Children whose mothers were assigned to the education program were rated by teachers to have less externalizing behavior and more positive behavior than children whose mothers were assigned to the employment program, but only when mothers had strong preferences for education. PMID:22861169

Intrasubject multimodal groupwise registration with the conditional template entropy.

PubMed

Polfliet, Mathias; Klein, Stefan; Huizinga, Wyke; Paulides, Margarethus M; Niessen, Wiro J; Vandemeulebroucke, Jef

2018-05-01

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Particle swarm optimization and gravitational wave data analysis: Performance on a binary inspiral testbed

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

Wang Yan; Mohanty, Soumya D.; Center for Gravitational Wave Astronomy, Department of Physics and Astronomy, University of Texas at Brownsville, 80 Fort Brown, Brownsville, Texas 78520

2010-03-15

The detection and estimation of gravitational wave signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Because of noise in the data, the function to be maximized is often highly multimodal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the particle swarm optimization method in this context. The method ismore » applied to a test bed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that particle swarm optimization works well in the presence of high multimodality, making it a viable candidate method for further applications in gravitational wave data analysis.« less

Negotiating Multicollinearity with Spike-and-Slab Priors.

PubMed

Ročková, Veronika; George, Edward I

2014-08-01

In multiple regression under the normal linear model, the presence of multicollinearity is well known to lead to unreliable and unstable maximum likelihood estimates. This can be particularly troublesome for the problem of variable selection where it becomes more difficult to distinguish between subset models. Here we show how adding a spike-and-slab prior mitigates this difficulty by filtering the likelihood surface into a posterior distribution that allocates the relevant likelihood information to each of the subset model modes. For identification of promising high posterior models in this setting, we consider three EM algorithms, the fast closed form EMVS version of Rockova and George (2014) and two new versions designed for variants of the spike-and-slab formulation. For a multimodal posterior under multicollinearity, we compare the regions of convergence of these three algorithms. Deterministic annealing versions of the EMVS algorithm are seen to substantially mitigate this multimodality. A single simple running example is used for illustration throughout.

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Interactive multi-mode blade impact analysis

NASA Technical Reports Server (NTRS)

Alexander, A.; Cornell, R. W.

1978-01-01

The theoretical methodology used in developing an analysis for the response of turbine engine fan blades subjected to soft-body (bird) impacts is reported, and the computer program developed using this methodology as its basis is described. This computer program is an outgrowth of two programs that were previously developed for the purpose of studying problems of a similar nature (a 3-mode beam impact analysis and a multi-mode beam impact analysis). The present program utilizes an improved missile model that is interactively coupled with blade motion which is more consistent with actual observations. It takes into account local deformation at the impact area, blade camber effects, and the spreading of the impacted missile mass on the blade surface. In addition, it accommodates plate-type mode shapes. The analysis capability in this computer program represents a significant improvement in the development of the methodology for evaluating potential fan blade materials and designs with regard to foreign object impact resistance.

Supervising Unsuccessful Student Teaching Assignments: Two Terminator's Tales.

ERIC Educational Resources Information Center

St. Maurice, Henry

2001-01-01

Discusses problems that arise when there is a conflict between a student teacher and the supervising teacher and when a student teacher does not perform satisfactorily. Focuses on how supervisors deal with failed assignments and how beginning teachers improve their teaching and learn from failed assignments. (Contains 21 references.) (JOW)

The Biomes of Homewood: Interactive Map Software

ERIC Educational Resources Information Center

Shingles, Richard; Feist, Theron; Brosnan, Rae

2005-01-01

To build a learning community, the General Biology faculty at Johns Hopkins University conducted collaborative, problem-based learning assignments outside of class in which students are assigned to specific areas on campus, and gather and report data about their area. To overcome the logistics challenges presented by conducting such assignments in…

Multicasting for all-optical multifiber networks

NASA Astrophysics Data System (ADS)

Kã¶Ksal, Fatih; Ersoy, Cem

2007-02-01

All-optical wavelength-routed WDM WANs can support the high bandwidth and the long session duration requirements of the application scenarios such as interactive distance learning or on-line diagnosis of patients simultaneously in different hospitals. However, multifiber and limited sparse light splitting and wavelength conversion capabilities of switches result in a difficult optimization problem. We attack this problem using a layered graph model. The problem is defined as a k-edge-disjoint degree-constrained Steiner tree problem for routing and fiber and wavelength assignment of k multicasts. A mixed integer linear programming formulation for the problem is given, and a solution using CPLEX is provided. However, the complexity of the problem grows quickly with respect to the number of edges in the layered graph, which depends on the number of nodes, fibers, wavelengths, and multicast sessions. Hence, we propose two heuristics layered all-optical multicast algorithm [(LAMA) and conservative fiber and wavelength assignment (C-FWA)] to compare with CPLEX, existing work, and unicasting. Extensive computational experiments show that LAMA's performance is very close to CPLEX, and it is significantly better than existing work and C-FWA for nearly all metrics, since LAMA jointly optimizes routing and fiber-wavelength assignment phases compared with the other candidates, which attack the problem by decomposing two phases. Experiments also show that important metrics (e.g., session and group blocking probability, transmitter wavelength, and fiber conversion resources) are adversely affected by the separation of two phases. Finally, the fiber-wavelength assignment strategy of C-FWA (Ex-Fit) uses wavelength and fiber conversion resources more effectively than the First Fit.

Contributions au probleme d'affectation des types d'avion

NASA Astrophysics Data System (ADS)

Belanger, Nicolas

In this thesis, we approach the problem of assigning aircraft types to flights (what is called aircraft fleet assignment) in a strategic planning context. The literature mentions many studies considering this problem on a daily flight schedule basis, but the proposed models do no allow to consider many elements that are either necessary to assure the practical feasibility of the solutions, or relevant to get more beneficial solutions. After describing the practical context of the problem (Chapter 1) and presenting the literature on the subject (Chapter 2), we propose new models and solution approaches to improve the quality of' the solutions obtained. The general scheme of the thesis is presented in Chapter 3. We summarize here the models and solution approaches that we propose; and present the main elements of our conclusions. First, in Chapter 4, we consider the problem of aircraft fleet Assignment over a weekly flight schedule, integrating into the objective an homogeneity factor for driving the choice of the aircraft types for the flights with the same flight number over the week. We present an integer linear model based on a time-space multicommodity network. This model includes, among others, decision variables relative to the aircraft type assigned to each flight and to the dominant aircraft type assigned to each flight number. We present in Chapter 5 the results of a research project made in collaboration with Air Canada within a consulting contract. The project aimed at analyzing the relevance for the planners of using an optimization software to help them to first identify non profitable flight legs in the network, and second to efficiently establish the aircraft fleet assignment. In this chapter, we propose an iterative approach to take into account the fact that the passenger demand is not known on a leg basis, but rather on an origin-destination and departure time basis. Finally, in Chapter 6, we propose a model and a solution approach that aim at solving the fleet assignment problem over a periodic schedule in the case where there is a flexibility on the flight departure times and the fleet size must be minimized. Moreover, the objective of this model includes the impact on the passenger demand for each flight of the variation of the flight departure times and the closing of the departure times of consecutive flights connecting the same pairs of stations. (Abstract shortened by UMI.)

Prevention of Serious Conduct Problems in Youth with Attention Deficit/Hyperactivity Disorder

PubMed Central

Villodas, Miguel T.; Pfiffner, Linda J.; McBurnett, Keith

2013-01-01

The purpose of this review is to discuss issues in the prevention of serious conduct problems among children and adolescents with Attention Deficit/Hyperactivity Disorder (ADHD). We begin by reviewing research on the common genetic and environmental etiological factors, developmental trajectories, characteristics, and impairments associated with ADHD and comorbid Oppositional Defiant and Conduct Disorders. Next, we present empirically-based models for intervention with children and adolescents with ADHD that are at risk of developing serious conduct problems and detail the evidence supporting these models. Researchers have demonstrated the utility of medication and psychosocial intervention approaches to treat youth with these problems, but current evidence appears to support the superiority of multi-modal treatments that include both approaches. Future directions for researchers are discussed. PMID:23082741

The effect of wind and moisture gradients on the arbitrary assignment of cloud motions to a vertical coordinate system in two Sesame cases

NASA Technical Reports Server (NTRS)

Peslen, C. A.; Koch, S. E.; Uccellini, L. W.

1984-01-01

Satellite-derived cloud motion 'wind' vectors (CMV) are increasingly used in mesoscale and in global analyses, and questions have been raised regarding the uncertainty of the level assignment for the CMV. One of two major problems in selecting a level for the CMV is related to uncertainties in assigning the motion vector to either the cloud top or base. The second problem is related to the inability to transfer the 'wind' derived from the CMV at individually specified heights to a standard coordinated surface. The present investigation has the objective to determine if the arbitrary level assignment represents a serious obstacle to the use of cloud motion wind vectors in the mesoscale analysis of a severe storm environment.

Multi Objective Decision Analysis for Assignment Problems

DTIC Science & Technology

2011-03-01

needed data or try to get data from related databases. 2.3.8 Deterministic Analysis In order to determine an overall score for each...The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Turkish Air...DECISION ANALYSIS FOR ASSIGNMENT PROBLEMS THESIS Presented to the Faculty Department of Operational Sciences Graduate School of

Using the Same Problem with Different Techniques in Programming Assignments: An Empirical Study of Its Effectiveness

ERIC Educational Resources Information Center

Newby, Michael; Nguyen, ThuyUyen H.

2010-01-01

This paper examines the effectiveness of a technique that first appeared as a Teaching Tip in the Journal of Information Systems Education. In this approach the same problem is used in every programming assignment within a course, but the students are required to use different programming techniques. This approach was used in an intermediate C++…

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment

NASA Astrophysics Data System (ADS)

Barnawi, Waleed T.

Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned vehicle. Civil applications that involve missions where human observability would be limited could benefit from the independent UAV task assignment, such as exploration and fire surveillance are also notable uses for this approach.

Addition of a Sagittal Cervical Posture Corrective Orthotic Device to a Multimodal Rehabilitation Program Improves Short- and Long-Term Outcomes in Patients With Discogenic Cervical Radiculopathy.

PubMed

Moustafa, Ibrahim M; Diab, Aliaa A; Taha, Shimaa; Harrison, Deed E

2016-12-01

To investigate the immediate and 1-year effects of a multimodal program, with cervical lordosis and anterior head translation (AHT) rehabilitation, on the intensity of pain, disability, and peripheral and central nervous system function in patients with discogenic cervical radiculopathy (CR). A randomized controlled trial with 1-year and 10-week follow-up. University research laboratory. Patients (N=60; 27 men) with chronic discogenic CR, a defined hypolordotic cervical spine, and AHT posture were randomly assigned to a control group (n=30; mean age, 43.9±6.2y) or an intervention group (n=30; mean age, 41.5±3.7y). Both groups received the multimodal program; in addition, the intervention group received the Denneroll cervical traction device. AHT distance, cervical lordosis, arm pain intensity, neck pain intensity, and disability (Neck Disability Index [NDI]), dermatomal somatosensory evoked potentials (DSSEPs), and central somatosensory conduction time (N13-N20). Measures were assessed at 3 time intervals: baseline, 10 weeks, and 1-year follow-up. After 10 weeks of treatment, between-group analysis showed equal improvement in arm pain intensity (P=.40), neck pain intensity (P=.60), and latency of DSSEPs (P=.60) in both intervention and control groups. However, also at 10 weeks, there were significant differences between groups, favoring the intervention group for cervical lordosis (P<.0005), AHT distance (P<.0005), amplitude of DSSEPs (P<.0005), N13 to N20 conduction time (P<.0005), and NDI (P<.0005). Although at 1-year follow-up, between-group analysis identified a regression back to baseline values for the control group. Thus, all variables were significantly different, favoring the intervention group at 1-year follow-up: cervical lordosis (P<.0005), AHT distance (P<.0005), latency and amplitude of DSSEPs (P<.0005), N13 to N20 conduction time (P<.0005), intensity of neck and arm pain, and NDI (P<.0005). The addition of the Denneroll cervical orthotic device to a multimodal program positively affected discogenic CR outcomes at long-term follow-up. We speculate that improved cervical lordosis and reduced AHT contributed to our findings. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

On the problem of resonance assignments in solid state NMR of uniformly 15N, 13C-labeled proteins

NASA Astrophysics Data System (ADS)

Tycko, Robert

2015-04-01

Determination of accurate resonance assignments from multidimensional chemical shift correlation spectra is one of the major problems in biomolecular solid state NMR, particularly for relative large proteins with less-than-ideal NMR linewidths. This article investigates the difficulty of resonance assignment, using a computational Monte Carlo/simulated annealing (MCSA) algorithm to search for assignments from artificial three-dimensional spectra that are constructed from the reported isotropic 15N and 13C chemical shifts of two proteins whose structures have been determined by solution NMR methods. The results demonstrate how assignment simulations can provide new insights into factors that affect the assignment process, which can then help guide the design of experimental strategies. Specifically, simulations are performed for the catalytic domain of SrtC (147 residues, primarily β-sheet secondary structure) and the N-terminal domain of MLKL (166 residues, primarily α-helical secondary structure). Assuming unambiguous residue-type assignments and four ideal three-dimensional data sets (NCACX, NCOCX, CONCA, and CANCA), uncertainties in chemical shifts must be less than 0.4 ppm for assignments for SrtC to be unique, and less than 0.2 ppm for MLKL. Eliminating CANCA data has no significant effect, but additionally eliminating CONCA data leads to more stringent requirements for chemical shift precision. Introducing moderate ambiguities in residue-type assignments does not have a significant effect.

Due-Window Assignment Scheduling with Variable Job Processing Times

PubMed Central

Wu, Yu-Bin

2015-01-01

We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost function includes earliness, tardiness, the window location, window size, and weighted number of tardy jobs. We prove that the problem can be solved in polynomial time. PMID:25918745

Kernel Manifold Alignment for Domain Adaptation.

PubMed

Tuia, Devis; Camps-Valls, Gustau

2016-01-01

The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. However, multimodal architectures must rely on models able to adapt to changes in the data distribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation problem as domain adaptation. In this paper, instead of adapting the trained models themselves, we alternatively focus on finding mappings of the data sources into a common, semantically meaningful, representation domain. This field of manifold alignment extends traditional techniques in statistics such as canonical correlation analysis (CCA) to deal with nonlinear adaptation and possibly non-corresponding data pairs between the domains. We introduce a kernel method for manifold alignment (KEMA) that can match an arbitrary number of data sources without needing corresponding pairs, just few labeled examples in all domains. KEMA has interesting properties: 1) it generalizes other manifold alignment methods, 2) it can align manifolds of very different complexities, performing a discriminative alignment preserving each manifold inner structure, 3) it can define a domain-specific metric to cope with multimodal specificities, 4) it can align data spaces of different dimensionality, 5) it is robust to strong nonlinear feature deformations, and 6) it is closed-form invertible, which allows transfer across-domains and data synthesis. To authors' knowledge this is the first method addressing all these important issues at once. We also present a reduced-rank version of KEMA for computational efficiency, and discuss the generalization performance of KEMA under Rademacher principles of stability. Aligning multimodal data with KEMA reports outstanding benefits when used as a data pre-conditioner step in the standard data analysis processing chain. KEMA exhibits very good performance over competing methods in synthetic controlled examples, visual object recognition and recognition of facial expressions tasks. KEMA is especially well-suited to deal with high-dimensional problems, such as images and videos, and under complicated distortions, twists and warpings of the data manifolds. A fully functional toolbox is available at https://github.com/dtuia/KEMA.git.

Learner-Centered Teaching and Improving Learning by Writing Down the Statement of Problems in an Introductory Physics Course

NASA Astrophysics Data System (ADS)

Aurora, Tarlok

2005-04-01

In a calculus-based introductory physics course, students were assigned to write the statements of word problems (along with the accompanying diagrams if any), analyze these, identify important concepts/equations and try to solve these end-of- chapter homework problems. They were required to bring to class their written assignment until the chapter was completed in lecture. These were quickly checked at the beginning of the class. In addition, re-doing selected solved examples in the textbook were assigned as homework. Where possible, students were asked to look for similarities between the solved-examples and the end-of-the-chapter problems, or occasionally these were brought to the students' attention. It was observed that many students were able to solve several of the solved-examples on the test even though the instructor had not solved these in class. This was seen as an improvement over the previous years. It made the students more responsible for their learning. Another benefit was that it alleviated the problems previously created by many students not bringing the textbooks to class. It allowed more time for problem solving/discussions in class.

Frequency assignments for HFDF receivers in a search and rescue network

NASA Astrophysics Data System (ADS)

Johnson, Krista E.

1990-03-01

This thesis applies a multiobjective linear programming approach to the problem of assigning frequencies to high frequency direction finding (HFDF) receivers in a search-and-rescue network in order to maximize the expected number of geolocations of vessels in distress. The problem is formulated as a multiobjective integer linear programming problem. The integrality of the solutions is guaranteed by the totally unimodularity of the A-matrix. Two approaches are taken to solve the multiobjective linear programming problem: (1) the multiobjective simplex method as implemented in ADBASE; and (2) an iterative approach. In this approach, the individual objective functions are weighted and combined in a single additive objective function. The resulting single objective problem is expressed as a network programming problem and solved using SAS NETFLOW. The process is then repeated with different weightings for the objective functions. The solutions obtained from the multiobjective linear programs are evaluated using a FORTRAN program to determine which solution provides the greatest expected number of geolocations. This solution is then compared to the sample mean and standard deviation for the expected number of geolocations resulting from 10,000 random frequency assignments for the network.

Fleet Assignment Using Collective Intelligence

NASA Technical Reports Server (NTRS)

Antoine, Nicolas E.; Bieniawski, Stefan R.; Kroo, Ilan M.; Wolpert, David H.

2004-01-01

Airline fleet assignment involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of an agent-based integer optimization algorithm to a "cold start" fleet assignment problem. Results show that the optimizer can successfully solve such highly- constrained problems (129 variables, 184 constraints).

Novel probabilistic neuroclassifier

NASA Astrophysics Data System (ADS)

Hong, Jiang; Serpen, Gursel

2003-09-01

A novel probabilistic potential function neural network classifier algorithm to deal with classes which are multi-modally distributed and formed from sets of disjoint pattern clusters is proposed in this paper. The proposed classifier has a number of desirable properties which distinguish it from other neural network classifiers. A complete description of the algorithm in terms of its architecture and the pseudocode is presented. Simulation analysis of the newly proposed neuro-classifier algorithm on a set of benchmark problems is presented. Benchmark problems tested include IRIS, Sonar, Vowel Recognition, Two-Spiral, Wisconsin Breast Cancer, Cleveland Heart Disease and Thyroid Gland Disease. Simulation results indicate that the proposed neuro-classifier performs consistently better for a subset of problems for which other neural classifiers perform relatively poorly.

[The application of universal adhesives in dental bonding].

PubMed

Guo, Jingmei; Lei, Wenlong; Yang, Hongye; Huang, Cui

2016-03-01

The bonding restoration has become an important clinical technique for the development of dental bonding technology. Because of its easy operation and the maximum preservation of tooth tissues, bonding repair is widely used in dental restoration. The recent multi-mode universal adhesives have brought new progress in dental bonding restoration. In this article the universal adhesives were reviewed according to its definition, development, improvement, application features and possible problems.

Two Novel Methods and Multi-Mode Periodic Solutions for the Fermi-Pasta-Ulam Model

NASA Astrophysics Data System (ADS)

Arioli, Gianni; Koch, Hans; Terracini, Susanna

2005-04-01

We introduce two novel methods for studying periodic solutions of the FPU β-model, both numerically and rigorously. One is a variational approach, based on the dual formulation of the problem, and the other involves computer-assisted proofs. These methods are used e.g. to construct a new type of solutions, whose energy is spread among several modes, associated with closely spaced resonances.

Multicomponent-flow analyses by multimode method of characteristics

USGS Publications Warehouse

Lai, Chintu

1994-01-01

For unsteady open-channel flows having N interacting unknown variables, a system of N mutually independent, partial differential equations can be used to describe the flow-field. The system generally belongs to marching-type problems and permits transformation into characteristic equations that are associated with N distinct characteristics directions. Because characteristics can be considered 'wave' or 'disturbance' propagation, a fluvial system so described can be viewed as adequately definable using these N component waves. A numerical algorithm to solve the N families of characteristics can then be introduced for formulation of an N-component flow-simulation model. The multimode method of characteristics (MMOC), a new numerical scheme that has a combined capacity of several specified-time-interval (STI) schemes of the method of characteristics, makes numerical modeling of such N-component riverine flows feasible and attainable. Merging different STI schemes yields different kinds of MMOC schemes, for which two kinds are displayed herein. With the MMOC, each characteristics is dynamically treated by an appropriate numerical mode, which should lead to an effective and suitable global simulation, covering various types of unsteady flow. The scheme is always linearly stable and its numerical accuracy can be systematically analyzed. By increasing the N value, one can develop a progressively sophisticated model that addresses increasingly complex river-mechanics problems.

