Multimodal approach to the international transit transport

Directory of Open Access Journals (Sweden)

D. Bazaras

2003-12-01

Full Text Available In the article not only the problems of multi-modal and inter-modal conveyances in Lithuania and the concept of transit and the transit system stimulating factors are analysed, but also the modelling of transit transport and the flows of the loads are given. The main part of the article comes to the analysis of resent situation of Lithuania. In this part the place of transport sector in the market of transit services is analysed and the transit profit for Lithuanian economy is evaluated. The conclusions and proposals are given at the end of the article.

A multimodal spectral approach to characterize rhythm in natural speech.

Science.gov (United States)

Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta

2016-01-01

Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.

Content-based TV sports video retrieval using multimodal analysis

Science.gov (United States)

Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

2003-09-01

In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

Learning multimodal dictionaries.

Science.gov (United States)

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.

Double-Wavelet Approach to Studying the Modulation Properties of Nonstationary Multimode Dynamics

DEFF Research Database (Denmark)

Sosnovtseva, Olga; Mosekilde, Erik; Pavlov, A.N.

2005-01-01

On the basis of double-wavelet analysis, the paper proposes a method to study interactions in the form of frequency and amplitude modulation in nonstationary multimode data series. Special emphasis is given to the problem of quantifying the strength of modulation for a fast signal by a coexisting...

A Learning Algorithm for Multimodal Grammar Inference.

Science.gov (United States)

D'Ulizia, A; Ferri, F; Grifoni, P

2011-12-01

The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.

Multimodal biometric approach for cancelable face template generation

Science.gov (United States)

Paul, Padma Polash; Gavrilova, Marina

2012-06-01

Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.

A robust probabilistic collaborative representation based classification for multimodal biometrics

Science.gov (United States)

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 multimodal parallel architecture: A cognitive framework for multimodal interactions.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: A dynamic forward approach

Directory of Open Access Journals (Sweden)

Aidin Delgoshaei

2016-09-01

Full Text Available Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.

Bidirectional Joint Representation Learning with Symmetrical Deep Neural Networks for Multimodal and Crossmodal Applications

OpenAIRE

Vukotic , Vedran; Raymond , Christian; Gravier , Guillaume

2016-01-01

International audience; Common approaches to problems involving multiple modalities (classification, retrieval, hyperlinking, etc.) are early fusion of the initial modalities and crossmodal translation from one modality to the other. Recently, deep neural networks, especially deep autoencoders, have proven promising both for crossmodal translation and for early fusion via multimodal embedding. In this work, we propose a flexible cross-modal deep neural network architecture for multimodal and ...

Multimodal Landscaping in Higher Education Research

DEFF Research Database (Denmark)

Lueg, Klarissa

2018-01-01

The purpose of this paper is to introduce Multimodal Landscaping (ML) as a conceptual framework, and to illustrate how this approach can be applied within the field of higher education research. It is argued that ML is a suitable tool, especially, in studies investigating university...... internationalization, and in studies focusing on the agent level of higher education organizations. ML is argued to add to the diversity of methods within a social constructivist methodology. The author illustrates how ML is connected and/or different from kindred approaches. Pathways are proposed as to how...

The Effects of Using Multimodal Approaches in Meaning-Making of 21st Century Literacy Texts Among ESL Students in a Private School in Malaysia

Directory of Open Access Journals (Sweden)

Malini Ganapathy

2016-04-01

Full Text Available In today’s globalised digital era, students are inevitably engaged in various multimodal texts due to their active participation in social media and frequent usage of mobile devices on a daily basis. Such daily activities advocate the need for a transformation in the teaching and learning of ESL lessons in order to promote students’ capabilities in making meaning of different literacy texts which students come across in their ESL learning activities. This paper puts forth the framework of Multimodality in the restructuring of the teaching and learning of ESL with the aim of investigating its effects and students perspectives on the use of multimodal approaches underlying the Multiliteracies theory. Using focus group interviews, this qualitative case study examines the effectiveness of ESL teaching and learning using the Multimodal approaches on literacy in meaning-making among 15 students in a private school in Penang, Malaysia. The results confirm the need to reorientate the teaching and learning of ESL with the focus on multimodal pedagogical practices as it promotes positive learning outcomes among students. The implications of this study suggest that the multimodal approaches integrated in the teaching and learning of ESL have the capacity to promote students’ autonomy in learning, improve motivation to learn and facilitate various learning styles. Keywords: Multimodal Approaches; Multiliteracies; Monomodal; Flipped Classroom; Literacy; Multimodal texts; Ipad

A multi-modal approach to assessing recovery in youth athletes following concussion.