Evaluation of Goal Programming for the Optimal Assignment of Inspectors to Construction Projects

DTIC Science & Technology

1988-09-01

Inputs ..... .............. 90 Equation Coefficients . ....... .. 90 Weights, Priorities and the AHP . . 91 Right-Hand Side Values ........ .. 91...the AHP Hierarchy with k Levels . . 36 3. Sample Matrix for Pairwise Comparison ........ .. 37 4. Assignment of I and p for Example Problem...Weights for Example Problem ... 61 3. AHP Weights and Coefficient ci, Values. ........ 63 vii AFIT/GEM/LSM/88S-16 Abstract The purpose of this study was

An Examination of Problems and Solutions Related to the Chronic "Revolving Door" Alcohol Abuser. DHSS Planning Guideline #1, Task Assignment #1.11. Long-Term Support, Chronic Alcoholism and Other Drug Abuse.

ERIC Educational Resources Information Center

Vick, John W.; Houden, Dorothy

This report contains recommendations of a Wisconsin Task Assignment Steering Committee created to explore solutions to some significant problems facing adult chronic "revolving-detox-door" alcohol abusers (CRA's), persons with repeated admissions for detoxification services; and to examine the system that serves and funds them. This…

Robotics and STEM Learning: Students' Achievements in Assignments According to the P3 Task Taxonomy--Practice, Problem Solving, and Projects

ERIC Educational Resources Information Center

Barak, Moshe; Assal, Muhammad

2018-01-01

This study presents the case of development and evaluation of a STEM-oriented 30-h robotics course for junior high school students (n = 32). Class activities were designed according to the P3 Task Taxonomy, which included: (1) practice-basic closed-ended tasks and exercises; (2) problem solving--small-scale open-ended assignments in which the…

Scheduling Jobs and a Variable Maintenance on a Single Machine with Common Due-Date Assignment

PubMed Central

Wan, Long

2014-01-01

We investigate a common due-date assignment scheduling problem with a variable maintenance on a single machine. The goal is to minimize the total earliness, tardiness, and due-date cost. We derive some properties on an optimal solution for our problem. For a special case with identical jobs we propose an optimal polynomial time algorithm followed by a numerical example. PMID:25147861

Knowledge-based design of generate-and-patch problem solvers that solve global resource assignment problems

NASA Technical Reports Server (NTRS)

Voigt, Kerstin

1992-01-01

We present MENDER, a knowledge based system that implements software design techniques that are specialized to automatically compile generate-and-patch problem solvers that satisfy global resource assignments problems. We provide empirical evidence of the superior performance of generate-and-patch over generate-and-test: even with constrained generation, for a global constraint in the domain of '2D-floorplanning'. For a second constraint in '2D-floorplanning' we show that even when it is possible to incorporate the constraint into a constrained generator, a generate-and-patch problem solver may satisfy the constraint more rapidly. We also briefly summarize how an extended version of our system applies to a constraint in the domain of 'multiprocessor scheduling'.

Comparison of Virginia's multimodal transportation corridors using cost and demographic analyses.

DOT National Transportation Integrated Search

2006-01-01

This effort was performed in support of VTrans2025, Virginia's long-range multimodal transportation plan, and the VTrans2025 Multimodal Advisory Committee. The effort develops a preliminary approach to evaluating multimodal and highway-only corridor ...

[Expressed Emotions, Burden and Family Functioning in Schizophrenic and Bipolar I Patients of a Multimodal Intervention Program: PRISMA].

PubMed

Ramírez, Alexandra; Palacio, Juan David; Vargas, Cristian; Díaz-Zuluaga, Ana María; Duica, Kelly; Agudelo Berruecos, Yuli; Ospina, Sigifredo; López-Jaramillo, Carlos

Bipolar disorder and schizophrenia are causes of major suffering in patients. Nevertheless, they also affect family and caregiver functioning. This is important because the participation and involvement of families and caregivers is essential to achieve an optimal treatment. To describe the level of expressed emotions, burden, and family functioning of bipolar and schizophrenic patients and, to evaluate the efficacy of the multimodal intervention (MI) versus traditional intervention (TI) in family functioning and its perception by patients and caregivers. A prospective, longitudinal, therapeutic-comparative study was conducted with 302 patients (104 schizophrenic and 198 bipolar patients) who were randomly assigned to a MI or TI groups of a multimodal intervention program PRISMA. MI group received care from psychiatry, general medicine, neuropsychology, family therapy, and occupational therapy. TI group received care from psychiatry and general medicine. Hamilton, Young and SANS, SAPS scales were applied to bipolar and schizophrenic patients, respectively. The EEAG, FEICS, FACES III and ECF were also applied at the initial and final time. There were statistically significant differences in socio- demographic and clinical variables in schizophrenia vs bipolar group: 83% vs 32.2% were male, 37 vs 43 mean age, 96% vs 59% were single, 50% vs 20% unemployed, and 20% vs 40% had college studies. In addition, 2 vs 2.5 numbers of hospitalisations, 18 vs 16 mean age of substance abuse onset and, 55 vs 80 points in EEAG. There were no statistically significant differences in family scales after conducting a multivariate analysis on thr initial and final time in both groups. This study did not show changes in variables of burden and family functioning between bipolar and schizophrenic groups that were under TI vs MI. Copyright © 2016 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Performance of a new one-step multi-mode adhesive on etched vs non-etched enamel on bond strength and interfacial morphology.

PubMed

de Goes, Mario Fernando; Shinohara, Mirela Sanae; Freitas, Marcela Santiago

2014-06-01

To compare microtensile bond strength (μTBS) and interfacial morphology of a new one-step multimode adhesive with a two-step self-etching adhesive and two etch-and-rinse adhesives systems on enamel. Thirty human third molars were sectioned to obtain two enamel fragments. For μTBS, 48 enamel surfaces were ground using 600-grit SiC paper and randomly assigned into 6 groups (n = 8): nonetched Scotchbond Universal [SBU]; etched SBU [SBU-et]; non-etched Clearfil SE Bond [CSE]; etched CSE [CSE-et]; Scotchbond Multi-PURPOSE [SBMP]; Excite [EX]. The etched specimens were conditioned with 37% phosphoric acid for 30 s, each adhesive system was applied according to manufacturers' instructions, and composite resin blocks (Filtek Supreme Plus, 3M ESPE) were incrementally built up. Specimens were sectioned into beams with a cross-sectional area of 0.8-mm2 and tested under tension (1 mm/min). The data were analyzed with oneway ANOVA and Fisher's PLSD (α = 0.05). For interface analysis, two samples from each group were embedded in epoxy resin, polished, and then observed using scanning electron microscopy (SEM). The μTBS values (in MPa) and the standard deviations were: SBU = 27.4 (8.5); SBU-et = 33.6 (9.3); CSE = 28.5 (8.3); CSE-et = 34.2 (9.0); SBMP = 30.4 (11.0); EX = 23.3 (8.2). CSE-et and SBU-et presented the highest bond strength values, followed by SBMP, CSE, and SBU which did not differ significantly from each other. EX showed the statistically significantly lowest bond strength values. SEM images of interfaces from etched samples showed long adhesive-resin tags penetrating into demineralized enamel. Preliminary etching of enamel significantly increased bond strength for the new one-step multimode adhesive SBU and two-step self-etching adhesive CSE.

Adhesive performance of a multi-mode adhesive system: 1-year in vitro study.

PubMed

Marchesi, Giulio; Frassetto, Andrea; Mazzoni, Annalisa; Apolonio, Fabianni; Diolosà, Marina; Cadenaro, Milena; Di Lenarda, Roberto; Pashley, David H; Tay, Franklin; Breschi, Lorenzo

2014-05-01

The aim of this study was to investigate the adhesive stability over time of a multi-mode one-step adhesive applied using different bonding techniques on human coronal dentine. The hypotheses tested were that microtensile bond strength (μTBS), interfacial nanoleakage expression and matrix metalloproteinases (MMPs) activation are not affected by the adhesive application mode (following the use of self-etch technique or with the etch-and-rinse technique on dry or wet dentine) or by ageing for 24h, 6 months and 1year in artificial saliva. Human molars were cut to expose middle/deep dentine and assigned to one of the following bonding systems (N=15): (1) Scotchbond Universal (3M ESPE) self-etch mode, (2) Scotchbond Universal etch-and-rinse technique on wet dentine, (3) Scotchbond Universal etch-and-rinse technique on dry dentine, and (4) Prime&Bond NT (Dentsply De Trey) etch-and-rinse technique on wet dentine (control). Specimens were processed for μTBS test in accordance with the non-trimming technique and stressed to failure after 24h, 6 months or 1 year. Additional specimens were processed and examined to assay interfacial nanoleakage and MMP expression. At baseline, no differences between groups were found. After 1 year of storage, Scotchbond Universal applied in the self-etch mode and Prime&Bond NT showed higher μTBS compared to the other groups. The lowest nanoleakage expression was found for Scotchbond Universal applied in the self-etch mode, both at baseline and after storage. MMPs activation was found after application of each tested adhesive. The results of this study support the use of the self-etch approach for bonding the tested multi-mode adhesive system to dentine due to improved stability over time. Improved bonding effectiveness of the tested universal adhesive system on dentine may be obtained if the adhesive is applied with the self-etch approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

A new universal simplified adhesive: 6-month clinical evaluation.

PubMed

Mena-Serrano, Alexandra; Kose, Carlos; De Paula, Eloisa Andrade; Tay, Lidia Yileng; Reis, Alessandra; Loguercio, Alessandro D; Perdigão, Jorge

2013-02-01

Multimode adhesives, which can be used as etch-and-rinse or as self-etch adhesives, have been recently introduced without clinical data to back their use. To evaluate the 6-month clinical performance of Scotchbond Universal Adhesive (SU; 3M ESPE, St. Paul, MN, USA) in noncarious cervical lesions (NCCLs) using two evaluation criteria. Thirty-nine patients participated in this study. Two hundred restorations were assigned to four groups: SU-TEm: etch-and-rinse + moist dentin; SU-TEd: etch-and-rinse + dry dentin; SU-SEet: selective enamel etching; and SU-SE: self-etch. The composite resin Filtek Supreme Ultra (3M ESPE) was placed incrementally. The restorations were evaluated at baseline and after 6 months using both the World Dental Federation (FDI) and the United States Public Health Service (USPHS) criteria. Statistical analyses were performed with Friedman repeated measures analysis of variance by rank and McNemar test for significance in each pair (α = 0.05). Only four restorations (SU-SE: 3 and SU-TEm: 1) were lost after 6 months (p > 0.05 for either criteria). Marginal discoloration occurred in one restoration in the SU-SE group (p > 0.05 for either criteria). Only 2/200 restorations were scored as bravo for marginal adaptation using the USPHS criteria (one for SU-SE and one for SU-SEet, p > 0.05). However, when using the FDI criteria, the percentage of bravo scores for marginal adaptation at 6 months were 32%, 36%, 42%, and 46% for groups SU-TEm, SU-TEd, SU-SEet, and SU-SE, respectively (p > 0.05). The clinical behavior of the multimode adhesive does not depend on the bonding strategy at 6 months. The FDI evaluation criteria are more sensitive than the USPHS criteria. At 6 months, the clinical behavior of the new multimode adhesive Scotchbond Universal was found to be reliable when used in noncarious cervical lesions and may not depend on the bonding strategy employed. © 2012 Wiley Periodicals, Inc.

Acute Pain Service and multimodal therapy for postsurgical pain control: evaluation of protocol efficacy.

PubMed

Moizo, E; Berti, M; Marchetti, C; Deni, F; Albertin, A; Muzzolon, F; Antonino, A

2004-11-01

The institution of a postoperative Acute Pain Control Service is mandatory to improve the control of pain induced by surgical injury. Treatment of postoperative pain may be achieved using a combination of analgesic agents and techniques, reducing the incidence of side effects owing to the lower doses of the individual drugs. In 1997 we established an Acute Pain Service (APS) at the San Raffaele Hospital in Milan. The aim of this study was to assess the efficacy and safety of our APS both in terms of treatment protocols and organisational issues. In this prospective observational study we included 592 patients undergoing abdominal, gynecological, or orthopedic surgery with severe expected pain. According to general guidelines on pain treatment, the patients were assigned to different treatment protocols based on the kind of operation. All protocols were based on the multimodal therapy, with the association of nonsteroidal anti-inflammatory drugs (NSAIDS), opioids and regional anesthesia techniques. During the first 48 h of the postoperative period we recorded vital signs, level of pain and occurrence of any side effect. Our analgesic protocols proved to be effective and safe (low incidence of side effects) for every surgery. The incidence of postoperative nausea and vomiting was higher in patients receiving patient-controlled morphine than that with continuous epidural or nerve block. After lower abdominal surgery, pain at movement at 24 h was significantly lower in the epidural group than in the Patient Control Analgesia group. Nausea and vomiting, numbness and paresthesias at the lower limbs were higher in gynecological patients. A larger percentage of orthopedic patients in the epidural group reported numbness and paresthesias at the lower limbs in comparison with patients receiving continuous peripheral nerve block. In agreement with previous literature, this study confirmed that a multimodal approach to pain treatment provides an adequate control of postoperative pain, minimizing side effects.

[Impact of a Multimodal Intervention on the Psychological Profile of Schizophrenic and Bipolar I Patients: A Study of PRISMA Program].

PubMed

Díaz-Zuluaga, Ana María; Vargas, Cristian; Duica, Kelly; Richard, Shanel; Palacio, Juan David; Agudelo Berruecos, Yuli; Ospina, Sigifredo; López-Jaramillo, Carlos

Bipolar Disorder (BD) and schizophrenia are included in the group of severe mental illness and are main causes of disability and morbidity in the local population due to the bio-psycho-social implications in patients. In the last 20 years or so, adjunctive psychological interventions been studied with the purpose of decreasing recurrences, stabilising the course of the disease, and improving the functionality in these patients. To analyse the psychological effect of a multimodal intervention (MI) vs a traditional intervention (TI) program in BD I and schizophrenic patients. A prospective, longitudinal, therapeutic-comparative study was conducted with 302 patients (104 schizophrenic and 198 bipolar patients) who were randomly assigned to the MI or TI groups of a multimodal intervention program PRISMA. The MI group received care from psychiatry, general medicine, neuropsychology, family therapy, and occupational therapy. The TI group received care from psychiatry and general medicine. The Hamilton and Young scales, and the Scales for the Assessment of Negative Symptoms (SANS) and Postive Symptoms (SAPS) were used on bipolar and schizophrenic patients, respectively. The scales AQ-12, TEMPS-A, FAST, Zuckerman sensation seeking scale, BIS-11, SAI-E and EEAG were applied to measure the psychological variables. The scales were performed before and after the interventions. The psychotherapy used in this study was cognitive behavioural therapy. There were statistically significant differences in socio-demographic and clinical variables in the schizophrenia and bipolar disorder group. There were no statistically significant differences in the psychological scales after conducting a multivariate analysis between the intervention groups and for both times (initial and final). This study did not show any changes in variables of psychological functioning variables between bipolar and schizophrenic groups, who were subjected to TI vs MI (who received cognitive behavioural therapy). Further studies are needed with other psychological interventions or other psychometric scales. Copyright © 2016 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Substantial improvement of primary cardiovascular prevention by a systematic score-based multimodal approach: A randomized trial: The PreFord-Study.

PubMed

Gysan, Detlef Bernd; Millentrup, Stefanie; Albus, Christian; Bjarnason-Wehrens, Birna; Latsch, Joachim; Gohlke, Helmut; Herold, Gerd; Wegscheider, Karl; Heming, Christian; Seyfarth, Melchior; Predel, Hans-Georg

2017-09-01

Trial design Prospective randomized multicentre interventional study. Methods Individual cardiovascular risk assessment in Ford Company, Germany employees ( n = 4.196), using the European Society of Cardiology-Systematic Coronary Risk Evaluation (ESC-SCORE) for classification into three risk groups. Subjects assigned to ESC high-risk group (ESC-SCORE ≥ 5%), without a history of cardiovascular disease were eligible for randomization to a multimodal 15-week intervention programme (INT) or to usual care and followed up for 36 months. Objectives Evaluation of the long-term effects of a risk-adjusted multimodal intervention in high-risk subjects. Primary endpoint: reduction of ESC-SCORE in INT versus usual care. Secondary endpoints: composite of fatal and non-fatal cardiovascular events and time to first cardiovascular event. intention-to-treat and per-protocol analysis. Results Four hundred and forty-seven subjects were randomized to INT ( n = 224) or to usual care ( n = 223). After 36 months ESC-SCORE development favouring INT was observed (INT: 8.70% to 10.03% vs. usual care: 8.49% to 12.09%; p = 0.005; net difference: 18.50%). Moreover, a significant reduction in the composite cardiovascular events was observed: (INT: n = 11 vs. usual care: n = 27). Hazard ratio of intervention versus control was 0.51 (95% confidence interval 0.25-1.03; p = 0.062) in the intention-to-treat analysis and 0.41 (95% confidence interval 0.18-0.90; p = 0.026) in the per-protocol analysis, respectively. No intervention-related adverse events or side-effects were observed. Conclusions Our results demonstrate the efficiency of identifying cardiovascular high-risk subjects by the ESC-SCORE in order to enrol them to a risk adjusted primary prevention programme. This strategy resulted in a significant improvement of ESC-SCORE, as well as a reduction in predefined cardiovascular endpoints in the INT within 36 months. (ISRCTN 23536103.).

Static assignment of complex stochastic tasks using stochastic majorization

NASA Technical Reports Server (NTRS)

Nicol, David; Simha, Rahul; Towsley, Don

1992-01-01

We consider the problem of statically assigning many tasks to a (smaller) system of homogeneous processors, where a task's structure is modeled as a branching process, and all tasks are assumed to have identical behavior. We show how the theory of majorization can be used to obtain a partial order among possible task assignments. Our results show that if the vector of numbers of tasks assigned to each processor under one mapping is majorized by that of another mapping, then the former mapping is better than the latter with respect to a large number of objective functions. In particular, we show how measurements of finishing time, resource utilization, and reliability are all captured by the theory. We also show how the theory may be applied to the problem of partitioning a pool of processors for distribution among parallelizable tasks.

Robust detection of heartbeats using association models from blood pressure and EEG signals.

PubMed

Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol

2016-01-15

The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data association method of supplementing ECG with a variety of physiological signals and accounting for the patient-specific lag between different pulsatile signals and ECG. Multimodal signal detectors and data-fusion approaches such as those proposed in this article can reduce false alarms and improve patient monitoring.

Skill training in multimodal virtual environments.

PubMed

Gopher, Daniel

2012-01-01

Multimodal, immersive, virtual reality (VR) techniques open new perspectives for perceptual-motor skill trainers. They also introduce new risks and dangers. This paper describes the benefits and pitfalls of multimodal training and the cognitive building blocks of a multimodal, VR training simulators.

Internet-Based Assessment of Oncology Health Care Professional Learning Style and Optimization of Materials for Web-Based Learning: Controlled Trial With Concealed Allocation.

PubMed

Micheel, Christine M; Anderson, Ingrid A; Lee, Patricia; Chen, Sheau-Chiann; Justiss, Katy; Giuse, Nunzia B; Ye, Fei; Kusnoor, Sheila V; Levy, Mia A

2017-07-25

Precision medicine has resulted in increasing complexity in the treatment of cancer. Web-based educational materials can help address the needs of oncology health care professionals seeking to understand up-to-date treatment strategies. This study aimed to assess learning styles of oncology health care professionals and to determine whether learning style-tailored educational materials lead to enhanced learning. In all, 21,465 oncology health care professionals were invited by email to participate in the fully automated, parallel group study. Enrollment and follow-up occurred between July 13 and September 7, 2015. Self-enrolled participants took a learning style survey and were assigned to the intervention or control arm using concealed alternating allocation. Participants in the intervention group viewed educational materials consistent with their preferences for learning (reading, listening, and/or watching); participants in the control group viewed educational materials typical of the My Cancer Genome website. Educational materials covered the topic of treatment of metastatic estrogen receptor-positive (ER+) breast cancer using cyclin-dependent kinases 4/6 (CDK4/6) inhibitors. Participant knowledge was assessed immediately before (pretest), immediately after (posttest), and 2 weeks after (follow-up test) review of the educational materials. Study statisticians were blinded to group assignment. A total of 751 participants enrolled in the study. Of these, 367 (48.9%) were allocated to the intervention arm and 384 (51.1%) were allocated to the control arm. Of those allocated to the intervention arm, 256 (69.8%) completed all assessments. Of those allocated to the control arm, 296 (77.1%) completed all assessments. An additional 12 participants were deemed ineligible and one withdrew. Of the 552 participants, 438 (79.3%) self-identified as multimodal learners. The intervention arm showed greater improvement in posttest score compared to the control group (0.4 points or 4.0% more improvement on average; P=.004) and a higher follow-up test score than the control group (0.3 points or 3.3% more improvement on average; P=.02). Although the study demonstrated more learning with learning style-tailored educational materials, the magnitude of increased learning and the largely multimodal learning styles preferred by the study participants lead us to conclude that future content-creation efforts should focus on multimodal educational materials rather than learning style-tailored content. ©Christine M Micheel, Ingrid A Anderson, Patricia Lee, Sheau-Chiann Chen, Katy Justiss, Nunzia B Giuse, Fei Ye, Sheila V Kusnoor, Mia A Levy. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.07.2017.

Problems on Divisibility of Binomial Coefficients

ERIC Educational Resources Information Center

Osler, Thomas J.; Smoak, James

2004-01-01

Twelve unusual problems involving divisibility of the binomial coefficients are represented in this article. The problems are listed in "The Problems" section. All twelve problems have short solutions which are listed in "The Solutions" section. These problems could be assigned to students in any course in which the binomial theorem and Pascal's…

The Study on the Optimization of Container Multimodal Transport Business Process in Shandong

NASA Astrophysics Data System (ADS)

Wang, Fengmei; Gong, Xiaoyi; Ni, Yingying; Zhan, Jun; Che, Huiping

2018-06-01

Shandong is a coastal city with good location advantages. As a hub port for international trade goods and a port of transhipment, shandong's demand for multimodal transport is more urgent. By selecting the suitable non-water port and the multimodal transport carrier to improve the efficiency of multimodal transport, the purpose of saving the time of logistics is achieved, thus reducing the logistics cost.It branch out through Shandongt, and it can reach the central region of China, can reach the Western remote area ,too. This paper puts forward the optimization scheme of the business process of container multimodal transport. The optimization of freight forwarding business process is analyzed. The multimodal transport model in Shandong was designed. Finally, the optimal approach of multimodal transport in Shandong is put forward.

Construction of Multimodal Transport Information Platform

NASA Astrophysics Data System (ADS)

Wang, Ya; Cheng, Yu; Zhao, Zhi

2018-06-01

With the rapid development of economy, the volume of transportation in China is increasing, the opening process of the market is accelerating, the scale of enterprises is expanding, the service quality is being improved, and the container multimodal transport is developing continuously.The hardware infrastructure of container multimodal transport is improved obviously, but the network platform construction of multimodal transport is still insufficient.Taking Shandong region of China as an example, the present situation of container multimodal transport in Shandong area can no longer meet the requirement of rapid development of container, and the construction of network platform needs to be solved urgently. Therefore, this paper will briefly describe the conception of construction of multimodal transport network platform in Shandong area.In order to achieve the rapid development of multimodal transport.

An agglomerative hierarchical clustering approach to visualisation in Bayesian clustering problems

PubMed Central

Dawson, Kevin J.; Belkhir, Khalid

2009-01-01

Clustering problems (including the clustering of individuals into outcrossing populations, hybrid generations, full-sib families and selfing lines) have recently received much attention in population genetics. In these clustering problems, the parameter of interest is a partition of the set of sampled individuals, - the sample partition. In a fully Bayesian approach to clustering problems of this type, our knowledge about the sample partition is represented by a probability distribution on the space of possible sample partitions. Since the number of possible partitions grows very rapidly with the sample size, we can not visualise this probability distribution in its entirety, unless the sample is very small. As a solution to this visualisation problem, we recommend using an agglomerative hierarchical clustering algorithm, which we call the exact linkage algorithm. This algorithm is a special case of the maximin clustering algorithm that we introduced previously. The exact linkage algorithm is now implemented in our software package Partition View. The exact linkage algorithm takes the posterior co-assignment probabilities as input, and yields as output a rooted binary tree, - or more generally, a forest of such trees. Each node of this forest defines a set of individuals, and the node height is the posterior co-assignment probability of this set. This provides a useful visual representation of the uncertainty associated with the assignment of individuals to categories. It is also a useful starting point for a more detailed exploration of the posterior distribution in terms of the co-assignment probabilities. PMID:19337306

Prefrontal Neurons Encode a Solution to the Credit-Assignment Problem

PubMed Central

Perge, János A.; Eskandar, Emad N.

2017-01-01

To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects. SIGNIFICANCE STATEMENT Credit assignment is the process by which we infer the causes of our successes and failures. We found that neuronal activity in the dorsolateral prefrontal cortex conveyed the necessary information for performing credit assignment. Importantly, while there are various potential mechanisms to retain a “trace” of the causal events over time, we observed that spiking activity was sufficiently stable to act as the link between causes and effects, in contrast to prior reports that suggested spiking representations were unstable over time. In addition, we observed that this stability varied as a function of learning, such that the neural code was more reliable over time during early learning, when it was most needed. PMID:28634307

Distributed resource allocation under communication constraints

NASA Astrophysics Data System (ADS)

Dodin, Pierre; Nimier, Vincent

2001-03-01

This paper deals with a study of the multi-sensor management problem for multi-target tracking. The collaboration between many sensors observing the same target means that they are able to fuse their data during the information process. Then one must take into account this possibility to compute the optimal association sensors-target at each step of time. In order to solve this problem for real large scale system, one must both consider the information aspect and the control aspect of the problem. To unify these problems, one possibility is to use a decentralized filtering algorithm locally driven by an assignment algorithm. The decentralized filtering algorithm we use in our model is the filtering algorithm of Grime, which relaxes the usual full-connected hypothesis. By full-connected, one means that the information in a full-connected system is totally distributed everywhere at the same moment, which is unacceptable for a real large scale system. We modelize the distributed assignment decision with the help of a greedy algorithm. Each sensor performs a global optimization, in order to estimate other information sets. A consequence of the relaxation of the full- connected hypothesis is that the sensors' information set are not the same at each step of time, producing an information dis- symmetry in the system. The assignment algorithm uses a local knowledge of this dis-symmetry. By testing the reactions and the coherence of the local assignment decisions of our system, against maneuvering targets, we show that it is still possible to manage with decentralized assignment control even though the system is not full-connected.

Multisystemic Therapy and Functional Family Therapy Compared on their Effectiveness Using the Propensity Score Method.

PubMed

Eeren, Hester V; Goossens, Lucas M A; Scholte, Ron H J; Busschbach, Jan J V; van der Rijken, Rachel E A

2018-01-09

Multisystemic Therapy (MST) and Functional Family Therapy (FFT) have overlapping target populations and treatment goals. In this study, these interventions were compared on their effectiveness using a quasi-experimental design. Between October, 2009 and June, 2014, outcome data were collected from 697 adolescents (mean age 15.3 (SD 1.48), 61.9% male) assigned to either MST or FFT (422 MST; 275 FFT). Data were gathered during Routine Outcome Monitoring. The primary outcome was externalizing problem behavior (Child Behavior Checklist and Youth Self Report). Secondary outcomes were the proportion of adolescents living at home, engaged in school or work, and who lacked police contact during treatment. Because of the non-random assignment, a propensity score method was used to control for observed pre-treatment differences. Because the risk-need-responsivity (RNR) model guided treatment assignment, effectiveness was also estimated in youth with and without a court order as an indicator of their risk level. Looking at the whole sample, no difference in effect was found with regard to externalizing problems. For adolescents without a court order, effects on externalizing problems were larger after MST. Because many more adolescents with a court order were assigned to MST compared to FFT, the propensity score method could not balance the treatment groups in this subsample. In conclusion, few differences between MST and FFT were found. In line with the RNR model, higher risk adolescents were assigned to the more intensive treatment, namely MST. In the group with lower risk adolescents, this more intensive treatment was more effective in reducing externalizing problems.

"Filming in Progress": New Spaces for Multimodal Designing

ERIC Educational Resources Information Center

Mills, Kathy A.

2010-01-01

Global trends call for new research to investigate multimodal designing mediated by new technologies and the implications for classroom spaces. This article addresses the relationship between new technologies, students' multimodal designing, and the social production of classroom spaces. Multimodal semiotics and sociological principles are applied…

Maternal education preferences moderate the effects of mandatory employment and education programs on child positive and problem behaviors.

PubMed

Gassman-Pines, Anna; Godfrey, Erin B; Yoshikawa, Hirokazu

2013-01-01

Grounded in person-environment fit theory, this study examined whether low-income mothers' preferences for education moderated the effects of employment- and education-focused welfare programs on children's positive and problem behaviors. The sample included 1,365 families with children between ages 3 and 5 years at study entry. Results 5 years after random assignment, when children were ages 8-10 years, indicated that mothers' education preferences did moderate program impacts on teacher-reported child behavior problems and positive behavior. Children whose mothers were assigned to the education program were rated by teachers to have less externalizing behavior and more positive behavior than children whose mothers were assigned to the employment program but only when mothers had strong preferences for education. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Mining Stable Roles in RBAC

NASA Astrophysics Data System (ADS)

Colantonio, Alessandro; di Pietro, Roberto; Ocello, Alberto; Verde, Nino Vincenzo

In this paper we address the problem of generating a candidate role-set for an RBAC configuration that enjoys the following two key features: it minimizes the administration cost; and, it is a stable candidate role-set. To achieve these goals, we implement a three steps methodology: first, we associate a weight to roles; second, we identify and remove the user-permission assignments that cannot belong to a role that have a weight exceeding a given threshold; third, we restrict the problem of finding a candidate role-set for the given system configuration using only the user-permission assignments that have not been removed in the second step—that is, user-permission assignments that belong to roles with a weight exceeding the given threshold. We formally show—proof of our results are rooted in graph theory—that this methodology achieves the intended goals. Finally, we discuss practical applications of our approach to the role mining problem.

3D multimodal MRI brain glioma tumor and edema segmentation: a graph cut distribution matching approach.

PubMed

Njeh, Ines; Sallemi, Lamia; Ayed, Ismail Ben; Chtourou, Khalil; Lehericy, Stephane; Galanaud, Damien; Hamida, Ahmed Ben

2015-03-01

This study investigates a fast distribution-matching, data-driven algorithm for 3D multimodal MRI brain glioma tumor and edema segmentation in different modalities. We learn non-parametric model distributions which characterize the normal regions in the current data. Then, we state our segmentation problems as the optimization of several cost functions of the same form, each containing two terms: (i) a distribution matching prior, which evaluates a global similarity between distributions, and (ii) a smoothness prior to avoid the occurrence of small, isolated regions in the solution. Obtained following recent bound-relaxation results, the optima of the cost functions yield the complement of the tumor region or edema region in nearly real-time. Based on global rather than pixel wise information, the proposed algorithm does not require an external learning from a large, manually-segmented training set, as is the case of the existing methods. Therefore, the ensuing results are independent of the choice of a training set. Quantitative evaluations over the publicly available training and testing data set from the MICCAI multimodal brain tumor segmentation challenge (BraTS 2012) demonstrated that our algorithm yields a highly competitive performance for complete edema and tumor segmentation, among nine existing competing methods, with an interesting computing execution time (less than 0.5s per image). Copyright © 2014 Elsevier Ltd. All rights reserved.

Emerging technology in fiber optic sensors

NASA Astrophysics Data System (ADS)

Dyott, Richard B.

1991-03-01

Some recent innovations in interferoinetric fiber optic sensors include special fibers new components and sensor systems. Many of the concepts have precedents in microwaves. 1. GENERAL PRINCIPLES The application of optical fibers to sensors is diffuse compared with their application to optical communications which is essentially focused on the single problem of how to get information from A to B. A fiber sensor is viable when it can do something not possible with better than more cheaply than any existing method. The probability of the emergence of a new sensor depends on the length of time that a need for the sensor and the possibility of meeting that need have co-existed regardless of whether the need or the possibility has appeared first. 2. TYPES OF SENSOR Fiber sensors can be divided into: a) Multimode fiber sensors which depend on amplitude effects b) Single mode (single path) fiber sensors which depend on phase effects. Since multimode fiber has existed for many decades the emergence of a new multimode sensor depends mostly on the discovery of a new need for such a sensor. On the other hand single mode/single path (i. e. polarization maintaining) fiber is relatively new and so is still being applied to existing needs. This is particularly so of recent innovations in fibers and components. SPIE Vol. 1396 Applications of Optical Engineering Proceedings of OE/Midwest ''90 / 709

An automated system for reduction of the firm's employees under maximal overall efficiency

NASA Astrophysics Data System (ADS)

Yonchev, Yoncho; Nikolov, Simeon; Baeva, Silvia

2012-11-01

Achieving maximal overall efficiency is a priority in all companies. This problem is formulated as a knap-sack problem and afterwards as a linear assignment problem. An automated system is created for solving of this problem.

Adaptive multimodal interaction in mobile augmented reality: A conceptual framework

NASA Astrophysics Data System (ADS)

Abidin, Rimaniza Zainal; Arshad, Haslina; Shukri, Saidatul A'isyah Ahmad

2017-10-01

Recently, Augmented Reality (AR) is an emerging technology in many mobile applications. Mobile AR was defined as a medium for displaying information merged with the real world environment mapped with augmented reality surrounding in a single view. There are four main types of mobile augmented reality interfaces and one of them are multimodal interfaces. Multimodal interface processes two or more combined user input modes (such as speech, pen, touch, manual gesture, gaze, and head and body movements) in a coordinated manner with multimedia system output. In multimodal interface, many frameworks have been proposed to guide the designer to develop a multimodal applications including in augmented reality environment but there has been little work reviewing the framework of adaptive multimodal interface in mobile augmented reality. The main goal of this study is to propose a conceptual framework to illustrate the adaptive multimodal interface in mobile augmented reality. We reviewed several frameworks that have been proposed in the field of multimodal interfaces, adaptive interface and augmented reality. We analyzed the components in the previous frameworks and measure which can be applied in mobile devices. Our framework can be used as a guide for designers and developer to develop a mobile AR application with an adaptive multimodal interfaces.

Analyzing a multimodal biometric system using real and virtual users

NASA Astrophysics Data System (ADS)

Scheidat, Tobias; Vielhauer, Claus

2007-02-01

Three main topics of recent research on multimodal biometric systems are addressed in this article: The lack of sufficiently large multimodal test data sets, the influence of cultural aspects and data protection issues of multimodal biometric data. In this contribution, different possibilities are presented to extend multimodal databases by generating so-called virtual users, which are created by combining single biometric modality data of different users. Comparative tests on databases containing real and virtual users based on a multimodal system using handwriting and speech are presented, to study to which degree the use of virtual multimodal databases allows conclusions with respect to recognition accuracy in comparison to real multimodal data. All tests have been carried out on databases created from donations from three different nationality groups. This allows to review the experimental results both in general and in context of cultural origin. The results show that in most cases the usage of virtual persons leads to lower accuracy than the usage of real users in terms of the measurement applied: the Equal Error Rate. Finally, this article will address the general question how the concept of virtual users may influence the data protection requirements for multimodal evaluation databases in the future.

Radiolabeled Nanoparticles for Multimodality Tumor Imaging

PubMed Central

Xing, Yan; Zhao, Jinhua; Conti, Peter S.; Chen, Kai

2014-01-01

Each imaging modality has its own unique strengths. Multimodality imaging, taking advantages of strengths from two or more imaging modalities, can provide overall structural, functional, and molecular information, offering the prospect of improved diagnostic and therapeutic monitoring abilities. The devices of molecular imaging with multimodality and multifunction are of great value for cancer diagnosis and treatment, and greatly accelerate the development of radionuclide-based multimodal molecular imaging. Radiolabeled nanoparticles bearing intrinsic properties have gained great interest in multimodality tumor imaging over the past decade. Significant breakthrough has been made toward the development of various radiolabeled nanoparticles, which can be used as novel cancer diagnostic tools in multimodality imaging systems. It is expected that quantitative multimodality imaging with multifunctional radiolabeled nanoparticles will afford accurate and precise assessment of biological signatures in cancer in a real-time manner and thus, pave the path towards personalized cancer medicine. This review addresses advantages and challenges in developing multimodality imaging probes by using different types of nanoparticles, and summarizes the recent advances in the applications of radiolabeled nanoparticles for multimodal imaging of tumor. The key issues involved in the translation of radiolabeled nanoparticles to the clinic are also discussed. PMID:24505237

"Ask Ernö": a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra.

PubMed

Castillo, Andrés M; Bernal, Andrés; Dieden, Reiner; Patiny, Luc; Wist, Julien

2016-01-01

We present "Ask Ernö", a self-learning system for the automatic analysis of NMR spectra, consisting of integrated chemical shift assignment and prediction tools. The output of the automatic assignment component initializes and improves a database of assigned protons that is used by the chemical shift predictor. In turn, the predictions provided by the latter facilitate improvement of the assignment process. Iteration on these steps allows Ask Ernö to improve its ability to assign and predict spectra without any prior knowledge or assistance from human experts. This concept was tested by training such a system with a dataset of 2341 molecules and their (1)H-NMR spectra, and evaluating the accuracy of chemical shift predictions on a test set of 298 partially assigned molecules (2007 assigned protons). After 10 iterations, Ask Ernö was able to decrease its prediction error by 17 %, reaching an average error of 0.265 ppm. Over 60 % of the test chemical shifts were predicted within 0.2 ppm, while only 5 % still presented a prediction error of more than 1 ppm. Ask Ernö introduces an innovative approach to automatic NMR analysis that constantly learns and improves when provided with new data. Furthermore, it completely avoids the need for manually assigned spectra. This system has the potential to be turned into a fully autonomous tool able to compete with the best alternatives currently available.Graphical abstractSelf-learning loop. Any progress in the prediction (forward problem) will improve the assignment ability (reverse problem) and vice versa.

Multimodal Hierarchical Dirichlet Process-Based Active Perception by a Robot

PubMed Central

Taniguchi, Tadahiro; Yoshino, Ryo; Takano, Toshiaki

2018-01-01

In this paper, we propose an active perception method for recognizing object categories based on the multimodal hierarchical Dirichlet process (MHDP). The MHDP enables a robot to form object categories using multimodal information, e.g., visual, auditory, and haptic information, which can be observed by performing actions on an object. However, performing many actions on a target object requires a long time. In a real-time scenario, i.e., when the time is limited, the robot has to determine the set of actions that is most effective for recognizing a target object. We propose an active perception for MHDP method that uses the information gain (IG) maximization criterion and lazy greedy algorithm. We show that the IG maximization criterion is optimal in the sense that the criterion is equivalent to a minimization of the expected Kullback–Leibler divergence between a final recognition state and the recognition state after the next set of actions. However, a straightforward calculation of IG is practically impossible. Therefore, we derive a Monte Carlo approximation method for IG by making use of a property of the MHDP. We also show that the IG has submodular and non-decreasing properties as a set function because of the structure of the graphical model of the MHDP. Therefore, the IG maximization problem is reduced to a submodular maximization problem. This means that greedy and lazy greedy algorithms are effective and have a theoretical justification for their performance. We conducted an experiment using an upper-torso humanoid robot and a second one using synthetic data. The experimental results show that the method enables the robot to select a set of actions that allow it to recognize target objects quickly and accurately. The numerical experiment using the synthetic data shows that the proposed method can work appropriately even when the number of actions is large and a set of target objects involves objects categorized into multiple classes. The results support our theoretical outcomes. PMID:29872389

Multimodal Hierarchical Dirichlet Process-Based Active Perception by a Robot.

PubMed

Taniguchi, Tadahiro; Yoshino, Ryo; Takano, Toshiaki

2018-01-01

In this paper, we propose an active perception method for recognizing object categories based on the multimodal hierarchical Dirichlet process (MHDP). The MHDP enables a robot to form object categories using multimodal information, e.g., visual, auditory, and haptic information, which can be observed by performing actions on an object. However, performing many actions on a target object requires a long time. In a real-time scenario, i.e., when the time is limited, the robot has to determine the set of actions that is most effective for recognizing a target object. We propose an active perception for MHDP method that uses the information gain (IG) maximization criterion and lazy greedy algorithm. We show that the IG maximization criterion is optimal in the sense that the criterion is equivalent to a minimization of the expected Kullback-Leibler divergence between a final recognition state and the recognition state after the next set of actions. However, a straightforward calculation of IG is practically impossible. Therefore, we derive a Monte Carlo approximation method for IG by making use of a property of the MHDP. We also show that the IG has submodular and non-decreasing properties as a set function because of the structure of the graphical model of the MHDP. Therefore, the IG maximization problem is reduced to a submodular maximization problem. This means that greedy and lazy greedy algorithms are effective and have a theoretical justification for their performance. We conducted an experiment using an upper-torso humanoid robot and a second one using synthetic data. The experimental results show that the method enables the robot to select a set of actions that allow it to recognize target objects quickly and accurately. The numerical experiment using the synthetic data shows that the proposed method can work appropriately even when the number of actions is large and a set of target objects involves objects categorized into multiple classes. The results support our theoretical outcomes.

Multimodal Optimization by Covariance Matrix Self-Adaptation Evolution Strategy with Repelling Subpopulations.