Science.gov (United States)

Reed, Nick; Murphy, James; Dick, Talia; Mah, Katie; Paniccia, Melissa; Verweel, Lee; Dobney, Danielle; Keightley, Michelle

2014-09-25

Concussion is one of the most commonly reported injuries amongst children and youth involved in sport participation. Following a concussion, youth can experience a range of short and long term neurobehavioral symptoms (somatic, cognitive and emotional/behavioral) that can have a significant impact on one's participation in daily activities and pursuits of interest (e.g., school, sports, work, family/social life, etc.). Despite this, there remains a paucity in clinically driven research aimed specifically at exploring concussion within the youth sport population, and more specifically, multi-modal approaches to measuring recovery. This article provides an overview of a novel and multi-modal approach to measuring recovery amongst youth athletes following concussion. The presented approach involves the use of both pre-injury/baseline testing and post-injury/follow-up testing to assess performance across a wide variety of domains (post-concussion symptoms, cognition, balance, strength, agility/motor skills and resting state heart rate variability). The goal of this research is to gain a more objective and accurate understanding of recovery following concussion in youth athletes (ages 10-18 years). Findings from this research can help to inform the development and use of improved approaches to concussion management and rehabilitation specific to the youth sport community.

Video genre classification using multimodal features

Science.gov (United States)

Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

2003-12-01

We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

A Multimodal Search Engine for Medical Imaging Studies.

Science.gov (United States)

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.

Robust Multimodal Dictionary Learning

Science.gov (United States)

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 optimization for multi-modal transportation routing planning problem based on Pareto optimality

Directory of Open Access Journals (Sweden)

Yan Sun

2015-09-01

Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

KAUST Repository

Elsheikh, Ahmed H.

2013-05-01

A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.

Framework for Developing a Multimodal Programming Interface Used on Industrial Robots

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Bogdan Mocan

2014-12-01

Full Text Available The proposed approach within this paper shifts the focus from the coordinate based programming of an industrial robot, which currently dominates the field, to an object based programming scheme. The general framework proposed in this paper is designed to perform natural language understanding, gesture integration and semantic analysis which facilitate the development of a multimodal robot programming interface that facilitate an intuitive programming.

Metal complex-based templates and nanostructures for magnetic resonance/optical multimodal imaging agents

NARCIS (Netherlands)

Galindo Millan, Jealemy

2012-01-01

In this thesis, new approaches directed towards simple and functional imaging agents (IAs) for magnetic resonance (MR) and fluorescence multimodal imaging are proposed. In Chapter 3, hybrid silver nanostructures (hAgNSs), grown using a polyamino carboxylic acid scaffold, namely

Adaptive multimodal interaction in mobile augmented reality: A conceptual framework

Science.gov (United States)

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.

Multimodal Aspects of Corporate Social Responsibility Communication

Directory of Open Access Journals (Sweden)

Carmen Daniela Maier

2014-12-01

Full Text Available This article addresses how the multimodal persuasive strategies of corporate social responsibility communication can highlight a company’s commitment to gender empowerment and environmental protection while advertising simultaneously its products. Drawing on an interdisciplinary methodological framework related to CSR communication, multimodal discourse analysis and gender theory, the article proposes a multimodal analysis model through which it is possible to map and explain the multimodal persuasive strategies employed by Coca-Cola company in their community-related films. By examining the semiotic modes’ interconnectivity and functional differentiation, this analytical endeavour expands the existing research work as the usual textual focus is extended to a multimodal one.

Multimodal Stepped Care Approach Involving Topical Analgesics for Severe Intractable Neuropathic Pain in CRPS Type 1: A Case Report

Directory of Open Access Journals (Sweden)

David J. Kopsky

2011-01-01

Full Text Available A multimodal stepped care approach has been successfully applied to a patient with complex regional pain syndrome type 1 and severe intractable pain, not responding to regular neuropathic pain medication. The choice to administer drugs in creams was made because of the intolerable adverse effects to oral medication. With this method, peak-dose adverse effects did not occur. The multimodal stepped care approach resulted in considerable and clinically relevant decrease in pain after every step, using topical amitriptyline, ketamine, and dimethylsulphoxide.

Approaches to determining the reliability of a multimodal three-dimensional dynamic signature

Directory of Open Access Journals (Sweden)

Yury E. Kozlov

2018-03-01

Full Text Available The market of modern mobile applications has increasingly strict requirements for the authentication system reliability. This article examines an authentication method using a multimodal three-dimensional dynamic signature (MTDS, that can be used both as a main and additional method of user authentication in mobile applications. It is based on the use of gesture in the air performed by two independent mobile devices as an identifier. The MTDS method has certain advantages over currently used biometric methods, including fingerprint authentication, face recognition and voice recognition. A multimodal three-dimensional dynamic signature allows quickly changing an authentication gesture, as well as concealing the authentication procedure using gestures that do not attract attention. Despite all its advantages, the MTDS method has certain limitations, the main one is building functionally dynamic complex (FDC skills required for accurate repeating an authentication gesture. To correctly create MTDS need to have a system for assessing the reliability of gestures. Approaches to the solution of this task are grouped in this article according to methods of their implementation. Two of the approaches can be implemented only with the use of a server as a centralized MTDS processing center and one approach can be implemented using smartphone's own computing resources. The final part of the article provides data of testing one of these methods on a template performing the MTDS authentication.

Multimodal Speaker Diarization.

Science.gov (United States)

Noulas, A; Englebienne, G; Krose, B J A

2012-01-01

We present a novel probabilistic framework that fuses information coming from the audio and video modality to perform speaker diarization. The proposed framework is a Dynamic Bayesian Network (DBN) that is an extension of a factorial Hidden Markov Model (fHMM) and models the people appearing in an audiovisual recording as multimodal entities that generate observations in the audio stream, the video stream, and the joint audiovisual space. The framework is very robust to different contexts, makes no assumptions about the location of the recording equipment, and does not require labeled training data as it acquires the model parameters using the Expectation Maximization (EM) algorithm. We apply the proposed model to two meeting videos and a news broadcast video, all of which come from publicly available data sets. The results acquired in speaker diarization are in favor of the proposed multimodal framework, which outperforms the single modality analysis results and improves over the state-of-the-art audio-based speaker diarization.

Optimal Face-Iris Multimodal Fusion Scheme

Directory of Open Access Journals (Sweden)

Omid Sharifi

2016-06-01

Full Text Available Multimodal biometric systems are considered a way to minimize the limitations raised by single traits. This paper proposes new schemes based on score level, feature level and decision level fusion to efficiently fuse face and iris modalities. Log-Gabor transformation is applied as the feature extraction method on face and iris modalities. At each level of fusion, different schemes are proposed to improve the recognition performance and, finally, a combination of schemes at different fusion levels constructs an optimized and robust scheme. In this study, CASIA Iris Distance database is used to examine the robustness of all unimodal and multimodal schemes. In addition, Backtracking Search Algorithm (BSA, a novel population-based iterative evolutionary algorithm, is applied to improve the recognition accuracy of schemes by reducing the number of features and selecting the optimized weights for feature level and score level fusion, respectively. Experimental results on verification rates demonstrate a significant improvement of proposed fusion schemes over unimodal and multimodal fusion methods.

Spatiotemporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition

DEFF Research Database (Denmark)

Irani, Ramin; Nasrollahi, Kamal; Oliu Simon, Marc

2015-01-01

facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain...

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

Science.gov (United States)

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.

Multimodality localization of epileptic foci

Science.gov (United States)

Desco, Manuel; Pascau, Javier; Pozo, M. A.; Santos, Andres; Reig, Santiago; Gispert, Juan D.; Garcia-Barreno, Pedro

2001-05-01

This paper presents a multimodality approach for the localization of epileptic foci using PET, MRI and EEG combined without the need of external markers. Mutual Information algorithm is used for MRI-PET registration. Dipole coordinates (provided by BESA software) are projected onto the MRI using a specifically developed algorithm. The four anatomical references used for electrode positioning (nasion, inion and two preauricular points) are located on the MRI using a triplanar viewer combined with a surface-rendering tool. Geometric transformation using deformation of the ideal sphere used for dipole calculations is then applied to match the patient's brain size and shape. Eight treatment-refractory epileptic patients have been studied. The combination of the anatomical information from the MRI, hipoperfusion areas in PET and dipole position and orientation helped the physician in the diagnosis of epileptic focus location. Neurosurgery was not indicated for patients where PET and dipole results were inconsistent; in two cases it was clinically indicated despite the mismatch, showing a negative follow up. The multimodality approach presented does not require external markers for dipole projection onto the MRI, this being the main difference with previous methods. The proposed method may play an important role in the indication of surgery for treatment- refractory epileptic patients.