PubMed

Ahrari, Ali; Deb, Kalyanmoy; Preuss, Mike

2017-01-01

During the recent decades, many niching methods have been proposed and empirically verified on some available test problems. They often rely on some particular assumptions associated with the distribution, shape, and size of the basins, which can seldom be made in practical optimization problems. This study utilizes several existing concepts and techniques, such as taboo points, normalized Mahalanobis distance, and the Ursem's hill-valley function in order to develop a new tool for multimodal optimization, which does not make any of these assumptions. In the proposed method, several subpopulations explore the search space in parallel. Offspring of a subpopulation are forced to maintain a sufficient distance to the center of fitter subpopulations and the previously identified basins, which are marked as taboo points. The taboo points repel the subpopulation to prevent convergence to the same basin. A strategy to update the repelling power of the taboo points is proposed to address the challenge of basins of dissimilar size. The local shape of a basin is also approximated by the distribution of the subpopulation members converging to that basin. The proposed niching strategy is incorporated into the covariance matrix self-adaptation evolution strategy (CMSA-ES), a potent global optimization method. The resultant method, called the covariance matrix self-adaptation with repelling subpopulations (RS-CMSA), is assessed and compared to several state-of-the-art niching methods on a standard test suite for multimodal optimization. An organized procedure for parameter setting is followed which assumes a rough estimation of the desired/expected number of minima available. Performance sensitivity to the accuracy of this estimation is also studied by introducing the concept of robust mean peak ratio. Based on the numerical results using the available and the introduced performance measures, RS-CMSA emerges as the most successful method when robustness and efficiency are considered at the same time.

Locating the Semiotic Power of Multimodality

ERIC Educational Resources Information Center

Hull, Glynda A.; Nelson, Mark Evan

2005-01-01

This article reports research that attempts to characterize what is powerful about digital multimodal texts. Building from recent theoretical work on understanding the workings and implications of multimodal communication, the authors call for a continuing empirical investigation into the roles that digital multimodal texts play in real-world…

A multimodal parallel architecture: A cognitive framework for multimodal interactions.

PubMed

Cohn, Neil

2016-01-01

Human communication is naturally multimodal, and substantial focus has examined the semantic correspondences in speech-gesture and text-image relationships. However, visual narratives, like those in comics, provide an interesting challenge to multimodal communication because the words and/or images can guide the overall meaning, and both modalities can appear in complicated "grammatical" sequences: sentences use a syntactic structure and sequential images use a narrative structure. These dual structures create complexity beyond those typically addressed by theories of multimodality where only a single form uses combinatorial structure, and also poses challenges for models of the linguistic system that focus on single modalities. This paper outlines a broad theoretical framework for multimodal interactions by expanding on Jackendoff's (2002) parallel architecture for language. Multimodal interactions are characterized in terms of their component cognitive structures: whether a particular modality (verbal, bodily, visual) is present, whether it uses a grammatical structure (syntax, narrative), and whether it "dominates" the semantics of the overall expression. Altogether, this approach integrates multimodal interactions into an existing framework of language and cognition, and characterizes interactions between varying complexity in the verbal, bodily, and graphic domains. The resulting theoretical model presents an expanded consideration of the boundaries of the "linguistic" system and its involvement in multimodal interactions, with a framework that can benefit research on corpus analyses, experimentation, and the educational benefits of multimodality. Copyright © 2015.

The solution of target assignment problem in command and control decision-making behaviour simulation

NASA Astrophysics Data System (ADS)

Li, Ni; Huai, Wenqing; Wang, Shaodan

2017-08-01

C2 (command and control) has been understood to be a critical military component to meet an increasing demand for rapid information gathering and real-time decision-making in a dynamically changing battlefield environment. In this article, to improve a C2 behaviour model's reusability and interoperability, a behaviour modelling framework was proposed to specify a C2 model's internal modules and a set of interoperability interfaces based on the C-BML (coalition battle management language). WTA (weapon target assignment) is a typical C2 autonomous decision-making behaviour modelling problem. Different from most WTA problem descriptions, here sensors were considered to be available resources of detection and the relationship constraints between weapons and sensors were also taken into account, which brought it much closer to actual application. A modified differential evolution (MDE) algorithm was developed to solve this high-dimension optimisation problem and obtained an optimal assignment plan with high efficiency. In case study, we built a simulation system to validate the proposed C2 modelling framework and interoperability interface specification. Also, a new optimisation solution was used to solve the WTA problem efficiently and successfully.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Matching School Resources and Student Needs: Scheduling and Assignment Problems in High Schools Serving At-Risk Youth. Final Report.

ERIC Educational Resources Information Center

Natriello, Gary; And Others

By studying the process by which disadvantaged and low-achieving high school students are assigned to classes and special programs, how and why disadvantaged students are placed in inappropriate programs can be understood. Reasons exist to question the assumption that students are assigned to programs rationally on the basis of information about…

An analysis of sponge genomes.

PubMed

Costantini, Maria

2004-11-24

The genome of sponges has only been investigated so far by Bartmann-Lindholm et al. [Progr. Colloid. Polym. Sci. 107 (1997) 122-126] who reported a multimodal CsCl profile which could be resolved into five peaks for Geodia cydonium. This problem was reinvestigated here on both G. cydonium and Suberites domuncula. It was shown that DNAs from both sponges are characterized by unimodal CsCl profiles, additional peaks being due to contaminating prokaryotic and eukaryotic microorganisms.

An algorithm for solving the perturbed gas dynamic equations

NASA Technical Reports Server (NTRS)

Davis, Sanford

1993-01-01

The present application of a compact, higher-order central-difference approximation to the linearized Euler equations illustrates the multimodal character of these equations by means of computations for acoustic, vortical, and entropy waves. Such dissipationless central-difference methods are shown to propagate waves exhibiting excellent phase and amplitude resolution on the basis of relatively large time-steps; they can be applied to wave problems governed by systems of first-order partial differential equations.

Multimodal Discourse Analysis of the Movie "Argo"

ERIC Educational Resources Information Center

Bo, Xu

2018-01-01

Based on multimodal discourse theory, this paper makes a multimodal discourse analysis of some shots in the movie "Argo" from the perspective of context of culture, context of situation and meaning of image. Results show that this movie constructs multimodal discourse through particular context, language and image, and successfully…

The Work of Comics Collaborations: Considerations of Multimodal Composition for Writing Scholarship and Pedagogy

ERIC Educational Resources Information Center

Scanlon, Molly J.

2015-01-01

Though multimodality is increasingly incorporated into our pedagogies and scholarship, explorations of collaborative multimodal composition are lacking. Existing literature on collaborative writing focuses predominately on texts either composed in singular modes or by a single author, neglecting the ways in which multimodal texts are composed…

How Multimodality Works in Mathematical Activity: Young Children Graphing Motion

ERIC Educational Resources Information Center

Ferrara, Francesca

2014-01-01

This paper aims to contribute to discussions on the multimodal nature of cognition through an elaboration of the ways multimodal aspects of thinking are exploited by learners doing mathematics. Moving beyond the fact "that" multimodality occurs, this paper focuses on "how" it occurs, with particular attention drawn to the…

Designing Multimodal Texts about the Middle Ages

ERIC Educational Resources Information Center

Insulander, Eva; Lindstrand, Fredrik; Selander, Staffan

2017-01-01

Multimedial and multimodal communication arouse interest in many fields of research today. By contrast, little attention is paid to multimodality in relation to designs for learning, especially in relation to representations of knowledge on an aggregated level. By analyzing three multimodal texts about the Middle Ages, including a textbook, a film…

Game theory and traffic assignment.

DOT National Transportation Integrated Search

2013-09-01

Traffic assignment is used to determine the number of users on roadway links in a network. While this problem has : been widely studied in transportation literature, its use of the concept of equilibrium has attracted considerable interest : in the f...

Task Assignment Heuristics for Parallel and Distributed CFD Applications

NASA Technical Reports Server (NTRS)

Lopez-Benitez, Noe; Djomehri, M. Jahed; Biswas, Rupak

2003-01-01

This paper proposes a task graph (TG) model to represent a single discrete step of multi-block overset grid computational fluid dynamics (CFD) applications. The TG model is then used to not only balance the computational workload across the overset grids but also to reduce inter-grid communication costs. We have developed a set of task assignment heuristics based on the constraints inherent in this class of CFD problems. Two basic assignments, the smallest task first (STF) and the largest task first (LTF), are first presented. They are then systematically costs. To predict the performance of the proposed task assignment heuristics, extensive performance evaluations are conducted on a synthetic TG with tasks defined in terms of the number of grid points in predetermined overlapping grids. A TG derived from a realistic problem with eight million grid points is also used as a test case.

Multimodality: a basis for augmentative and alternative communication--psycholinguistic, cognitive, and clinical/educational aspects.

PubMed

Loncke, Filip T; Campbell, Jamie; England, Amanda M; Haley, Tanya

2006-02-15

Message generating is a complex process involving a number of processes, including the selection of modes to use. When expressing a message, human communicators typically use a combination of modes. This phenomenon is often termed multimodality. This article explores the use of models that explain multimodality as an explanatory framework for augmentative and alternative communication (AAC). Multimodality is analysed from a communication, psycholinguistic, and cognitive perspective. Theoretical and applied topics within AAC can be explained or described within the multimodality framework considering iconicity, simultaneous communication, lexical organization, and compatibility of communication modes. Consideration of multimodality is critical to understanding underlying processes in individuals who use AAC and individuals who interact with them.

Mid-infrared multi-mode absorption spectroscopy, MUMAS, using difference frequency generation

NASA Astrophysics Data System (ADS)

Northern, Henry; O'Hagan, Seamus; Hamilton, Michelle L.; Ewart, Paul

2015-03-01

Multi-mode absorption spectroscopy of ammonia and methane at 3.3 μm has been demonstrated using a source of multi-mode mid-infrared radiation based on difference frequency generation. Multi-mode radiation at 1.56 μm from a diode-pumped Er:Yb:glass laser was mixed with a single-mode Nd:YAG laser at 1.06 μm in a periodically poled lithium niobate crystal to produce multi-mode radiation in the region of 3.3 μm. Detection, by direct multi-mode absorption, of NH3 and CH4 is reported for each species individually and also simultaneously in mixtures allowing measurements of partial pressures of each species.

Frequency Assignments for HFDF Receivers in a Search and Rescue Network

DTIC Science & Technology

1990-03-01

SAR problem where whether or not a signal is detected by RS or HFDF at the various stations is described by probabilities. Daskin assumes the...allows the problem to be formulated with a linear objective function (6:52-53). Daskin also developed a heuristic solution algorithm to solve this...en CM in o CM CM < I Q < - -.~- -^ * . . . ■ . ,■ . :ST.-.r . 5 Frequency Assignments for HFDF Receivers in a Search and

Good Student/Bad Student: Situated Identities in the Figured Worlds of School and Creative Multimodal Production

ERIC Educational Resources Information Center

Jocius, Robin

2017-01-01

This study situates young adolescents' multimodal composing practices within two figured worlds--school and creative multimodal production. In a microanalysis of two focal students' multimodal processes and products, I trace how pedagogical, interactional, and semiotic resources both reified and challenged students' developing identities as…

Using Shaun Tan's Work to Foster Multiliteracies in 21st-Century Classrooms

ERIC Educational Resources Information Center

Dallacqua, Ashley K.; Kersten, Sara; Rhoades, Mindi

2015-01-01

This paper explores work in multimodality and design as it relates to 21st century multiliteracies. After outlining the concept of a multiliteracies pedagogy, this paper describes multimodality and multimodal texts. Moving from the theoretical to the practical, this paper primarily explores selected multimodal works of Shaun Tan and the…

Multimodal Hip Hop Productions as Media Literacies

ERIC Educational Resources Information Center

Turner, K. C. Nat

2012-01-01

This study draws on ethnographic data from a year-long multimodal media production (MMP) course and the experience of an African American female adolescent who used the production of multimodal Hip Hop texts to express her creativity and growing socially conscious view of the world. The study demonstrates how students made meaning multimodally and…

Towards an intelligent framework for multimodal affective data analysis.

PubMed

Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

2015-03-01

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Practical multimodal care for cancer cachexia.

PubMed

Maddocks, Matthew; Hopkinson, Jane; Conibear, John; Reeves, Annie; Shaw, Clare; Fearon, Ken C H

2016-12-01

Cancer cachexia is common and reduces function, treatment tolerability and quality of life. Given its multifaceted pathophysiology a multimodal approach to cachexia management is advocated for, but can be difficult to realise in practice. We use a case-based approach to highlight practical approaches to the multimodal management of cachexia for patients across the cancer trajectory. Four cases with lung cancer spanning surgical resection, radical chemoradiotherapy, palliative chemotherapy and no anticancer treatment are presented. We propose multimodal care approaches that incorporate nutritional support, exercise, and anti-inflammatory agents, on a background of personalized oncology care and family-centred education. Collectively, the cases reveal that multimodal care is part of everyone's remit, often focuses on supported self-management, and demands buy-in from the patient and their family. Once operationalized, multimodal care approaches can be tested pragmatically, including alongside emerging pharmacological cachexia treatments. We demonstrate that multimodal care for cancer cachexia can be achieved using simple treatments and without a dedicated team of specialists. The sharing of advice between health professionals can help build collective confidence and expertise, moving towards a position in which every team member feels they can contribute towards multimodal care.

Overcoming an obstacle in expanding a UMLS semantic type extent.

PubMed

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2012-02-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. Copyright © 2011 Elsevier Inc. All rights reserved.

Overcoming an Obstacle in Expanding a UMLS Semantic Type Extent

PubMed Central

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2011-01-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. PMID:21925287

Manipulatives and problem situations as escalators for students' geometric understanding: a semiotic analysis

NASA Astrophysics Data System (ADS)

Daher, Wajeeh M.

2014-04-01

Mathematical learning and teaching are increasingly seen as a multimodal experience involved in cultural and social semiotic registers and means, and as such social-cultural semiotic analysis is expected to shed light on learning and teaching processes occurring in the mathematics classroom. In this research, three social-cultural semiotic frameworks were utilised to analyse elementary school students' learning of a geometric relation: the semiotic bundle, the space of action, production and communication and the theoretical framework of attention, awareness and objectification. Educational mathematical situations are described, in addition to semiotic sets, registers and means emerging in the different mathematical situations and that are relevant to the three social-cultural semiotic frameworks which the current research utilizes. Further, the students, as a consequence of (1) their multimodal experience, (2) their connecting between the different mathematical situations and semiotic registers, and (3) the teacher's questions and tasks, could objectify the geometric relation between the lengths of the triangle's edges.

A Novel Hybrid Firefly Algorithm for Global Optimization.

PubMed

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate.

A Novel Hybrid Firefly Algorithm for Global Optimization

PubMed Central

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

2016-01-01

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate. PMID:27685869

Negotiating Multicollinearity with Spike-and-Slab Priors

PubMed Central

Ročková, Veronika

2014-01-01

In multiple regression under the normal linear model, the presence of multicollinearity is well known to lead to unreliable and unstable maximum likelihood estimates. This can be particularly troublesome for the problem of variable selection where it becomes more difficult to distinguish between subset models. Here we show how adding a spike-and-slab prior mitigates this difficulty by filtering the likelihood surface into a posterior distribution that allocates the relevant likelihood information to each of the subset model modes. For identification of promising high posterior models in this setting, we consider three EM algorithms, the fast closed form EMVS version of Rockova and George (2014) and two new versions designed for variants of the spike-and-slab formulation. For a multimodal posterior under multicollinearity, we compare the regions of convergence of these three algorithms. Deterministic annealing versions of the EMVS algorithm are seen to substantially mitigate this multimodality. A single simple running example is used for illustration throughout. PMID:25419004

From ancient to avant-garde: a review of traditional and modern multimodal approaches to surgical anatomy education.

PubMed

Hu, Minhao; Wattchow, David; de Fontgalland, Dayan

2018-03-01

The landscape of surgical anatomy education is progressively changing. Traditional methods, such as cadaveric dissection and didacticism are being increasingly phased out in undergraduate courses for multimodal approaches incorporating problem-based learning, radiology and computer-based simulations. Although effective at clinically contextualizing and integrating anatomical information, these approaches may be a poor substitute for fostering a grasp of foundational 'pure' anatomy. Dissection is ideal for this purpose and hence remains the cornerstone of anatomical education. However, novel methods and technological advancements continually give way to adjuncts such as cadaveric surgery, three-dimensional printing, virtual simulation and live surgical streaming, which have demonstrated significant efficacy alone or alongside dissection. Therefore, although divergent paradigms of 'new versus old' approaches have engulfed and divided the community, educators should seek to integrate the ancient and avant-garde to comprehensively satisfy all of the modern anatomy learner's educational needs. © 2017 Royal Australasian College of Surgeons.

The generalized pole assignment problem. [dynamic output feedback problems

NASA Technical Reports Server (NTRS)

Djaferis, T. E.; Mitter, S. K.

1979-01-01

Two dynamic output feedback problems for a linear, strictly proper system are considered, along with their interrelationships. The problems are formulated in the frequency domain and investigated in terms of linear equations over rings of polynomials. Necessary and sufficient conditions are expressed using genericity.

Formative feedback and scaffolding for developing complex problem solving and modelling outcomes

NASA Astrophysics Data System (ADS)

Frank, Brian; Simper, Natalie; Kaupp, James

2018-07-01

This paper discusses the use and impact of formative feedback and scaffolding to develop outcomes for complex problem solving in a required first-year course in engineering design and practice at a medium-sized research-intensive Canadian university. In 2010, the course began to use team-based, complex, open-ended contextualised problems to develop problem solving, communications, teamwork, modelling, and professional skills. Since then, formative feedback has been incorporated into: task and process-level feedback on scaffolded tasks in-class, formative assignments, and post-assignment review. Development in complex problem solving and modelling has been assessed through analysis of responses from student surveys, direct criterion-referenced assessment of course outcomes from 2013 to 2015, and an external longitudinal study. The findings suggest that students are improving in outcomes related to complex problem solving over the duration of the course. Most notably, the addition of new feedback and scaffolding coincided with improved student performance.

Child-Level Predictors of Responsiveness to Evidence-Based Mathematics Intervention.

PubMed

Powell, Sarah R; Cirino, Paul T; Malone, Amelia S

2017-07-01

We identified child-level predictors of responsiveness to 2 types of mathematics (calculation and word-problem) intervention among 2nd-grade children with mathematics difficulty. Participants were 250 children in 107 classrooms in 23 schools pretested on mathematics and general cognitive measures and posttested on mathematics measures. We assigned classrooms randomly assigned to calculation intervention, word-problem intervention, or business-as-usual control. Intervention lasted 17 weeks. Path analyses indicated that scores on working memory and language comprehension assessments moderated responsiveness to calculation intervention. No moderators were identified for responsiveness to word-problem intervention. Across both intervention groups and the control group, attentive behavior predicted both outcomes. Initial calculation skill predicted the calculation outcome, and initial language comprehension predicted word-problem outcomes. These results indicate that screening for calculation intervention should include a focus on working memory, language comprehension, attentive behavior, and calculations. Screening for word-problem intervention should focus on attentive behavior and word problems.

29 CFR 785.37 - Home to work on special one-day assignment in another city.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 3 2011-07-01 2011-07-01 false Home to work on special one-day assignment in another city... another city. A problem arises when an employee who regularly works at a fixed location in one city is given a special 1-day work assignment in another city. For example, an employee who works in Washington...

29 CFR 785.37 - Home to work on special one-day assignment in another city.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false Home to work on special one-day assignment in another city... another city. A problem arises when an employee who regularly works at a fixed location in one city is given a special 1-day work assignment in another city. For example, an employee who works in Washington...

Spectrum-to-Spectrum Searching Using a Proteome-wide Spectral Library*

PubMed Central

Yen, Chia-Yu; Houel, Stephane; Ahn, Natalie G.; Old, William M.

2011-01-01

The unambiguous assignment of tandem mass spectra (MS/MS) to peptide sequences remains a key unsolved problem in proteomics. Spectral library search strategies have emerged as a promising alternative for peptide identification, in which MS/MS spectra are directly compared against a reference library of confidently assigned spectra. Two problems relate to library size. First, reference spectral libraries are limited to rediscovery of previously identified peptides and are not applicable to new peptides, because of their incomplete coverage of the human proteome. Second, problems arise when searching a spectral library the size of the entire human proteome. We observed that traditional dot product scoring methods do not scale well with spectral library size, showing reduction in sensitivity when library size is increased. We show that this problem can be addressed by optimizing scoring metrics for spectrum-to-spectrum searches with large spectral libraries. MS/MS spectra for the 1.3 million predicted tryptic peptides in the human proteome are simulated using a kinetic fragmentation model (MassAnalyzer version2.1) to create a proteome-wide simulated spectral library. Searches of the simulated library increase MS/MS assignments by 24% compared with Mascot, when using probabilistic and rank based scoring methods. The proteome-wide coverage of the simulated library leads to 11% increase in unique peptide assignments, compared with parallel searches of a reference spectral library. Further improvement is attained when reference spectra and simulated spectra are combined into a hybrid spectral library, yielding 52% increased MS/MS assignments compared with Mascot searches. Our study demonstrates the advantages of using probabilistic and rank based scores to improve performance of spectrum-to-spectrum search strategies. PMID:21532008

New Technologies, New Possibilities for the Arts and Multimodality in English Language Arts

ERIC Educational Resources Information Center

Williams, Wendy R.