A Pretargeted Approach for the Multimodal PET/NIRF Imaging of Colorectal Cancer.

Science.gov (United States)

Adumeau, Pierre; Carnazza, Kathryn E; Brand, Christian; Carlin, Sean D; Reiner, Thomas; Agnew, Brian J; Lewis, Jason S; Zeglis, Brian M

2016-01-01

The complementary nature of positron emission tomography (PET) and near-infrared fluorescence (NIRF) imaging makes the development of strategies for the multimodal PET/NIRF imaging of cancer a very enticing prospect. Indeed, in the context of colorectal cancer, a single multimodal PET/NIRF imaging agent could be used to stage the disease, identify candidates for surgical intervention, and facilitate the image-guided resection of the disease. While antibodies have proven to be highly effective vectors for the delivery of radioisotopes and fluorophores to malignant tissues, the use of radioimmunoconjugates labeled with long-lived nuclides such as 89 Zr poses two important clinical complications: high radiation doses to the patient and the need for significant lag time between imaging and surgery. In vivo pretargeting strategies that decouple the targeting vector from the radioactivity at the time of injection have the potential to circumvent these issues by facilitating the use of positron-emitting radioisotopes with far shorter half-lives. Here, we report the synthesis, characterization, and in vivo validation of a pretargeted strategy for the multimodal PET and NIRF imaging of colorectal carcinoma. This approach is based on the rapid and bioorthogonal ligation between a trans -cyclooctene- and fluorophore-bearing immunoconjugate of the huA33 antibody (huA33-Dye800-TCO) and a 64 Cu-labeled tetrazine radioligand ( 64 Cu-Tz-SarAr). In vivo imaging experiments in mice bearing A33 antigen-expressing SW1222 colorectal cancer xenografts clearly demonstrate that this approach enables the non-invasive visualization of tumors and the image-guided resection of malignant tissue, all at only a fraction of the radiation dose created by a directly labeled radioimmunoconjugate. Additional in vivo experiments in peritoneal and patient-derived xenograft models of colorectal carcinoma reinforce the efficacy of this methodology and underscore its potential as an innovative and useful

Detection of heart beats in multimodal data: a robust beat-to-beat interval estimation approach.

Science.gov (United States)

Antink, Christoph Hoog; Brüser, Christoph; Leonhardt, Steffen

2015-08-01

The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is straightforward under ideal conditions, the exact localization can be a challenging task if the signal is severely contaminated with noise and artifacts. At the same time, other signals directly related to cardiac activity are often available. In this multi-sensor scenario, methods of multimodal sensor-fusion allow the exploitation of redundancies to increase the accuracy and robustness of beat detection.In this paper, an algorithm for the robust detection of heart beats in multimodal data is presented. Classic peak-detection is augmented by robust multi-channel, multimodal interval estimation to eliminate false detections and insert missing beats. This approach yielded a score of 90.70 and was thus ranked third place in the PhysioNet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Muthmodal Data follow-up analysis.In the future, the robust beat-to-beat interval estimator may directly be used for the automated processing of multimodal patient data for applications such as diagnosis support and intelligent alarming.

Naming Block Structures: A Multimodal Approach

Science.gov (United States)

Cohen, Lynn; Uhry, Joanna

2011-01-01

This study describes symbolic representation in block play in a culturally diverse suburban preschool classroom. Block play is "multimodal" and can allow children to experiment with materials to represent the world in many forms of literacy. Combined qualitative and quantitative data from seventy-seven block structures were collected and analyzed.…

Human Behavior Analysis by Means of Multimodal Context Mining

Directory of Open Access Journals (Sweden)