2014-01-01

This article discusses the arts, multimodality, and new technologies in English language arts. It then turns to the example of the illuminated text--a multimodal book report consisting of animated text, music, and images--to consider how art, multimodality, and technology can work together to support students' reading of literature and inspire…

Multimode fiber devices with single-mode performance

NASA Astrophysics Data System (ADS)

Leon-Saval, S. G.; Birks, T. A.; Bland-Hawthorn, J.; Englund, M.

2005-10-01

A taper transition can couple light between a multimode fiber and several single-mode fibers. If the number of single-mode fibers matches the number of spatial modes in the multimode fiber, the transition can have low loss in both directions. This enables the high performance of single-mode fiber devices to be attained in multimode fibers. We report an experimental proof of concept by using photonic crystal fiber techniques to make the transitions, demonstrating a multimode fiber filter with the transmission spectrum of a single-mode fiber grating.

A group-based tasks allocation algorithm for the optimization of long leave opportunities in academic departments

NASA Astrophysics Data System (ADS)

Eyono Obono, S. D.; Basak, Sujit Kumar

2011-12-01

The general formulation of the assignment problem consists in the optimal allocation of a given set of tasks to a workforce. This problem is covered by existing literature for different domains such as distributed databases, distributed systems, transportation, packets radio networks, IT outsourcing, and teaching allocation. This paper presents a new version of the assignment problem for the allocation of academic tasks to staff members in departments with long leave opportunities. It presents the description of a workload allocation scheme and its algorithm, for the allocation of an equitable number of tasks in academic departments where long leaves are necessary.

Encouraging Sixth-Grade Students' Problem-Solving Performance by Teaching through Problem Solving

ERIC Educational Resources Information Center

Bostic, Jonathan D.; Pape, Stephen J.; Jacobbe, Tim

2016-01-01

This teaching experiment provided students with continuous engagement in a problem-solving based instructional approach during one mathematics unit. Three sections of sixth-grade mathematics were sampled from a school in Florida, U.S.A. and one section was randomly assigned to experience teaching through problem solving. Students' problem-solving…

Thermal area effectiveness for future aircraft

NASA Technical Reports Server (NTRS)

Happ, W. W.

1975-01-01

Problem areas in airport planning, design, and operations identified by a decision matrix developed to display various airport functions interfaced with facilities and an extensive literature survey were investigated. Areas considered include: site selection and growth potential; emissions and noise control/containment for airports; financial and legal aspects of airport planning, contruction, and operation; intra-airport transportation and other passenger flow facilitators; simulation and modeling for airports; guidelines for airport multimodal access planning. Results are summarized and a bibliography is included.

Facilitating Revision in the English as a Second Language (ESL) Composition Classroom through Computer-Based Multimodal Composing Activities: A Case Study of Composing Practices of ESL Students

ERIC Educational Resources Information Center

Dzekoe, Richmond

2013-01-01

Literature on second language (L2) writing indicates that, on their own, L2 writers are not able to notice problems with the linguistic and rhetorical features of their drafts and do successful self-revision; and that there is the need to facilitate self-revision in the L2 writing classroom. In view of this need, this dissertation explored the…

Stochastic search in structural optimization - Genetic algorithms and simulated annealing

NASA Technical Reports Server (NTRS)

Hajela, Prabhat

1993-01-01

An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.

Multimodality Therapy and Liver Transplantation for Hepatocellular Carcinoma: A 14-Year Prospective Analysis of Outcomes

PubMed Central

Ramanathan, Rajesh; Sharma, Amit; Lee, David D; Behnke, Martha; Bornstein, Karen; Stravitz, R Todd; Sydnor, Malcolm; Fulcher, Ann; Cotterell, Adrian; Posner, Marc P; Fisher, Robert A

2014-01-01

Background Hepatocellular carcinoma is a major cause of death among patients with cirrhosis. A standardized approach of multimodality therapy with intent-to-treat by transplantation for all patients with hepatocellular carcinoma was instituted at our transplant center in 1997. Data were prospectively collected to evaluate the impact of multimodality therapy on post-transplant patient survival, tumor recurrence and patient survival without transplantation. Methods All patients with hepatocellular carcinoma were eligible for multimodality therapy. Multimodality therapy consisted of hepatic resection, radiofrequency ablation, transarterial chemoembolization, transarterial chemoinfusion, yttrium-90 microsphere radioembolization and sorafenib. Results 715 patients underwent multimodality therapy. 231 patients were included in the intent-to-treat with transplantation arm and 484 patients were treated with multimodality therapy or palliative therapy due to contraindications for transplantation. A 60.2% transplantation rate was achieved in the intent-to-treat with transplantation arm. Post-transplant survivals at 1- and 5-years were 97.1% and 72.5% respectively. Tumor recurrence rates at 1-, 3- and 5-years were 2.4%, 6.2% and 11.6% respectively. Patients with contraindications to transplant had increased 1- and 5-year survival from diagnosis with multimodality therapy compared to those not treated (73.1% and 46.5% vs. 15.5% and 4.4%, p<0.0001). Conclusions Using multimodality therapy prior to liver transplantation for hepatocellular carcinoma achieved low recurrence rates and post-transplant survival equivalent to patients with primary liver disease without hepatocellular carcinoma. Multimodality therapy may help identify patients with less active tumor biology and result in improved disease-free survival and organ utilization. PMID:24503764

An integrated GIS-based data model for multimodal urban public transportation analysis and management

NASA Astrophysics Data System (ADS)

Chen, Shaopei; Tan, Jianjun; Ray, C.; Claramunt, C.; Sun, Qinqin

2008-10-01

Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Reconceptualising Understandings of Texts, Readers and Contexts: One English Teacher's Response to Using Multimodal Texts and Interactive Whiteboards

ERIC Educational Resources Information Center

Kitson, Lisbeth

2011-01-01

The comprehension of multimodal texts is now a key concern with the release of the Australian National Curriculum for English (ACARA, 2010). However, the nature of multimodal texts, the diversity of readers in classrooms, and the complex technological environments through which multimodal texts are mediated, requires English teachers to reconsider…

Preference in Random Assignment: Implications for the Interpretation of Randomized Trials

PubMed Central

Gold, Paul B.; Hargreaves, William A.; Aronson, Elliot; Bickman, Leonard; Barreira, Paul J.; Jones, Danson R.; Rodican, Charles F.; Fisher, William H.

2009-01-01

Random assignment to a preferred experimental condition can increase service engagement and enhance outcomes, while assignment to a less-preferred condition can discourage service receipt and limit outcome attainment. We examined randomized trials for one prominent psychiatric rehabilitation intervention, supported employment, to gauge how often assignment preference might have complicated the interpretation of findings. Condition descriptions, and greater early attrition from services-as-usual comparison conditions, suggest that many study enrollees favored assignment to new rapid-job-placement supported employment, but no study took this possibility into account. Reviews of trials in other service fields are needed to determine whether this design problem is widespread. PMID:19434489

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

Improving the accuracy of the diagnosis of schizophrenia by means of virtual reality.

PubMed

Sorkin, Anna; Weinshall, Daphna; Modai, Ilan; Peled, Avi

2006-03-01

The authors' goal was to improve the diagnosis of schizophrenia by using virtual reality technology to build a complex, multimodal environment in which cognitive functions can be studied (and measured) in parallel. The authors studied sensory integration within working memory by means of computer navigation through a virtual maze. The simulated journey consisted of a series of rooms, each of which included three doors. Each door was characterized by three features (color, shape, and sound), and a single combination of features--the door-opening rule--was correct. Subjects had to learn the rule and use it. The participants were 39 schizophrenic patients and 21 healthy comparison subjects. Upon completion, each subject was assigned a performance profile, including various error scores, response time, navigation ability, and strategy. A classification procedure based on the subjects' performance profile correctly predicted 85% of the schizophrenic patients (and all of the comparison subjects). Several performance variables showed significant correlations with scores on a standard diagnostic measure (Positive and Negative Syndrome Scale), suggesting potential use of these measurements for the diagnosis of schizophrenia. On the other hand, the patients did not show unusual repetition of response despite stimulus cessation (called "perseveration" in classical studies of schizophrenia), which is a common symptom of the disease. This deficit appeared only when the subjects did not receive proper explanation of the task. The ability to study multimodal performance simultaneously by using virtual reality technology opens new possibilities for the diagnosis of schizophrenia with objective procedures.

Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems.

PubMed

Mehler, Bruce; Kidd, David; Reimer, Bryan; Reagan, Ian; Dobres, Jonathan; McCartt, Anne

2016-03-01

One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers' visual and manual distractions with 'infotainment' technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual-manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox 'one-shot' voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory-vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers' interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation.

Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems

PubMed Central

Mehler, Bruce; Kidd, David; Reimer, Bryan; Reagan, Ian; Dobres, Jonathan; McCartt, Anne

2016-01-01

Abstract One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers’ visual and manual distractions with ‘infotainment’ technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual–manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox ‘one-shot’ voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory–vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers’ interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation. PMID:26269281

Assigning Oxidation States to Some Metal Dioxygen Complexes of Biological Interest.

ERIC Educational Resources Information Center

Summerville, David A.; And Others

1979-01-01

The bonding of dioxygen in metal-dioxygen complexes is discussed, paying particular attention to the problems encountered in assigning conventional oxidation numbers to both the metal center and coordinated dioxygen. Complexes of iron, cobalt, chromium, and manganese are considered. (BB)

College Students' Preferences for Psychotherapy across Depression, Anxiety, Relationship, and Academic Problems

ERIC Educational Resources Information Center

Joyce, Aaron W.; Ross, Michael J.; Vander Wal, Jillon S.; Austin, Chammie C.

2009-01-01

The present study examined differences in college students' preferences for processes of change across four kinds of problems: academic, relationship, depression, and anxiety. Two hundred eighteen undergraduates were randomly assigned to complete either an academic problems, relationship problems, depression, or anxiety Processes of Change…

Interleaved Practice Improves Mathematics Learning

ERIC Educational Resources Information Center

Rohrer, Doug; Dedrick, Robert F.; Stershic, Sandra

2015-01-01

A typical mathematics assignment consists primarily of practice problems requiring the strategy introduced in the immediately preceding lesson (e.g., a dozen problems that are solved by using the Pythagorean theorem). This means that students know which strategy is needed to solve each problem before they read the problem. In an alternative…

Steady-State ALPS for Real-Valued Problems

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2009-01-01

The two objectives of this paper are to describe a steady-state version of the Age-Layered Population Structure (ALPS) Evolutionary Algorithm (EA) and to compare it against other GAs on real-valued problems. Motivation for this work comes from our previous success in demonstrating that a generational version of ALPS greatly improves search performance on a Genetic Programming problem. In making steady-state ALPS some modifications were made to the method for calculating age and the method for moving individuals up layers. To demonstrate that ALPS works well on real-valued problems we compare it against CMA-ES and Differential Evolution (DE) on five challenging, real-valued functions and on one real-world problem. While CMA-ES and DE outperform ALPS on the two unimodal test functions, ALPS is much better on the three multimodal test problems and on the real-world problem. Further examination shows that, unlike the other GAs, ALPS maintains a genotypically diverse population throughout the entire search process. These findings strongly suggest that the ALPS paradigm is better able to avoid premature convergence then the other GAs.

Binary Bees Algorithm - bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem

NASA Astrophysics Data System (ADS)

Xu, Shuo; Ji, Ze; Truong Pham, Duc; Yu, Fan

2011-11-01

The simultaneous mission assignment and home allocation for hospital service robots studied is a Multidimensional Assignment Problem (MAP) with multiobjectives and multiconstraints. A population-based metaheuristic, the Binary Bees Algorithm (BBA), is proposed to optimize this NP-hard problem. Inspired by the foraging mechanism of honeybees, the BBA's most important feature is an explicit functional partitioning between global search and local search for exploration and exploitation, respectively. Its key parts consist of adaptive global search, three-step elitism selection (constraint handling, non-dominated solutions selection, and diversity preservation), and elites-centred local search within a Hamming neighbourhood. Two comparative experiments were conducted to investigate its single objective optimization, optimization effectiveness (indexed by the S-metric and C-metric) and optimization efficiency (indexed by computational burden and CPU time) in detail. The BBA outperformed its competitors in almost all the quantitative indices. Hence, the above overall scheme, and particularly the searching history-adapted global search strategy was validated.

GCSE Assessment Notes: Six GCSE Assessment Assignments.

ERIC Educational Resources Information Center

Graham, Stephen

1988-01-01

Provided are copy masters, instructions for use, and grading criteria for six problems used as part of the practical assessment for a modular science course. Each problem gives a narrative and a list of materials necessary to complete the problem. (CW)

Alternative therapies for metastatic breast cancer: multimodal approach targeting tumor cell heterogeneity.

PubMed

Sambi, Manpreet; Haq, Sabah; Samuel, Vanessa; Qorri, Bessi; Haxho, Fiona; Hill, Kelli; Harless, William; Szewczuk, Myron R

2017-01-01

One of the primary challenges in developing effective therapies for malignant tumors is the specific targeting of a heterogeneous cancer cell population within the tumor. The cancerous tumor is made up of a variety of distinct cells with specialized receptors and proteins that could potentially be viable targets for drugs. In addition, the diverse signals from the local microenvironment may also contribute to the induction of tumor growth and metastasis. Collectively, these factors must be strategically studied and targeted in order to develop an effective treatment protocol. Targeted multimodal approaches need to be strategically studied in order to develop a treatment protocol that is successful in controlling tumor growth and preventing metastatic burden. Breast cancer, in particular, presents a unique problem because of the variety of subtypes of cancer that can arise and the multiple drug targets that could be exploited. For example, the tumor stage and subtypes often dictate the appropriate treatment regimen. Alternate multimodal therapies should consider the importance of time-dependent drug administration, as well as targeting the local and systemic tumor environment. Many reviews and papers have briefly touched on the clinical implications of this cellular heterogeneity; however, there has been very little discussion on the development of study models that reflect this diversity and on multimodal therapies that could target these subpopulations. Here, we summarize the current understanding of the origins of intratumoral heterogeneity in breast cancer subtypes, and its implications for tumor progression, metastatic potential, and treatment regimens. We also discuss the advantages and disadvantages of utilizing specific breast cancer models for research, including in vitro monolayer systems and three-dimensional mammospheres, as well as in vivo murine models that may have the capacity to encompass this heterogeneity. Lastly, we summarize some of the current advancements in the development of multitarget therapeutics that have shown promising results in clinical and preclinical studies when used alone or in combination with traditional regimens of surgery, chemotherapy, and/or radiation.

Real life working shift assignment problem

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Kwek, Yeek-Ling; Tiong, Wei-King; Chiew, Kang-Leng

2017-07-01

This study concerns about the working shift assignment in an outlet of Supermarket X in Eastern Mall, Kuching. The working shift assignment needs to be solved at least once in every month. Current approval process of working shifts is too troublesome and time-consuming. Furthermore, the management staff cannot have an overview of manpower and working shift schedule. Thus, the aim of this study is to develop working shift assignment simulation and propose a working shift assignment solution. The main objective for this study is to fulfill manpower demand at minimum operation cost. Besides, the day off and meal break policy should be fulfilled accordingly. Demand based heuristic is proposed to assign working shift and the quality of the solution is evaluated by using the real data.

SALSA: A Novel Dataset for Multimodal Group Behavior Analysis.

PubMed

Alameda-Pineda, Xavier; Staiano, Jacopo; Subramanian, Ramanathan; Batrinca, Ligia; Ricci, Elisa; Lepri, Bruno; Lanz, Oswald; Sebe, Nicu

2016-08-01

Studying free-standing conversational groups (FCGs) in unstructured social settings (e.g., cocktail party ) is gratifying due to the wealth of information available at the group (mining social networks) and individual (recognizing native behavioral and personality traits) levels. However, analyzing social scenes involving FCGs is also highly challenging due to the difficulty in extracting behavioral cues such as target locations, their speaking activity and head/body pose due to crowdedness and presence of extreme occlusions. To this end, we propose SALSA, a novel dataset facilitating multimodal and Synergetic sociAL Scene Analysis, and make two main contributions to research on automated social interaction analysis: (1) SALSA records social interactions among 18 participants in a natural, indoor environment for over 60 minutes, under the poster presentation and cocktail party contexts presenting difficulties in the form of low-resolution images, lighting variations, numerous occlusions, reverberations and interfering sound sources; (2) To alleviate these problems we facilitate multimodal analysis by recording the social interplay using four static surveillance cameras and sociometric badges worn by each participant, comprising the microphone, accelerometer, bluetooth and infrared sensors. In addition to raw data, we also provide annotations concerning individuals' personality as well as their position, head, body orientation and F-formation information over the entire event duration. Through extensive experiments with state-of-the-art approaches, we show (a) the limitations of current methods and (b) how the recorded multiple cues synergetically aid automatic analysis of social interactions. SALSA is available at http://tev.fbk.eu/salsa.

Multi-modal myocontrol: Testing combined force- and electromyography.

PubMed

Nowak, Markus; Eiband, Thomas; Castellini, Claudio

2017-07-01

Myocontrol, that is control of prostheses using bodily signals, has proved in the decades to be a surprisingly hard problem for the scientific community of assistive and rehabilitation robotics. In particular, traditional surface electromyography (sEMG) seems to be no longer enough to guarantee dexterity (i.e., control over several degrees of freedom) and, most importantly, reliability. Multi-modal myocontrol is concerned with the idea of using novel signal gathering techniques as a replacement of, or alongside, sEMG, to provide high-density and diverse signals to improve dexterity and make the control more reliable. In this paper we present an offline and online assessment of multi-modal sEMG and force myography (FMG) targeted at hand and wrist myocontrol. A total number of twenty sEMG and FMG sensors were used simultaneously, in several combined configurations, to predict opening/closing of the hand and activation of two degrees of freedom of the wrist of ten intact subjects. The analysis was targeted at determining the optimal sensor combination and control parameters; the experimental results indicate that sEMG sensors alone perform worst, yielding a nRMSE of 9.1%, while mixing FMG and sEMG or using FMG only reduces the nRMSE to 5.2-6.6%. To validate these results, we engaged the subject with median performance in an online goal-reaching task. Analysis of this further experiment reveals that the online behaviour is similar to the offline one.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

Aerobic training for improved memory in patients with stress-related exhaustion: a randomized controlled trial.

PubMed

Eskilsson, Therese; Slunga Järvholm, Lisbeth; Malmberg Gavelin, Hanna; Stigsdotter Neely, Anna; Boraxbekk, Carl-Johan

2017-09-02

Patients with stress-related exhaustion suffer from cognitive impairments, which often remain after psychological treatment or work place interventions. It is important to find effective treatments that can address this problem. Therefore, the aim of this study was to investigate the effects on cognitive performance and psychological variables of a 12-week aerobic training program performed at a moderate-vigorous intensity for patients with exhaustion disorder who participated in a multimodal rehabilitation program. In this open-label, parallel, randomized and controlled trial, 88 patients diagnosed with exhaustion disorder participated in a 24-week multimodal rehabilitation program. After 12 weeks in the program the patients were randomized to either a 12-week aerobic training intervention or to a control group with no additional training. Primary outcome measure was cognitive function, and secondary outcome measures were psychological health variables and aerobic capacity. In total, 51% patients in the aerobic training group and 78% patients in the control group completed the intervention period. The aerobic training group significantly improved in maximal oxygen uptake and episodic memory performance. No additional improvement in burnout, depression or anxiety was observed in the aerobic group compared with controls. Aerobic training at a moderate-vigorous intensity within a multimodal rehabilitation program for patients with exhaustion disorder facilitated episodic memory. A future challenge would be the clinical implementation of aerobic training and methods to increase feasibility in this patient group. ClinicalTrials.gov: NCT03073772 . Retrospectively registered 21 February 2017.

Evaluation of the Dawson College Shooting Psychological Intervention: Moving Toward a Multimodal Extensive Plan

PubMed Central

Séguin, Monique; Chawky, Nadia; Lesage, Alain; Boyer, Richard; Guay, Stéphane; Bleau, Pierre; Miquelon, Paule; Szkrumelak, Nadia; Steiner, Warren; Roy, Denise

2013-01-01

In 2006, following the shooting at Dawson College, the authorities implemented an intervention plan. This provided an opportunity to analyze the responses to services offered, and afforded a learning opportunity, which led to the proposal of an extensive multimodal short- and long-term psychological plan for future needs. Both quantitative and qualitative data were gathered 18 months after the event, involving the participation of 948 students and staff. Mental health problems and the perception of services offered after the shooting were investigated, using standardized measures. Second, focus groups and individual interviews were conducted among a subgroup of participants (support team members; teachers and employees; students and parents) and permitted to gather data on services received and services required. Individual report of events, the extent of psychological impact and services offered and received were analyzed in terms of the following dimensions: intervention philosophy, training, ongoing offer of services and finally, detection and outreach. A significant incidence of disorders and a high rate of exacerbation of preexisting mental disorders were observed within the 18 months following the shooting. Postimmediate and short-term intervention appeared adequate, but the long-term collective vision toward community support and availability of mental health services were lacking. Lessons learned from this evaluation and other school shootings suggest that preparedness and long-term community responses are often overlooked. A multimodal extensive plan is proposed based on a theoretical model from which interventions strategies could be drawn. PMID:24795790

Constructing and Using Multimodal Narratives to Research in Science Education: Contributions Based on Practical Classroom

NASA Astrophysics Data System (ADS)

Lopes, J. B.; Silva, A. A.; Cravino, J. P.; Santos, C. A.; Cunha, A.; Pinto, A.; Silva, A.; Viegas, C.; Saraiva, E.; Branco, M. J.

2014-06-01

This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of teaching and learning processes, we developed the multimodal narrative (MN), which describes what happens during a task and incorporates data such as examples of students' work, photos, diagrams, etc. Also, it describes teachers' intentions, preserving the nature of teaching practice in natural settings and it is verifiable and comparable. In this paper, we show how the MN was developed and present the protocol that was used for its construction. We identify the main characteristics of the MN and place it in the context of international research. We explore the potential of the MN for research purposes, illustrating its use in a research study that we carried out. We find that the MN provides a way to gather, organize and transform data, avoiding confusing and time-consuming manipulation of data, while minimizing the natural subjectivity of the narrator. The same MN can be used by the same or by different researchers for different purposes. Furthermore, the same MN can be used with different analysis techniques. It is also possible to study research practices on a large scale using MNs from different teachers and lessons. We propose that MNs can also be useful for teachers' professional development.

Measuring Human Performance on Clustering Problems: Some Potential Objective Criteria and Experimental Research Opportunities

ERIC Educational Resources Information Center

Brusco, Michael J.

2007-01-01

The study of human performance on discrete optimization problems has a considerable history that spans various disciplines. The two most widely studied problems are the Euclidean traveling salesperson problem and the quadratic assignment problem. The purpose of this paper is to outline a program of study for the measurement of human performance on…

An investigation of the use of temporal decomposition in space mission scheduling

NASA Technical Reports Server (NTRS)

Bullington, Stanley E.; Narayanan, Venkat

1994-01-01

This research involves an examination of techniques for solving scheduling problems in long-duration space missions. The mission timeline is broken up into several time segments, which are then scheduled incrementally. Three methods are presented for identifying the activities that are to be attempted within these segments. The first method is a mathematical model, which is presented primarily to illustrate the structure of the temporal decomposition problem. Since the mathematical model is bound to be computationally prohibitive for realistic problems, two heuristic assignment procedures are also presented. The first heuristic method is based on dispatching rules for activity selection, and the second heuristic assigns performances of a model evenly over timeline segments. These heuristics are tested using a sample Space Station mission and a Spacelab mission. The results are compared with those obtained by scheduling the missions without any problem decomposition. The applicability of this approach to large-scale mission scheduling problems is also discussed.

Parallel, Asynchronous Executive (PAX): System concepts, facilities, and architecture

NASA Technical Reports Server (NTRS)

Jones, W. H.

1983-01-01

The Parallel, Asynchronous Executive (PAX) is a software operating system simulation that allows many computers to work on a single problem at the same time. PAX is currently implemented on a UNIVAC 1100/42 computer system. Independent UNIVAC runstreams are used to simulate independent computers. Data are shared among independent UNIVAC runstreams through shared mass-storage files. PAX has achieved the following: (1) applied several computing processes simultaneously to a single, logically unified problem; (2) resolved most parallel processor conflicts by careful work assignment; (3) resolved by means of worker requests to PAX all conflicts not resolved by work assignment; (4) provided fault isolation and recovery mechanisms to meet the problems of an actual parallel, asynchronous processing machine. Additionally, one real-life problem has been constructed for the PAX environment. This is CASPER, a collection of aerodynamic and structural dynamic problem simulation routines. CASPER is not discussed in this report except to provide examples of parallel-processing techniques.

MILP model for integrated balancing and sequencing mixed-model two-sided assembly line with variable launching interval and assignment restrictions

NASA Astrophysics Data System (ADS)

Azmi, N. I. L. Mohd; Ahmad, R.; Zainuddin, Z. M.

2017-09-01

This research explores the Mixed-Model Two-Sided Assembly Line (MMTSAL). There are two interrelated problems in MMTSAL which are line balancing and model sequencing. In previous studies, many researchers considered these problems separately and only few studied them simultaneously for one-sided line. However in this study, these two problems are solved simultaneously to obtain more efficient solution. The Mixed Integer Linear Programming (MILP) model with objectives of minimizing total utility work and idle time is generated by considering variable launching interval and assignment restriction constraint. The problem is analysed using small-size test cases to validate the integrated model. Throughout this paper, numerical experiment was conducted by using General Algebraic Modelling System (GAMS) with the solver CPLEX. Experimental results indicate that integrating the problems of model sequencing and line balancing help to minimise the proposed objectives function.

Enhancing resource coordination for multi-modal evacuation planning.

DOT National Transportation Integrated Search

2013-01-01

This research project seeks to increase knowledge about coordinating effective multi-modal evacuation for disasters. It does so by identifying, evaluating, and assessing : current transportation management approaches for multi-modal evacuation planni...

Survey of statewide multimodal transportation planning practices.

DOT National Transportation Integrated Search

2002-01-01

Multimodal planning refers to planning for different modes of transportation (e.g., automobile, bus, bicycles, pedestrian, aviation, rail, waterways) and the connections among them. This study identified states thought to excel in multimodal planning...

NVR-BIP: Nuclear Vector Replacement using Binary Integer Programming for NMR Structure-Based Assignments.

PubMed

Apaydin, Mehmet Serkan; Çatay, Bülent; Patrick, Nicholas; Donald, Bruce R

2011-05-01

Nuclear magnetic resonance (NMR) spectroscopy is an important experimental technique that allows one to study protein structure and dynamics in solution. An important bottleneck in NMR protein structure determination is the assignment of NMR peaks to the corresponding nuclei. Structure-based assignment (SBA) aims to solve this problem with the help of a template protein which is homologous to the target and has applications in the study of structure-activity relationship, protein-protein and protein-ligand interactions. We formulate SBA as a linear assignment problem with additional nuclear overhauser effect constraints, which can be solved within nuclear vector replacement's (NVR) framework (Langmead, C., Yan, A., Lilien, R., Wang, L. and Donald, B. (2003) A Polynomial-Time Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Proc. the 7th Annual Int. Conf. Research in Computational Molecular Biology (RECOMB) , Berlin, Germany, April 10-13, pp. 176-187. ACM Press, New York, NY. J. Comp. Bio. , (2004), 11, pp. 277-298; Langmead, C. and Donald, B. (2004) An expectation/maximization nuclear vector replacement algorithm for automated NMR resonance assignments. J. Biomol. NMR , 29, 111-138). Our approach uses NVR's scoring function and data types and also gives the option of using CH and NH residual dipolar coupling (RDCs), instead of NH RDCs which NVR requires. We test our technique on NVR's data set as well as on four new proteins. Our results are comparable to NVR's assignment accuracy on NVR's test set, but higher on novel proteins. Our approach allows partial assignments. It is also complete and can return the optimum as well as near-optimum assignments. Furthermore, it allows us to analyze the information content of each data type and is easily extendable to accept new forms of input data, such as additional RDCs.

Single and low order mode interrogation of a multimode sapphire fiber Bragg grating sensor with tapered fibers

NASA Astrophysics Data System (ADS)

Grobnic, Dan; Mihailov, Stephen J.; Ding, H.; Bilodeau, F.; Smelser, Christopher W.

2005-05-01

Multimode sapphire fiber Bragg gratings (SFBG) made with an IR femtosecond laser and a phase mask were probed using tapered single mode fibers of different taper diameters producing single and low order mode reflection/transmission responses. A configuration made of an input single mode tapered fiber and multimode silica fiber used for output coupling was also tested and has delivered a filtered multimode transmission spectrum. The tapered coupling improved the spectral resolution of the SFBG as compared to its multimode responses previously reported. Such improvements facilitate the utilization of the SFBG as a high temperature sensor. Wavelength shifts of the single mode response were monitored as a function of temperature up to 1500 °C and were consistent with the measurement obtained from the multimode response published previously.

Multimode entanglement in reconfigurable graph states using optical frequency combs

PubMed Central

Cai, Y.; Roslund, J.; Ferrini, G.; Arzani, F.; Xu, X.; Fabre, C.; Treps, N.

2017-01-01

Multimode entanglement is an essential resource for quantum information processing and quantum metrology. However, multimode entangled states are generally constructed by targeting a specific graph configuration. This yields to a fixed experimental setup that therefore exhibits reduced versatility and scalability. Here we demonstrate an optical on-demand, reconfigurable multimode entangled state, using an intrinsically multimode quantum resource and a homodyne detection apparatus. Without altering either the initial squeezing source or experimental architecture, we realize the construction of thirteen cluster states of various sizes and connectivities as well as the implementation of a secret sharing protocol. In particular, this system enables the interrogation of quantum correlations and fluctuations for any multimode Gaussian state. This initiates an avenue for implementing on-demand quantum information processing by only adapting the measurement process and not the experimental layout. PMID:28585530

Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

PubMed

Karkov, Hanne Sophie; Krogh, Berit Olsen; Woo, James; Parimal, Siddharth; Ahmadian, Haleh; Cramer, Steven M

2015-11-01

In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules. © 2015 Wiley Periodicals, Inc.

The use of writing assignments to help students synthesize content in upper-level undergraduate biology courses.

PubMed

Sparks-Thissen, Rebecca L

2017-02-01

Biology education is undergoing a transformation toward a more student-centered, inquiry-driven classroom. Many educators have designed engaging assignments that are designed to help undergraduate students gain exposure to the scientific process and data analysis. One of these types of assignments is use of a grant proposal assignment. Many instructors have used these assignments in lecture-based courses to help students process information in the literature and apply that information to a novel problem such as design of an antiviral drug or a vaccine. These assignments have been helpful in engaging students in the scientific process in the absence of an inquiry-driven laboratory. This commentary discusses the application of these grant proposal writing assignments to undergraduate biology courses. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Joint Sparse Representation for Robust Multimodal Biometrics Recognition

DTIC Science & Technology

2012-01-01

described in III. Experimental evaluations on a comprehensive multimodal dataset and a face database have been described in section V. Finally, in...WVU Multimodal Dataset The WVU multimodal dataset is a comprehensive collection of different biometric modalities such as fingerprint, iris, palmprint ...Martnez and R. Benavente, “The AR face database ,” CVC Technical Report, June 1998. [29] U. Park and A. Jain, “Face matching and retrieval using soft

Ecologically-Based Family Therapy Outcome with Substance Abusing Runaway Adolescents

PubMed Central

Slesnick, Natasha; Prestopnik, Jillian L.

2007-01-01

Runaway youth report a broader range and higher severity of substance-related, mental health and family problems relative to non-runaway youth. Most studies to date have collected self-report data on the family and social history; virtually no research has examined treatment effectiveness with this population. This study is a treatment development project in which 124 runaway youth were randomly assigned to 1) Ecologically-Based Family Therapy (EBFT) or 2) Service as Usual (SAU) through a shelter. Youth completed an intake, posttreatment, 6 and 12 month follow-up assessment. Youth assigned to EBFT reported greater reductions in overall substance abuse compared to youth assigned to SAU while other problem areas improved in both conditions. Findings suggest that EBFT is an efficacious intervention for this relatively severe population of youth. PMID:15878048

Using sound to solve syntactic problems: the role of phonology in grammatical category assignments.

PubMed

Kelly, M H

1992-04-01

One ubiquitous problem in language processing involves the assignment of words to the correct grammatical category, such as noun or verb. In general, semantic and syntactic cues have been cited as the principal information for grammatical category assignment, to the neglect of possible phonological cues. This neglect is unwarranted, and the following claims are made: (a) Numerous correlations between phonology and grammatical class exist, (b) some of these correlations are large and can pervade the entire lexicon of a language and hence can involve thousands of words, (c) experiments have repeatedly found that adults and children have learned these correlations, and (d) explanations for how these correlations arose can be proposed and evaluated. Implications of these phenomena for language representation and processing are discussed.

From simple receptors to complex multimodal percepts: a first global picture on the mechanisms involved in perceptual binding.

PubMed

Velik, Rosemarie

2012-01-01

The binding problem in perception is concerned with answering the question how information from millions of sensory receptors, processed by millions of neurons working in parallel, can be merged into a unified percept. Binding in perception reaches from the lowest levels of feature binding up to the levels of multimodal binding of information coming from the different sensor modalities and also from other functional systems. The last 40 years of research have shown that the binding problem cannot be solved easily. Today, it is considered as one of the key questions to brain understanding. To date, various solutions have been suggested to the binding problem including: (1) combination coding, (2) binding by synchrony, (3) population coding, (4) binding by attention, (5) binding by knowledge, expectation, and memory, (6) hardwired vs. on-demand binding, (7) bundling and binding of features, (8) the feature-integration theory of attention, and (9) synchronization through top-down processes. Each of those hypotheses addresses important aspects of binding. However, each of them also suffers from certain weak points and can never give a complete explanation. This article gives a brief overview of the so far suggested solutions of perceptual binding and then shows that those are actually not mutually exclusive but can complement each other. A computationally verified model is presented which shows that, most likely, the different described mechanisms of binding act (1) at different hierarchical levels and (2) in different stages of "perceptual knowledge acquisition." The model furthermore considers and explains a number of inhibitory "filter mechanisms" that suppress the activation of inappropriate or currently irrelevant information.

From Simple Receptors to Complex Multimodal Percepts: A First Global Picture on the Mechanisms Involved in Perceptual Binding

PubMed Central

Velik, Rosemarie

2012-01-01

The binding problem in perception is concerned with answering the question how information from millions of sensory receptors, processed by millions of neurons working in parallel, can be merged into a unified percept. Binding in perception reaches from the lowest levels of feature binding up to the levels of multimodal binding of information coming from the different sensor modalities and also from other functional systems. The last 40 years of research have shown that the binding problem cannot be solved easily. Today, it is considered as one of the key questions to brain understanding. To date, various solutions have been suggested to the binding problem including: (1) combination coding, (2) binding by synchrony, (3) population coding, (4) binding by attention, (5) binding by knowledge, expectation, and memory, (6) hardwired vs. on-demand binding, (7) bundling and binding of features, (8) the feature-integration theory of attention, and (9) synchronization through top-down processes. Each of those hypotheses addresses important aspects of binding. However, each of them also suffers from certain weak points and can never give a complete explanation. This article gives a brief overview of the so far suggested solutions of perceptual binding and then shows that those are actually not mutually exclusive but can complement each other. A computationally verified model is presented which shows that, most likely, the different described mechanisms of binding act (1) at different hierarchical levels and (2) in different stages of “perceptual knowledge acquisition.” The model furthermore considers and explains a number of inhibitory “filter mechanisms” that suppress the activation of inappropriate or currently irrelevant information. PMID:22837751

Multimodal Freight Distribution to Support Increased Port Operations

DOT National Transportation Integrated Search

2016-10-01

To support improved port operations, three different aspects of multimodal freight distribution are investigated: (i) Efficient load planning for double stack trains at inland ports; (ii) Optimization of a multimodal network for environmental sustain...

Towards the future : the promise of intermodal and multimodal transportation systems

DOT National Transportation Integrated Search

1995-02-01

Issues relating to intermodal and multimodal transportation systems are introduced and defined. Intermodal and multimodal transportation solutons are assessed within the framework of legislative efforts such as Intermodal Surface Transportation Effic...

Modeling intelligent agent beliefs in a card game scenario

NASA Astrophysics Data System (ADS)

Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

Innovative Approaches to Fuel-Air Mixing and Combustion in Airbreathing Hypersonic Engines

NASA Astrophysics Data System (ADS)

MacLeod, C.

This paper describes some innovative methods for achieving enhanced fuel-air mixing and combustion in Scramjet-like spaceplane engines. A multimodal approach to the problem is discussed; this involves using several concurrent methods of forced mixing. The paper concentrates on Electromagnetic Activation (EMA) and Electrostatic Attraction as suitable techniques for this purpose - although several other potential methods are also discussed. Previously published empirical data is used to draw conclusions about the likely effectiveness of the system and possible engine topologies are outlined.

FIBER AND INTEGRATED OPTICS: Propagation of circularly polarized light along a curved trajectory

NASA Astrophysics Data System (ADS)

Sadykov, Nail R.

1992-10-01

How the eigenfunction of an optical fiber is affected by a slight curvature at bends of the fiber without twisting is analyzed. The effect of a twisting of the ray trajectory in the case with curvature is examined theoretically by the geometric-optics approach. The results are used to analyze the problem of the turning of a meridional ray due to a circular polarization in a multimode optical fiber with a parabolic profile of the refractive index.

Multimodality imaging of foreign bodies of the musculoskeletal system.

PubMed

Jarraya, Mohamed; Hayashi, Daichi; de Villiers, Richard V; Roemer, Frank W; Murakami, Akira M; Cossi, Alda; Guermazi, Ali

2014-07-01

The purpose of this article is to clarify the most relevant points in managing suspected foreign bodies of the musculoskeletal system on the basis of a literature review and published reports with cases to illustrate each type on different imaging modalities. Foreign bodies of the musculoskeletal system are a common problem in emergency departments, with more than a third missed in the initial clinical evaluation. These retained objects may result in various complications and also offer fertile ground for litigation.

Problem Solution Project: Transforming Curriculum and Empowering Urban Students and Teachers

ERIC Educational Resources Information Center

Jarrett, Olga S.; Stenhouse, Vera

2011-01-01

This article presents findings of 6 years of implementing a Problem Solution Project, an assignment influenced by service learning, problem-based learning, critical theory, and critical pedagogy whereby teachers help children tackle real problems. Projects of 135 teachers in an urban certification/master's program were summarized by cohort year…

Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

DTIC Science & Technology

2015-12-24

minimizing a weighted sum ofthe time and control effort needed to collect sensor data. This problem formulation is a modified traveling salesman ...29 2.5 The Shortest Path Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5.1 Traveling Salesman Problem ...48 3.3.1 Initial Guess by Traveling Salesman Problem Solution

American Viticultural Areas: A Problem in Regional Geography.

ERIC Educational Resources Information Center

Macdonald, Gerald M.; Lemaire, Denyse

1995-01-01

Maintains that growing grapes for winemaking has increased dramatically in the United States. Describes a college class assignment in which students analyzed climate and soil type to identify appropriate viticulture areas. Reports high student interest in the assignment and includes four figures illustrating the approach. (CFR)

Motion Planning and Task Assignment for Unmanned Aerial Vehicles Cooperating with Unattended Ground Sensors

DTIC Science & Technology

2014-10-24

problem was formalized as the Dubins travelling salesman problem (TSP). In the second phase of the research we have...given constraints on its motion. This problem was formalized as the Dubins travelling salesman problem (TSP). The contributions of the study in the... problem was formalized as the Dubins travelling salesman problem (TSP). The Dubins Travelling Salesperson Problem (DTSP) and its variants [8, 12,

PROBABILISTIC CROSS-IDENTIFICATION IN CROWDED FIELDS AS AN ASSIGNMENT PROBLEM

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

Budavári, Tamás; Basu, Amitabh, E-mail: budavari@jhu.edu, E-mail: basu.amitabh@jhu.edu

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

NASA Astrophysics Data System (ADS)

2018-05-01

Eigenvalues and eigenvectors, together, constitute the eigenstructure of the system. The design of vibrating systems aimed at satisfying specifications on eigenvalues and eigenvectors, which is commonly known as eigenstructure assignment, has drawn increasing interest over the recent years. The most natural mathematical framework for such problems is constituted by the inverse eigenproblems, which consist in the determination of the system model that features a desired set of eigenvalues and eigenvectors. Although such a problem is intrinsically challenging, several solutions have been proposed in the literature. The approaches to eigenstructure assignment can be basically divided into passive control and active control.

Probabilistic Cross-identification in Crowded Fields as an Assignment Problem

NASA Astrophysics Data System (ADS)

Budavári, Tamás; Basu, Amitabh

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

Complete virilization in congenital adrenal hyperplasia: clinical course, medical management and disease-related complications.