Oresti Banos

2016-08-01

Full Text Available There is sufficient evidence proving the impact that negative lifestyle choices have on people’s health and wellness. Changing unhealthy behaviours requires raising people’s self-awareness and also providing healthcare experts with a thorough and continuous description of the user’s conduct. Several monitoring techniques have been proposed in the past to track users’ behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters. This work presents an innovative multimodal context mining framework to inspect and infer human behaviour in a more holistic fashion. The proposed approach extends beyond the state-of-the-art, since it not only explores a sole type of context, but also combines diverse levels of context in an integral manner. Namely, low-level contexts, including activities, emotions and locations, are identified from heterogeneous sensory data through machine learning techniques. Low-level contexts are combined using ontological mechanisms to derive a more abstract representation of the user’s context, here referred to as high-level context. An initial implementation of the proposed framework supporting real-time context identification is also presented. The developed system is evaluated for various realistic scenarios making use of a novel multimodal context open dataset and data on-the-go, demonstrating prominent context-aware capabilities at both low and high levels.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Multimodality and the literary text: making sense of Safran Foer's Extremely Loud and Incredibly Close

DEFF Research Database (Denmark)

Nørgaard, Nina

2010-01-01

This article explores the applicability of a multimodal framework to the analysis of literature. The framework adopted is that proposed by Kress and Van Leeuwen (2001) and Van Leeuwen (2005). In seeking to develop a detailed and consistent methodology that will allow us to deal with multimodal te...... typographies, graphics, colour, layout, photographic images etc. - emphatically invites an analytical approach designed to understand meaning-making as an interplay of different semiotic modes....

Interactivity in Educational Apps for Young children: A Multimodal Analysis

Directory of Open Access Journals (Sweden)

Alexandra H. Blitz-Raith

2017-11-01

Full Text Available Interactivity is an important indicator of an educational app's reception. Since most educational apps are multimodal, it justifies a methodological initiative to understand meaningful involvement of multimodality in enacting and even amplifying interactivity in an educational app. Yet research so far has largely concentrated on algorithm construct and user feedback rather than on multimodal interactions, especially from a social semiotics perspective. Drawing from social semiotics approaches, this article proposes a multimodal analytic framework to examine three layers of mode in engendering interaction; namely, multiplicity, function, and relationship. Using the analytic framework in an analysis of The Farm Adventure for Kids, a popular educational app for pre-school children, we found that still images are dominant proportionally and are central in the interactive process. We also found that tapping still images of animals on screen is the main action, with other screen actions deliberately excluded. Such findings suggest that aligning children’s cognitive and physical capabilities to the use of mode become the primary consideration in educational app design and that consistent attendance to this alignment in mobilizing modes significantly affect an educational app’s interactivity, and consequently its reception by young children

Multimodal label-free microscopy

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Nicolas Pavillon

2014-09-01

Full Text Available This paper reviews the different multimodal applications based on a large extent of label-free imaging modalities, ranging from linear to nonlinear optics, while also including spectroscopic measurements. We put specific emphasis on multimodal measurements going across the usual boundaries between imaging modalities, whereas most multimodal platforms combine techniques based on similar light interactions or similar hardware implementations. In this review, we limit the scope to focus on applications for biology such as live cells or tissues, since by their nature of being alive or fragile, we are often not free to take liberties with the image acquisition times and are forced to gather the maximum amount of information possible at one time. For such samples, imaging by a given label-free method usually presents a challenge in obtaining sufficient optical signal or is limited in terms of the types of observable targets. Multimodal imaging is then particularly attractive for these samples in order to maximize the amount of measured information. While multimodal imaging is always useful in the sense of acquiring additional information from additional modes, at times it is possible to attain information that could not be discovered using any single mode alone, which is the essence of the progress that is possible using a multimodal approach.

Multimodal coaching and its application to workplace, life and health coaching

OpenAIRE

Stephen Palmer

2012-01-01

This article highlights how the multimodal approach (Lazarus, 1989) has been adapted to the field of coachingand coaching psychology. It covers the basic theories underpinning the multimodal approach and illustratesthe link between the theory and practice. Key multimodal strategies are covered including modalityprofiles, structural profiles, tracking and bridging.

A multi-modal treatment approach for the shoulder: A 4 patient case series

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Pollard Henry

2005-09-01

Full Text Available Abstract Background This paper describes the clinical management of four cases of shoulder impingement syndrome using a conservative multimodal treatment approach. Clinical Features Four patients presented to a chiropractic clinic with chronic shoulder pain, tenderness in the shoulder region and a limited range of motion with pain and catching. After physical and orthopaedic examination a clinical diagnosis of shoulder impingement syndrome was reached. The four patients were admitted to a multi-modal treatment protocol including soft tissue therapy (ischaemic pressure and cross-friction massage, 7 minutes of phonophoresis (driving of medication into tissue with ultrasound with 1% cortisone cream, diversified spinal and peripheral joint manipulation and rotator cuff and shoulder girdle muscle exercises. The outcome measures for the study were subjective/objective visual analogue pain scales (VAS, range of motion (goniometer and return to normal daily, work and sporting activities. All four subjects at the end of the treatment protocol were symptom free with all outcome measures being normal. At 1 month follow up all patients continued to be symptom free with full range of motion and complete return to normal daily activities. Conclusion This case series demonstrates the potential benefit of a multimodal chiropractic protocol in resolving symptoms associated with a suspected clinical diagnosis of shoulder impingement syndrome.

Multimodal coaching and its application to workplace, life and health coaching

Directory of Open Access Journals (Sweden)

Stephen Palmer

2012-10-01

Full Text Available This article highlights how the multimodal approach (Lazarus, 1989 has been adapted to the field of coachingand coaching psychology. It covers the basic theories underpinning the multimodal approach and illustratesthe link between the theory and practice. Key multimodal strategies are covered including modalityprofiles, structural profiles, tracking and bridging.

The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

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Denis Pinha

2016-11-01

Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

Joint sparse representation for robust multimodal biometrics recognition.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Jing-Yu Yang

2012-04-01

Full Text Available 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.

Deterministic multimode photonic device for quantum-information processing

DEFF Research Database (Denmark)

Nielsen, Anne E. B.; Mølmer, Klaus

2010-01-01

We propose the implementation of a light source that can deterministically generate a rich variety of multimode quantum states. The desired states are encoded in the collective population of different ground hyperfine states of an atomic ensemble and converted to multimode photonic states by exci...

Multimodal approach to postoperative recovery

DEFF Research Database (Denmark)

Kehlet, Henrik

2009-01-01

PURPOSE OF REVIEW: To provide updated information on recent developments within individual components of multimodal interventions to improve postoperative outcome (fast-track methodology). RECENT FINDINGS: The value of the fast-track methodology to improve recovery and decrease hospital stay...... and morbidity has been firmly consolidated, especially in colorectal procedures. An increasing amount of data from other procedures supports the value of the fast-track concept across procedures. Fast-track programs should be based on the analysis of procedure-specific factors that may influence outcome...

Multimodality Registration without a Dedicated Multimodality Scanner

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Bradley J. Beattie

2007-03-01

Full Text Available Multimodality scanners that allow the acquisition of both functional and structural image sets on a single system have recently become available for animal research use. Although the resultant registered functional/structural image sets can greatly enhance the interpretability of the functional data, the cost of multimodality systems can be prohibitive, and they are often limited to two modalities, which generally do not include magnetic resonance imaging. Using a thin plastic wrap to immobilize and fix a mouse or other small animal atop a removable bed, we are able to calculate registrations between all combinations of four different small animal imaging scanners (positron emission tomography, single-photon emission computed tomography, magnetic resonance, and computed tomography [CT] at our disposal, effectively equivalent to a quadruple-modality scanner. A comparison of serially acquired CT images, with intervening acquisitions on other scanners, demonstrates the ability of the proposed procedures to maintain the rigidity of an anesthetized mouse during transport between scanners. Movement of the bony structures of the mouse was estimated to be 0.62 mm. Soft tissue movement was predominantly the result of the filling (or emptying of the urinary bladder and thus largely constrained to this region. Phantom studies estimate the registration errors for all registration types to be less than 0.5 mm. Functional images using tracers targeted to known structures verify the accuracy of the functional to structural registrations. The procedures are easy to perform and produce robust and accurate results that rival those of dedicated multimodality scanners, but with more flexible registration combinations and while avoiding the expense and redundancy of multimodality systems.