PubMed

Woelfle, J; Hoepffner, W; Sippell, W G; Brämswig, J H; Heidemann, P; Deiss, D; Bökenkamp, A; Roth, C; Irle, U; Wollmann, H A; Zachmann, M; Kubini, K; Albers, N

2002-02-01

In girls with congenital adrenal hyperplasia (CAH), genital ambiguity usually leads to a rapid neonatal diagnosis. Rarely, CAH causes complete virilization and male sex assignment with a delayed diagnosis. After being confronted with very specific problems in two of such patients, we collected data of patients with CAH and complete virilization in a nationwide study to delineate specific problems of these rare patients in order to improve their management. Through the German Working Group of Paediatric Endocrinology (Arbeitsgemeinschaft Pädiatrische Endokrinologie, APE), questionnaires were sent to all members caring for patients with CAH and complete virilization in their endocrine clinics. Data from 16 patients from 10 paediatric endocrine centres were assessed by questionnaire. The following problems have been encountered. (1) Sex assignment/gender identity: initially all patients had a male sex assignment. Six patients were diagnosed during the first month of life. Five were reassigned to female sex immediately, one at the age of 19 months. Except in one girl demonstrating some tomboyish behaviour, gender role behaviour in these patients did not differ from unaffected girls. Ten patients were diagnosed late at 3.4--7 years of age. In seven patients with a late diagnosis, male sex assignment was maintained; one of them expressed some concerns about living as a male. In three patients late sex reversal was performed, gender identity is very poor in one and new sex assignment is currently under consideration. (2) SURGERY: irrespective of the sex assigned, all patients had between one and three surgical procedures, including clitoris reduction and (repeated) vaginoplasties in patients with female sex assignment. Hysterectomy and ovarectomy were performed in patients with male sex assignment. (3) Short stature: patients with a late diagnosis of CAH had extremely advanced bone ages of +6.3 to +9.5 years, leading to severely reduced final height of 137 to 150 cm in adult patients. Patients tended to follow height percentiles of genetic females. One pubertal patient was suicidal due to short stature. (4) Central precocious puberty (CPP): prolonged exposition to adrenal androgens led to CPP in one patient. He was treated with GnRH analogues until gonadectomy. Patients with CAH and complete virilization have a high risk of being diagnosed late. There are major problems and uncertainties of the patients' families and the treating physicians concerning gender assignment. Gender identity is disturbed in some patients. In addition, multiple surgical procedures are necessary and short stature as well as central precocious puberty might be important to avoid late sequelae. While some surgical interventions are probably unavoidable, most of these issues could be resolved with an early diagnosis. Thus, especially for these patients, a neonatal screening programme for CAH would be of paramount importance.

Model regulations and plan amendments for multimodal transportation districts

DOT National Transportation Integrated Search

2004-02-01

In 1999, the Florida legislature enabled local governments to establish Multimodal Transportation Districts (MMTD) in their comprehensive plan as a means of promoting a high quality multimodal environment within selected urban areas. The Florida Depa...

The Effects of Multimodal Mobile Communications on Cooperative Team Interactions Executing Distributed Tasks

DTIC Science & Technology

2013-07-01

AFRL-RH-WP-TP-2013-0046 The Effects of Multimodal Mobile Communications on Cooperative Team Interactions Executing Distributed Tasks Gregory...3. DATES COVERED (From - To) 31-07-13 Interim 01 August 2011 – 01 August 2013 4. TITLE AND SUBTITLE The Effects of Multimodal Mobile... multimodal communication capabilities can con- tribute to the effectiveness and efficiency of real-time, task outcome and per- formance. In this paper, we

The Role of Multimodal Analgesia in Spine Surgery.

PubMed

Kurd, Mark F; Kreitz, Tyler; Schroeder, Gregory; Vaccaro, Alexander R

2017-04-01

Optimal postoperative pain control allows for faster recovery, reduced complications, and improved patient satisfaction. Historically, pain management after spine surgery relied heavily on opioid medications. Multimodal regimens were developed to reduce opioid consumption and associated adverse effects. Multimodal approaches used in orthopaedic surgery of the lower extremity, especially joint arthroplasty, have been well described and studies have shown reduced opioid consumption, improved pain and function, and decreased length of stay. A growing body of evidence supports multimodal analgesia in spine surgery. Methods include the use of preemptive analgesia, NSAIDs, the neuromodulatory agents gabapentin and pregabalin, acetaminophen, and extended-action local anesthesia. The development of a standard approach to multimodal analgesia in spine surgery requires extensive assessment of the literature. Because a substantial number of spine surgeries are performed annually, a standardized approach to multimodal analgesia may provide considerable benefits, particularly in the context of the increased emphasis on accountability within the healthcare system.

Increased discriminability of authenticity from multimodal laughter is driven by auditory information.

PubMed

Lavan, Nadine; McGettigan, Carolyn

2017-10-01

We present an investigation of the perception of authenticity in audiovisual laughter, in which we contrast spontaneous and volitional samples and examine the contributions of unimodal affective information to multimodal percepts. In a pilot study, we demonstrate that listeners perceive spontaneous laughs as more authentic than volitional ones, both in unimodal (audio-only, visual-only) and multimodal contexts (audiovisual). In the main experiment, we show that the discriminability of volitional and spontaneous laughter is enhanced for multimodal laughter. Analyses of relationships between affective ratings and the perception of authenticity show that, while both unimodal percepts significantly predict evaluations of audiovisual laughter, it is auditory affective cues that have the greater influence on multimodal percepts. We discuss differences and potential mismatches in emotion signalling through voices and faces, in the context of spontaneous and volitional behaviour, and highlight issues that should be addressed in future studies of dynamic multimodal emotion processing.

Do emergency medical services dispatch nature and severity codes agree with paramedic field findings?

PubMed

Neely, K W; Eldurkar, J A; Drake, M E

2000-02-01

Emergency medical services (EMS) systems increasingly seek to triage patients to alternative EMS resources. Emergency medical services dispatchers may be asked to perform this triage. New protocols may be necessary. Alternatively, existing protocols may be sufficient for this task. For an existing dispatch protocol to be sufficient, it at least must accurately categorize patient condition and severity based on an external standard. To examine the extent to which nature codes (NCs), or patient condition codes, and severity codes (SCs) currently assigned in one urban 911 center agree with paramedic field findings. The null hypothesis was that there is no routine agreement (75%) between dispatcher-assigned NC or SC and paramedic-assigned NC or SC for the same patient using the same protocol. Emergency medical services dispatch nature and severity code data and matching out-of-hospital data were prospectively gathered over six months. Dispatch data included the NC: caller-identified problem, and the SC: dispatcher-assessed severity. Each NC is modified by one of three SCs (1, 3, or 9): 1 is emergent, 3 is urgent, and 9 is neither. Paramedics verified and/or corrected dispatcher-assigned NCs and SCs using the same dispatch protocol. One thousand forty usable cases fell into 33 unique NC/SC combinations. The designation of SC 1 was assigned 275 times, SC 3 was assigned 736 times, and SC 9 was assigned 24 times. The SC was missing five times. The overall NC agreement was 0.70 (95% CI = 0.697 to 0.703). The overall SC agreement was 0.65 (95% CI = 0.645 to 0.655). The NC agreement exceeded 75% for ten (59%) NC/SC combinations. The SC agreement exceeded 75% for five (29%) NC/SC combinations. There was both NC and SC agreement for four (24%) combinations: urgent breathing problems, urgent diabetic problems, urgent falls, and urgent overdoses. The greatest NC/SC disagreement occurred within emergent and urgent traffic crashes. Paramedics adjusted SC toward lower severity 29% of the time and toward higher severity 5.4% of the time. There was no upward SC adjustment for eight (47%) combinations. Certain dispatcher-assigned NC and SC codes and NC/SC combinations achieved the study threshold. Overall agreement failed to achieve the threshold. The lowest SC level was rarely assigned, preventing a meaningful analysis of all severity levels.

Three geographic decomposition approaches in transportation network analysis

DOT National Transportation Integrated Search

1980-03-01

This document describes the results of research into the application of geographic decomposition techniques to practical transportation network problems. Three approaches are described for the solution of the traffic assignment problem. One approach ...

Application of Decomposition to Transportation Network Analysis

DOT National Transportation Integrated Search

1976-10-01

This document reports preliminary results of five potential applications of the decomposition techniques from mathematical programming to transportation network problems. The five application areas are (1) the traffic assignment problem with fixed de...

Feasibility, safety, acceptability, and functional outcomes of playing Nintendo Wii Fit Plus™ for frail elderly: study protocol for a feasibility trial.

PubMed

Gomes, Gisele Cristine Vieira; Bacha, Jéssica Maria Ribeiro; do Socorro Simões, Maria; Lin, Sumika Mori; Viveiro, Larissa Alamino Pereira; Varise, Eliana Maria; Filho, Wilson Jacob; Pompeu, José Eduardo

2017-01-01

Frailty can be defined as a medical syndrome with multiple causes and contributors, characterized by diminished strength and endurance and reduced physiological function that increases the vulnerability to develop functional dependency and/or death. Studies have shown that the most commonly studied exercise protocol for frail older adults is the multimodal training. Interactive video games (IVGs) involve tasks in virtual environments that combine physical and cognitive demands in an attractive and challenging way. The aim of this study will be to evaluate the feasibility, safety, acceptability, and functional outcomes of playing Nintendo Wii Fit Plus TM (NWFP) for frail older adults. The study is a randomized controlled, parallel group, feasibility trial. Participants will be randomly assigned to the experimental group (EG) and control group (CG). The EG will participate in 14 training sessions, each lasting 50 min, twice a week. In each training session, the participants will play five games, with three attempts at each game. The first attempt will be performed with the assistance of a physical therapist to correct the movements and posture of the patients and subsequent attempts will be performed independently. Scores achieved in the games will be recorded. The participants will be evaluated by a blinded physical therapist at three moments: before and after intervention and 30 days after the end of the intervention (follow-up). We will assess the feasibility, acceptability, safety, and clinical outcomes (postural control, gait, cognition, quality of life, mood, and fear of falling). Due to the deficiencies in multiple systems, studies have shown that multimodal interventions including motor-cognitive stimulation can improve the mobility of frail elderly adults. IVGs, among them the NWFP, are considered as a multimodal motor-cognitive intervention that can potentially improve motor and cognitive functions in the frail elderly. However, there is still no evidence in the literature that proves the feasibility, safety, acceptability, and functional outcomes of this intervention in frail elderly individuals. Brazilian Registry of Clinical Trials (RBR-823rst). World Health Organization Trial Registration Data Set (Additional file 1).

Multimodal Trip Planner System final evaluation report.

DOT National Transportation Integrated Search

2011-05-01

This evaluation of the Multimodal Trip Planning System (MMTPS) is the culmination of a multi-year project evaluating the development and deployment of a multimodal trip planner in the Chicagoland area between 2004 and 2010. The report includes an ove...

Accelerated Math®. Primary Mathematics. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2017

2017-01-01

"Accelerated Math®," published by Renaissance Learning, is a software tool that provides practice problems for students in grades K-12 and provides teachers with reports to monitor student progress. "Accelerated Math®" creates individualized student assignments, scores the assignments, and generates reports on student progress.…

(Explain It) x 3

ERIC Educational Resources Information Center

McGuire, Linda

2014-01-01

This article will describe a writing assignment designed for use in a liberal arts college whose mission stresses effective written communication both within and across disciplines. In this assignment, students write three separate solutions to the same mathematics problem: one for a mathematical peer, a second for a contemporary that does not…

Using Portfolio Assignments to Assess Students' Mathematical Thinking

ERIC Educational Resources Information Center

Fukawa-Connelly, Timothy; Buck, Stephen

2010-01-01

Writing in mathematics can improve procedural knowledge and communication skills and may also help students better understand and then remember problems. The majority of mathematics teachers know that they ought to include some writing assignments in their instructional plans, but the challenge of covering the curriculum and the time required to…

Student's Lab Assignments in PDE Course with MAPLE.

ERIC Educational Resources Information Center

Ponidi, B. Alhadi

Computer-aided software has been used intensively in many mathematics courses, especially in computational subjects, to solve initial value and boundary value problems in Partial Differential Equations (PDE). Many software packages were used in student lab assignments such as FORTRAN, PASCAL, MATLAB, MATHEMATICA, and MAPLE in order to accelerate…

Listener Reliability in Assigning Utterance Boundaries in Children's Spontaneous Speech

ERIC Educational Resources Information Center

Stockman, Ida J.

2010-01-01

Research and clinical practices often rely on an utterance unit for spoken language analysis. This paper calls attention to the problems encountered when identifying utterance boundaries in young children's spontaneous conversational speech. The results of a reliability study of utterance boundary assignment are described for 20 females with…

Distributed Collaborative Homework Activities in a Problem-Based Usability Engineering Course

ERIC Educational Resources Information Center

Carroll, John M.; Jiang, Hao; Borge, Marcela

2015-01-01

Teams of students in an upper-division undergraduate Usability Engineering course used a collaborative environment to carry out a series of three distributed collaborative homework assignments. Assignments were case-based analyses structured using a jigsaw design; students were provided a collaborative software environment and introduced to a…

Increasing Student-Learning Team Effectiveness with Team Charters

ERIC Educational Resources Information Center

Hunsaker, Phillip; Pavett, Cynthia; Hunsaker, Johanna

2011-01-01

Because teams are a ubiquitous part of most organizations today, it is common for business educators to use team assignments to help students experientially learn about course concepts and team process. Unfortunately, students frequently experience a number of problems during team assignments. The authors describe the results of their research and…

Teaching Case: A Systems Analysis Role-Play Exercise and Assignment

ERIC Educational Resources Information Center

Mitri, Michel; Cole, Carey; Atkins, Laura

2017-01-01

This paper presents a role-play exercise and assignment that provides an active learning experience related to the system investigation phase of an SDLC. Whether using waterfall or agile approaches, the first SDLC step usually involves system investigation activities, including problem identification, feasibility study, cost-benefit analysis, and…

Assessing Homework Problems in Children with ADHD: Validation of a Parent-Report Measure and Evaluation of Homework Performance Patterns.

PubMed

Langberg, Joshua M; Arnold, L Eugene; Flowers, Amanda M; Altaye, Mekibib; Epstein, Jeff N; Molina, Brooke S G

2010-03-01

The factor structure of a parent-report measure of child homework problems, the Homework Problems Checklist, was examined in a geographically and ethnically diverse sample of children with Attention-Deficit/Hyperactivity Disorder (ADHD). This measure was completed by the parents of 579 children ages 7.0-9.9 diagnosed with ADHD Combined Type as part of the Multimodal Treatment Study of Children with ADHD (MTA). Results replicated previous work showing two salient factors that measure homework completion behaviors (Factor I) and homework management behaviors (Factor II). This two-factor solution remained consistent when examined across child sex and ethnicity subgroups. Analysis of patterns revealed that homework problems are greater for children in higher grades and that children with ADHD and comorbid Learning Disabilities experience significantly more homework problems than children with ADHD alone. This study also replicated previous work showing that homework problems and ADHD inattentive symptoms are highly correlated whereas correlations between homework problems and hyperactivity and impulsivity are low to moderate. Implications of the findings for the assessment of homework problems in children with ADHD and for intervention are discussed.

Assessing Homework Problems in Children with ADHD: Validation of a Parent-Report Measure and Evaluation of Homework Performance Patterns

PubMed Central

Langberg, Joshua M.; Arnold, L. Eugene; Flowers, Amanda M.; Altaye, Mekibib; Epstein, Jeff N.; Molina, Brooke S.G.

2011-01-01

The factor structure of a parent-report measure of child homework problems, the Homework Problems Checklist, was examined in a geographically and ethnically diverse sample of children with Attention-Deficit/Hyperactivity Disorder (ADHD). This measure was completed by the parents of 579 children ages 7.0-9.9 diagnosed with ADHD Combined Type as part of the Multimodal Treatment Study of Children with ADHD (MTA). Results replicated previous work showing two salient factors that measure homework completion behaviors (Factor I) and homework management behaviors (Factor II). This two-factor solution remained consistent when examined across child sex and ethnicity subgroups. Analysis of patterns revealed that homework problems are greater for children in higher grades and that children with ADHD and comorbid Learning Disabilities experience significantly more homework problems than children with ADHD alone. This study also replicated previous work showing that homework problems and ADHD inattentive symptoms are highly correlated whereas correlations between homework problems and hyperactivity and impulsivity are low to moderate. Implications of the findings for the assessment of homework problems in children with ADHD and for intervention are discussed. PMID:21544228

Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems.

PubMed

Snelick, Robert; Uludag, Umut; Mink, Alan; Indovina, Michael; Jain, Anil

2005-03-01

We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. The majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.

A Framework and Toolkit for the Construction of Multimodal Learning Interfaces

DTIC Science & Technology

1998-04-29

human communication modalities in the context of a broad class of applications, specifically those that support state manipulation via parameterized actions. The multimodal semantic model is also the basis for a flexible, domain independent, incrementally trainable multimodal interpretation algorithm based on a connectionist network. The second major contribution is an application framework consisting of reusable components and a modular, distributed system architecture. Multimodal application developers can assemble the components in the framework into a new application,

38 CFR 21.198 - “Discontinued” status.

Code of Federal Regulations, 2011 CFR

2011-07-01

... personal or other problems; or (ii) Inability of the veteran to benefit from rehabilitation services... of entitlement. (4) Medical and related problems. A veteran's case will be discontinued and assigned... program because of a serious physical or emotional problem for an extended period; and (ii) VA medical...

38 CFR 21.198 - “Discontinued” status.

Code of Federal Regulations, 2010 CFR

2010-07-01

... personal or other problems; or (ii) Inability of the veteran to benefit from rehabilitation services... of entitlement. (4) Medical and related problems. A veteran's case will be discontinued and assigned... program because of a serious physical or emotional problem for an extended period; and (ii) VA medical...

Separation anxiety among birth-assigned male children in a specialty gender identity service.

PubMed

VanderLaan, Doug P; Santarossa, Alanna; Nabbijohn, A Natisha; Wood, Hayley; Owen-Anderson, Allison; Zucker, Kenneth J

2018-01-01

Previous research suggested that separation anxiety disorder (SAD) is overrepresented among birth-assigned male children clinic-referred for gender dysphoria (GD). The present study examined maternally reported separation anxiety of birth-assigned male children assessed in a specialty gender identity service (N = 360). SAD was determined in relation to DSM-III and DSM-IV criteria, respectively. A dimensional metric of separation anxiety was examined in relation to several additional factors: age, ethnicity, parental marital status and social class, IQ, gender nonconformity, behavioral and emotional problems, and poor peer relations. When defined in a liberal fashion, 55.8% were classified as having SAD. When using a more conservative criterion, 5.3% were classified as having SAD, which was significantly greater than the estimated general population prevalence for boys, but not for girls. Dimensionally, separation anxiety was associated with having parents who were not married or cohabitating as well as with elevations in gender nonconformity; however, the association with gender nonconformity was no longer significant when statistically controlling for internalizing problems. Thus, SAD appears to be common among birth-assigned males clinic-referred for GD when defined in a liberal fashion, and more common than in boys, but not girls, from the general population even when more stringent criteria were applied. Also, the degree of separation anxiety appears to be linked to generic risk factors (i.e., parental marital status, internalizing problems). As such, although separation anxiety is common among birth-assigned male children clinic-referred for GD, it seems unlikely to hold unique significance for this population based on the current data.

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis.

PubMed

Cui, Licong; Xu, Rong; Luo, Zhihui; Wentz, Susan; Scarberry, Kyle; Zhang, Guo-Qiang

2014-08-03

Finding quality consumer health information online can effectively bring important public health benefits to the general population. It can empower people with timely and current knowledge for managing their health and promoting wellbeing. Despite a popular belief that search engines such as Google can solve all information access problems, recent studies show that using search engines and simple search terms is not sufficient. Our objective is to provide an approach to organizing consumer health information for navigational exploration, complementing keyword-based direct search. Multi-topic assignment to health information, such as online questions, is a fundamental step for navigational exploration. We introduce a new multi-topic assignment method combining semantic annotation using UMLS concepts (CUIs) and Formal Concept Analysis (FCA). Each question was tagged with CUIs identified by MetaMap. The CUIs were filtered with term-frequency and a new term-strength index to construct a CUI-question context. The CUI-question context and a topic-subject context were used for multi-topic assignment, resulting in a topic-question context. The topic-question context was then directly used for constructing a prototype navigational exploration interface. Experimental evaluation was performed on the task of automatic multi-topic assignment of 99 predefined topics for about 60,000 consumer health questions from NetWellness. Using example-based metrics, suitable for multi-topic assignment problems, our method achieved a precision of 0.849, recall of 0.774, and F₁ measure of 0.782, using a reference standard of 278 questions with manually assigned topics. Compared to NetWellness' original topic assignment, a 36.5% increase in recall is achieved with virtually no sacrifice in precision. Enhancing the recall of multi-topic assignment without sacrificing precision is a prerequisite for achieving the benefits of navigational exploration. Our new multi-topic assignment method, combining term-strength, FCA, and information retrieval techniques, significantly improved recall and performed well according to example-based metrics.