First and second branchial arch syndromes: multimodality approach

Energy Technology Data Exchange (ETDEWEB)

Senggen, Elodie; Laswed, Tarek; Meuwly, Jean-Yves; Maestre, Leonor Alamo; Meuli, Reto; Gudinchet, Francois [University Hospital of Lausanne, Radiology Department, Lausanne (Switzerland); Jaques, Bertrand [University Hospital of Lausanne, Department of Otorhinolaryngology, Lausanne (Switzerland)

2011-05-15

First and second branchial arch syndromes (BAS) manifest as combined tissue deficiencies and hypoplasias of the face, external ear, middle ear and maxillary and mandibular arches. They represent the second most common craniofacial malformation after cleft lip and palate. Extended knowledge of the embryology and anatomy of each branchial arch derivative is mandatory for the diagnosis and grading of different BAS lesions and in the follow-up of postoperative patients. In recent years, many new complex surgical approaches and procedures have been designed by maxillofacial surgeons to treat extensive maxillary, mandibular and external and internal ear deformations. The purpose of this review is to evaluate the role of different imaging modalities (orthopantomogram (OPG), lateral and posteroanterior cephalometric radiographs, CT and MRI) in the diagnosis of a wide spectrum of first and second BAS, including hemifacial microsomia, mandibulofacial dysostosis, branchio-oto-renal syndrome, Pierre Robin sequence and Nager acrofacial dysostosis. Additionally, we aim to emphasize the importance of the systematic use of a multimodality imaging approach to facilitate the precise grading of these syndromes, as well as the preoperative planning of different reconstructive surgical procedures and their follow-up during treatment. (orig.)

First and second branchial arch syndromes: multimodality approach

International Nuclear Information System (INIS)

Senggen, Elodie; Laswed, Tarek; Meuwly, Jean-Yves; Maestre, Leonor Alamo; Meuli, Reto; Gudinchet, Francois; Jaques, Bertrand

2011-01-01

First and second branchial arch syndromes (BAS) manifest as combined tissue deficiencies and hypoplasias of the face, external ear, middle ear and maxillary and mandibular arches. They represent the second most common craniofacial malformation after cleft lip and palate. Extended knowledge of the embryology and anatomy of each branchial arch derivative is mandatory for the diagnosis and grading of different BAS lesions and in the follow-up of postoperative patients. In recent years, many new complex surgical approaches and procedures have been designed by maxillofacial surgeons to treat extensive maxillary, mandibular and external and internal ear deformations. The purpose of this review is to evaluate the role of different imaging modalities (orthopantomogram (OPG), lateral and posteroanterior cephalometric radiographs, CT and MRI) in the diagnosis of a wide spectrum of first and second BAS, including hemifacial microsomia, mandibulofacial dysostosis, branchio-oto-renal syndrome, Pierre Robin sequence and Nager acrofacial dysostosis. Additionally, we aim to emphasize the importance of the systematic use of a multimodality imaging approach to facilitate the precise grading of these syndromes, as well as the preoperative planning of different reconstructive surgical procedures and their follow-up during treatment. (orig.)

Dynamic analysis of holiday travel behavior with integrated multimodal travel information usage : a life-oriented approach

NARCIS (Netherlands)

Wang, B.; Shao, C.; Ji, X.

2017-01-01

The Integrated Multimodal Travel Information (IMTI) plays an important role in the evolution process of holiday travel behaviour, which is seldom investigated. To fill this gap, this study analyses holiday travel behaviour dynamics with IMTI usage, based on the life-oriented approach. IMTI usage is

Approaching Athenian Graffiti as a Multimodal Genre with GIS Application

OpenAIRE

Stampoulidis, Georgios

2017-01-01

Graffiti as an ever-changing form of urban art and visual communication is naturally multimodal, focusing on text–image relations (Bateman 2014; Forceville 2008; Kress 2006), which owe their existence mainly to the sociocultural and historical knowledge of the represented world of our experience – Husserlian Lebenswelt [Lifeworld] (Sonesson 2008; 2015). These relations constitute an interesting challenge to multimodal interpretations, because both verbal and/or pictorial representations can i...

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

Science.gov (United States)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Multimodal Pedagogies for Teacher Education in TESOL

Science.gov (United States)

Yi, Youngjoo; Angay-Crowder, Tuba

2016-01-01

As a growing number of English language learners (ELLs) engage in digital and multimodal literacy practices in their daily lives, teachers are starting to incorporate multimodal approaches into their instruction. However, anecdotal and empirical evidence shows that teachers often feel unprepared for integrating such practices into their curricula…

The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

Science.gov (United States)

Quek, Francis

2004-12-01

The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to "whole gesture" recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

Multimodality imaging techniques.