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis

PubMed Central

2014-01-01

Background Finding quality consumer health information online can effectively bring important public health benefits to the general population. It can empower people with timely and current knowledge for managing their health and promoting wellbeing. Despite a popular belief that search engines such as Google can solve all information access problems, recent studies show that using search engines and simple search terms is not sufficient. Our objective is to provide an approach to organizing consumer health information for navigational exploration, complementing keyword-based direct search. Multi-topic assignment to health information, such as online questions, is a fundamental step for navigational exploration. Methods We introduce a new multi-topic assignment method combining semantic annotation using UMLS concepts (CUIs) and Formal Concept Analysis (FCA). Each question was tagged with CUIs identified by MetaMap. The CUIs were filtered with term-frequency and a new term-strength index to construct a CUI-question context. The CUI-question context and a topic-subject context were used for multi-topic assignment, resulting in a topic-question context. The topic-question context was then directly used for constructing a prototype navigational exploration interface. Results Experimental evaluation was performed on the task of automatic multi-topic assignment of 99 predefined topics for about 60,000 consumer health questions from NetWellness. Using example-based metrics, suitable for multi-topic assignment problems, our method achieved a precision of 0.849, recall of 0.774, and F1 measure of 0.782, using a reference standard of 278 questions with manually assigned topics. Compared to NetWellness’ original topic assignment, a 36.5% increase in recall is achieved with virtually no sacrifice in precision. Conclusion Enhancing the recall of multi-topic assignment without sacrificing precision is a prerequisite for achieving the benefits of navigational exploration. Our new multi-topic assignment method, combining term-strength, FCA, and information retrieval techniques, significantly improved recall and performed well according to example-based metrics. PMID:25086916

Examining the Preparatory Effects of Problem Generation and Solution Generation on Learning from Instruction

ERIC Educational Resources Information Center

Kapur, Manu

2018-01-01

The goal of this paper is to isolate the preparatory effects of problem-generation from solution generation in problem-posing contexts, and their underlying mechanisms on learning from instruction. Using a randomized-controlled design, students were assigned to one of two conditions: (a) problem-posing with solution generation, where they…

Introduction of a Population Balance Based Design Problem in a Particle Science and Technology Course for Chemical Engineers

ERIC Educational Resources Information Center

Ehrman, Sheryl H.; Castellanos, Patricia; Dwivedi, Vivek; Diemer, R. Bertrum

2007-01-01

A particle technology design problem incorporating population balance modeling was developed and assigned to senior and first-year graduate students in a Particle Science and Technology course. The problem focused on particle collection, with a pipeline agglomerator, Cyclone, and baghouse comprising the collection system. The problem was developed…

Investigating the Effect of Complexity Factors in Stoichiometry Problems Using Logistic Regression and Eye Tracking

ERIC Educational Resources Information Center

Tang, Hui; Kirk, John; Pienta, Norbert J.

2014-01-01

This paper includes two experiments, one investigating complexity factors in stoichiometry word problems, and the other identifying students' problem-solving protocols by using eye-tracking technology. The word problems used in this study had five different complexity factors, which were randomly assigned by a Web-based tool that we developed. The…

Exploiting Elementary Landscapes for TSP, Vehicle Routing and Scheduling

DTIC Science & Technology

2015-09-03

Traveling Salesman Problem (TSP) and Graph Coloring are elementary. Problems such as MAX-kSAT are a superposition of k elementary landscapes. This...search space. Problems such as the Traveling Salesman Problem (TSP), Graph Coloring, the Frequency Assignment Problem , as well as Min-Cut and Max-Cut...echoing our earlier esults on the Traveling Salesman Problem . Using two locally optimal solutions as “parent” solutions, we have developed a

Capacity-constrained traffic assignment in networks with residual queues

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

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

A Markov Random Field Framework for Protein Side-Chain Resonance Assignment

NASA Astrophysics Data System (ADS)

Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall

Nuclear magnetic resonance (NMR) spectroscopy plays a critical role in structural genomics, and serves as a primary tool for determining protein structures, dynamics and interactions in physiologically-relevant solution conditions. The current speed of protein structure determination via NMR is limited by the lengthy time required in resonance assignment, which maps spectral peaks to specific atoms and residues in the primary sequence. Although numerous algorithms have been developed to address the backbone resonance assignment problem [68,2,10,37,14,64,1,31,60], little work has been done to automate side-chain resonance assignment [43, 48, 5]. Most previous attempts in assigning side-chain resonances depend on a set of NMR experiments that record through-bond interactions with side-chain protons for each residue. Unfortunately, these NMR experiments have low sensitivity and limited performance on large proteins, which makes it difficult to obtain enough side-chain resonance assignments. On the other hand, it is essential to obtain almost all of the side-chain resonance assignments as a prerequisite for high-resolution structure determination. To overcome this deficiency, we present a novel side-chain resonance assignment algorithm based on alternative NMR experiments measuring through-space interactions between protons in the protein, which also provide crucial distance restraints and are normally required in high-resolution structure determination. We cast the side-chain resonance assignment problem into a Markov Random Field (MRF) framework, and extend and apply combinatorial protein design algorithms to compute the optimal solution that best interprets the NMR data. Our MRF framework captures the contact map information of the protein derived from NMR spectra, and exploits the structural information available from the backbone conformations determined by orientational restraints and a set of discretized side-chain conformations (i.e., rotamers). A Hausdorff-based computation is employed in the scoring function to evaluate the probability of side-chain resonance assignments to generate the observed NMR spectra. The complexity of the assignment problem is first reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is used to find a set of optimal side-chain resonance assignments that best fit the NMR data. We have tested our algorithm on NMR data for five proteins, including the FF Domain 2 of human transcription elongation factor CA150 (FF2), the B1 domain of Protein G (GB1), human ubiquitin, the ubiquitin-binding zinc finger domain of the human Y-family DNA polymerase Eta (pol η UBZ), and the human Set2-Rpb1 interacting domain (hSRI). Our algorithm assigns resonances for more than 90% of the protons in the proteins, and achieves about 80% correct side-chain resonance assignments. The final structures computed using distance restraints resulting from the set of assigned side-chain resonances have backbone RMSD 0.5 - 1.4 Å and all-heavy-atom RMSD 1.0 - 2.2 Å from the reference structures that were determined by X-ray crystallography or traditional NMR approaches. These results demonstrate that our algorithm can be successfully applied to automate side-chain resonance assignment and high-quality protein structure determination. Since our algorithm does not require any specific NMR experiments for measuring the through-bond interactions with side-chain protons, it can save a significant amount of both experimental cost and spectrometer time, and hence accelerate the NMR structure determination process.

How did you guess? Or, what do multiple-choice questions measure?

PubMed

Cox, K R

1976-06-05

Multiple-choice questions classified as requiring problem-solving skills have been interpreted as measuring problem-solving skills within students, with the implicit hypothesis that questions needing an increasingly complex intellectual process should present increasing difficulty to the student. This hypothesis was tested in a 150-question paper taken by 721 students in seven Australian medical schools. No correlation was observed between difficulty and assigned process. Consequently, the question-answering process was explored with a group of final-year students. Anecdotal recall by students gave heavy weight to knowledge rather than problem solving in answering these questions. Assignment of the 150 questions to the classification by three teachers and six students showed their congruence to be a little above random probability.

Multimodal approaches for emotion recognition: a survey

NASA Astrophysics Data System (ADS)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2004-12-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

'Full dose' reirradiation of human cervical spinal cord.

PubMed

Ryu, S; Gorty, S; Kazee, A M; Bogart, J; Hahn, S S; Dalal, P S; Chung, C T; Sagerman, R H

2000-02-01

With the progress of modern multimodality cancer treatment, retreatment of late recurrences or second tumors became more commonly encountered in management of patients with cancer. Spinal cord retreatment with radiation is a common problem in this regard. Because radiation myelopathy may result in functional deficits, many oncologists are concerned about radiation-induced myelopathy when retreating tumors located within or immediately adjacent to the previous radiation portal. The treatment decision is complicated because it requires a pertinent assessment of prognostic factors with and without reirradiation, radiobiologic estimation of recovery of occult spinal cord damage from the previous treatment, as well as interactions because of multimodality treatment. Recent studies regarding reirradiation of spinal cord in animals using limb paralysis as an endpoint have shown substantial and almost complete recovery of spinal cord injury after a sufficient time after the initial radiotherapy. We report a case of "full" dose reirradiation of the entire cervical spinal cord in a patient who has not developed clinically detectable radiation-induced myelopathy on long-term follow-up of 17 years after the first radiotherapy and 5 years after the second radiotherapy.

Brain-computer interaction research at the Computer Vision and Multimedia Laboratory, University of Geneva.

PubMed

Pun, Thierry; Alecu, Teodor Iulian; Chanel, Guillaume; Kronegg, Julien; Voloshynovskiy, Sviatoslav

2006-06-01

This paper describes the work being conducted in the domain of brain-computer interaction (BCI) at the Multimodal Interaction Group, Computer Vision and Multimedia Laboratory, University of Geneva, Geneva, Switzerland. The application focus of this work is on multimodal interaction rather than on rehabilitation, that is how to augment classical interaction by means of physiological measurements. Three main research topics are addressed. The first one concerns the more general problem of brain source activity recognition from EEGs. In contrast with classical deterministic approaches, we studied iterative robust stochastic based reconstruction procedures modeling source and noise statistics, to overcome known limitations of current techniques. We also developed procedures for optimal electroencephalogram (EEG) sensor system design in terms of placement and number of electrodes. The second topic is the study of BCI protocols and performance from an information-theoretic point of view. Various information rate measurements have been compared for assessing BCI abilities. The third research topic concerns the use of EEG and other physiological signals for assessing a user's emotional status.

Stereo vision tracking of multiple objects in complex indoor environments.

PubMed

Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro

2010-01-01

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Transmission of multiplexed video signals in multimode optical fiber systems

NASA Technical Reports Server (NTRS)

White, Preston, III

1988-01-01

Kennedy Space Center has the need for economical transmission of two multiplexed video signals along multimode fiberoptic systems. These systems must span unusual distances and must meet RS-250B short-haul standards after reception. Bandwidth is a major problem and studies of the installed fibers, available LEDs and PINFETs led to the choice of 100 MHz as the upper limit for the system bandwidth. Optical multiplexing and digital transmission were deemed inappropriate. Three electrical multiplexing schemes were chosen for further study. Each of the multiplexing schemes included an FM stage to help meet the stringent S/N specification. Both FM and AM frequency division multiplexing methods were investigated theoretically and these results were validated with laboratory tests. The novel application of quadrature amplitude multiplexing was also considered. Frequency division multiplexing of two wideband FM video signal appears the most promising scheme although this application requires high power highly linear LED transmitters. Futher studies are necessary to determine if LEDs of appropriate quality exist and to better quantify performance of QAM in this application.

Real-time multi-mode neutron multiplicity counter

DOEpatents

Rowland, Mark S; Alvarez, Raymond A

2013-02-26

Embodiments are directed to a digital data acquisition method that collects data regarding nuclear fission at high rates and performs real-time preprocessing of large volumes of data into directly useable forms for use in a system that performs non-destructive assaying of nuclear material and assemblies for mass and multiplication of special nuclear material (SNM). Pulses from a multi-detector array are fed in parallel to individual inputs that are tied to individual bits in a digital word. Data is collected by loading a word at the individual bit level in parallel, to reduce the latency associated with current shift-register systems. The word is read at regular intervals, all bits simultaneously, with no manipulation. The word is passed to a number of storage locations for subsequent processing, thereby removing the front-end problem of pulse pileup. The word is used simultaneously in several internal processing schemes that assemble the data in a number of more directly useable forms. The detector includes a multi-mode counter that executes a number of different count algorithms in parallel to determine different attributes of the count data.

A Context-Aware-Based Audio Guidance System for Blind People Using a Multimodal Profile Model

PubMed Central

Lin, Qing; Han, Youngjoon

2014-01-01

A wearable guidance system is designed to provide context-dependent guidance messages to blind people while they traverse local pathways. The system is composed of three parts: moving scene analysis, walking context estimation and audio message delivery. The combination of a downward-pointing laser scanner and a camera is used to solve the challenging problem of moving scene analysis. By integrating laser data profiles and image edge profiles, a multimodal profile model is constructed to estimate jointly the ground plane, object locations and object types, by using a Bayesian network. The outputs of the moving scene analysis are further employed to estimate the walking context, which is defined as a fuzzy safety level that is inferred through a fuzzy logic model. Depending on the estimated walking context, the audio messages that best suit the current context are delivered to the user in a flexible manner. The proposed system is tested under various local pathway scenes, and the results confirm its efficiency in assisting blind people to attain autonomous mobility. PMID:25302812

Multimodal approaches for emotion recognition: a survey

NASA Astrophysics Data System (ADS)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2005-01-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

Dynamics and control of a multimode laser: Reduction of space-dependent rate equations to a low-dimensional system.

PubMed

Pyragas, K; Lange, F; Letz, T; Parisi, J; Kittel, A

2001-01-01

We suggest a quantitatively correct procedure for reducing the spatial degrees of freedom of the space-dependent rate equations of a multimode laser that describe the dynamics of the population inversion of the active medium and the mode intensities of the standing waves in the laser cavity. The key idea of that reduction is to take advantage of the small value of the parameter that defines the ratio between the population inversion decay rate and the cavity decay rate. We generalize the reduction procedure for the case of an intracavity frequency doubled laser. Frequency conversion performed by an optically nonlinear crystal placed inside the laser cavity may cause a pronounced instability in the laser performance, leading to chaotic oscillations of the output intensity. Based on the reduced equations, we analyze the dynamical properties of the system as well as the problem of stabilizing the steady state. The numerical analysis is performed considering the specific system of a Nd:YAG (neodymium-doped yttrium aluminum garnet) laser with an intracavity KTP (potassium titanyl phosphate) crystal.

Development and implementation of an integrated, multi-modality, user-centered interactive dietary change program

PubMed Central

Glasgow, Russell E.; Christiansen, Steve; Smith, K. Sabina; Stevens, Victor J.; Toobert, Deborah J.

2009-01-01

Computer-tailored behavior change programs offer the potential for reaching large populations at a much lower cost than individual or group-based programs. However, few of these programs to date appear to integrate behavioral theory with user choice, or combine different electronic modalities. We describe the development of an integrated CD-ROM and interactive voice response dietary change intervention that combines behavioral problem-solving theory with a high degree of user choice. The program, WISE CHOICES, is being evaluated as part of an ongoing trial. This paper describes the program development, emphasizing how user preferences are accommodated, and presents implementation and user satisfaction data. The program was successfully implemented; the linkages among the central database, the CD-ROM and the automated telephone components were robust, and participants liked the program almost as well as a counselor-delivered dietary change condition. Multi-modality programs that emphasize the strengths of each approach appear to be feasible. Future research is needed to determine the program impact and cost-effectiveness compared with counselor-delivered intervention. PMID:18711204

Missing Modality Transfer Learning via Latent Low-Rank Constraint.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2015-11-01

Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.

Fiber Optic Temperature Sensor Based on Multimode Interference Effects

NASA Astrophysics Data System (ADS)

Aguilar-Soto, J. G.; Antonio-Lopez, J. E.; Sanchez-Mondragon, J. J.; May-Arrioja, D. A.

2011-01-01

A novel fiber optic temperature sensor based on multimode interference was designed, fabricated and tested. The sensor is very simple and inexpensive since we only need to splice a section of multimode fiber between two single mode fibers. Using this device a sensing range of 25°C to 375°C is demonstrated. We should also highlight that due to the pass-band filter response of MMI devices, multiplexing is rather simple by just changing the length of the multimode section.

Quantum key distribution over an installed multimode optical fiber local area network.

PubMed

Namekata, Naoto; Mori, Shigehiko; Inoue, Shuichiro

2005-12-12

We have investigated the possibility of a multimode fiber link for a quantum channel. Transmission of light in an extremely underfilled mode distribution promises a single-mode-like behavior in the multimode fiber. To demonstrate the performance of the fiber link we performed quantum key distribution, on the basis of the BB84 four-state protocol, over 550 m of an installed multimode optical fiber local area network, and the quantum-bit-error rate of 1.09 percent was achieved.

Integrated optimization of location assignment and sequencing in multi-shuttle automated storage and retrieval systems under modified 2n-command cycle pattern

NASA Astrophysics Data System (ADS)

Yang, Peng; Peng, Yongfei; Ye, Bin; Miao, Lixin

2017-09-01

This article explores the integrated optimization problem of location assignment and sequencing in multi-shuttle automated storage/retrieval systems under the modified 2n-command cycle pattern. The decision of storage and retrieval (S/R) location assignment and S/R request sequencing are jointly considered. An integer quadratic programming model is formulated to describe this integrated optimization problem. The optimal travel cycles for multi-shuttle S/R machines can be obtained to process S/R requests in the storage and retrieval request order lists by solving the model. The small-sized instances are optimally solved using CPLEX. For large-sized problems, two tabu search algorithms are proposed, in which the first come, first served and nearest neighbour are used to generate initial solutions. Various numerical experiments are conducted to examine the heuristics' performance and the sensitivity of algorithm parameters. Furthermore, the experimental results are analysed from the viewpoint of practical application, and a parameter list for applying the proposed heuristics is recommended under different real-life scenarios.

Using Latent Class Analysis to Model Temperament Types.

PubMed

Loken, Eric

2004-10-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.

Adhesion of multimode adhesives to enamel and dentin after one year of water storage.

PubMed

Vermelho, Paulo Moreira; Reis, André Figueiredo; Ambrosano, Glaucia Maria Bovi; Giannini, Marcelo

2017-06-01

This study aimed to evaluate the ultramorphological characteristics of tooth-resin interfaces and the bond strength (BS) of multimode adhesive systems to enamel and dentin. Multimode adhesives (Scotchbond Universal (SBU) and All-Bond Universal) were tested in both self-etch and etch-and-rinse modes and compared to control groups (Optibond FL and Clearfil SE Bond (CSB)). Adhesives were applied to human molars and composite blocks were incrementally built up. Teeth were sectioned to obtain specimens for microtensile BS and TEM analysis. Specimens were tested after storage for either 24 h or 1 year. SEM analyses were performed to classify the failure pattern of beam specimens after BS testing. Etching increased the enamel BS of multimode adhesives; however, BS decreased after storage for 1 year. No significant differences in dentin BS were noted between multimode and control in either evaluation period. Storage for 1 year only reduced the dentin BS for SBU in self-etch mode. TEM analysis identified hybridization and interaction zones in dentin and enamel for all adhesives. Silver impregnation was detected on dentin-resin interfaces after storage of specimens for 1 year only with the SBU and CSB. Storage for 1 year reduced enamel BS when adhesives are applied on etched surface; however, BS of multimode adhesives did not differ from those of the control group. In dentin, no significant difference was noted between the multimode and control group adhesives, regardless of etching mode. In general, multimode adhesives showed similar behavior when compared to traditional adhesive techniques. Multimode adhesives are one-step self-etching adhesives that can also be used after enamel/dentin phosphoric acid etching, but each product may work better in specific conditions.

Multi-mode of Four and Six Wave Parametric Amplified Process

NASA Astrophysics Data System (ADS)

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-01

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Multi-mode of Four and Six Wave Parametric Amplified Process.

PubMed

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-03

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Multimodal Career Counseling: An Application of the "BASIC ID."

ERIC Educational Resources Information Center

Smith, Robert L.; Southern, Stephen

1980-01-01

The multimodal career counseling model is a logical extension of Lazarus' multimodal behavior therapy through the assessment of seven modalities that affect the career of the individual. Interventions may be directed at the early decision-making stage or when difficulties are encountered. (Author)

Critical Visual Literacy: Multimodal Communication across the Curriculum

ERIC Educational Resources Information Center

Duffelmeyer, Barb Blakely; Ellertson, Anthony

2005-01-01

"Critical Visual Literacy: Multimodal Communication Across the Curriculum" makes the case for expanding the pedagogical space and communication possibilities in undergraduate communication-intensive and linked (learning community) courses by allowing students to create multimodal texts that deal with civic and cultural and/or discipline…

Multimodal Narrative Inquiry: Six Teacher Candidates Respond

ERIC Educational Resources Information Center

Morawski, Cynthia M.; Rottmann, Jennifer

2016-01-01

In this paper we present findings of a study on the implementation of a multimodal teacher narrative inquiry component, theoretically grounded by Rosenblatt's theory of transaction analysis, methodologically supported by action research and practically enacted by narrative inquiry and multimodal learning. In particular, the component offered…

New methods of multimode fiber interferometer signal processing

NASA Astrophysics Data System (ADS)

Vitrik, Oleg B.; Kulchin, Yuri N.; Maxaev, Oleg G.; Kirichenko, Oleg V.; Kamenev, Oleg T.; Petrov, Yuri S.

1995-06-01

New methods of multimode fiber interferometers signal processing are suggested. For scheme of single fiber multimode interferometers with two excited modes, the method based on using of special fiber unit is developed. This unit provides the modes interaction and further sum optical field filtering. As a result the amplitude of output signal is modulated by external influence on interferometer. The stabilization of interferometer sensitivity is achieved by using additional special modulation of output signal. For scheme of single fiber multimode interferometers with excitation of wide mode spectrum, the signal of intermode interference is registered by photodiode matrix and then special electronic unit performs correlation processing. For elimination of temperature destabilization, the registered signal is adopted to multimode interferometers optical signal temperature changes. The achieved parameters for double mode scheme: temporary stability--0.6% per hour, sensitivity to interferometer length deviations--3,2 nm; for multimode scheme: temperature stability--(0.5%)/(K), temporary nonstability--0.2% per hour, sensitivity to interferometer length deviations--20 nm, dynamic range--35 dB.