Science.gov (United States)

Martí-Bonmatí, Luis; Sopena, Ramón; Bartumeus, Paula; Sopena, Pablo

2010-01-01

In multimodality imaging, the need to combine morphofunctional information can be approached by either acquiring images at different times (asynchronous), and fused them through digital image manipulation techniques or simultaneously acquiring images (synchronous) and merging them automatically. The asynchronous post-processing solution presents various constraints, mainly conditioned by the different positioning of the patient in the two scans acquired at different times in separated machines. The best solution to achieve consistency in time and space is obtained by the synchronous image acquisition. There are many multimodal technologies in molecular imaging. In this review we will focus on those multimodality image techniques more commonly used in the field of diagnostic imaging (SPECT-CT, PET-CT) and new developments (as PET-MR). The technological innovations and development of new tracers and smart probes are the main key points that will condition multimodality image and diagnostic imaging professionals' future. Although SPECT-CT and PET-CT are standard in most clinical scenarios, MR imaging has some advantages, providing excellent soft-tissue contrast and multidimensional functional, structural and morphological information. The next frontier is to develop efficient detectors and electronics systems capable of detecting two modality signals at the same time. Not only PET-MR but also MR-US or optic-PET will be introduced in clinical scenarios. Even more, MR diffusion-weighted, pharmacokinetic imaging, spectroscopy or functional BOLD imaging will merge with PET tracers to further increase molecular imaging as a relevant medical discipline. Multimodality imaging techniques will play a leading role in relevant clinical applications. The development of new diagnostic imaging research areas, mainly in the field of oncology, cardiology and neuropsychiatry, will impact the way medicine is performed today. Both clinical and experimental multimodality studies, in

Modern spinal instrumentation. Part 2: Multimodality imaging approach for assessment of complications

International Nuclear Information System (INIS)

Allouni, A.K.; Davis, W.; Mankad, K.; Rankine, J.; Davagnanam, I.

2013-01-01

Radiologists frequently encounter studies demonstrating spinal instrumentation, either as part of the patient's postoperative evaluation, or as incidental to a study performed for another purpose. It is important for the reporting radiologist to identify potential complications of commonly used spinal implants. Part 1 of this review examined both the surgical approaches used and the normal appearances of these spinal implants and bone grafting techniques. This second part of the review will focus on the multimodal imaging strategy adopted in the assessment of the instrumented spine and the demonstration of imaging findings of common postoperative complications.

Testing Multimodal Integration Hypotheses with Application to Schizophrenia Data

DEFF Research Database (Denmark)

Axelsen, Martin Christian; Bak, Nikolaj; Hansen, Lars Kai

2015-01-01

of the present paper is to propose a method for assessing these inter-modality dependencies. The approach is based on two permutations of an analyzed data set, each exploring different dependencies between and within modalities. The method was tested on the Kaggle MLSP 2014 Schizophrenia Classification Challenge...... data set which is composed of features from functional magnetic resonance imaging (MRI) and structural MRI. The results support the use of a permutation strategy for testing conditional dependencies between modalities in a multimodal classification problem....

Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

Directory of Open Access Journals (Sweden)

Xi Jin

2015-01-01

Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

Science.gov (United States)

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.

Advanced Multimode Radio for Wireless & Mobile Broadband Communication

DEFF Research Database (Denmark)

Kardaras, Georgios; Lanzani, Christian

2009-01-01

Distributed base station architectures represent the new trend that operators follow in order to resolve cost, performance and efficiency challenges when deploying 4G networks. Main components of such architectures are multimode radios capable of operating according to GSM, HSPA, WiMAX and LTE...... of a digital predistortion (DPD) block is emphasized and an adaptive polynomial approach based on cartesian to polar conversion is then proposed. Such radio architecture has successfully been implemented on a low-cost FPGA family meeting the WiMAX/LTE spectrum and Error Vector Magnitude (EVM) requirements....

Evaluation of the Multimodal Strategy for Improvement of Hand Hygiene as Proposed by the World Health Organization.

Science.gov (United States)

Pereira, Eliana B S; Jorge, Miguel T; Oliveira, Elias J; Júnior, Alberto Lopes Ribeiro; Santos, Lauro R L; Mendes-Rodrigues, Clesnan

Hand hygiene has the biggest impact and is the least expensive way to prevent and control health care-associated infections. In this study, we assessed the effectiveness of the multimodal strategy of the World Health Organization to improve health care-associated infection rates, hand hygiene compliance, and the related knowledge of health care professionals in a Brazilian university hospital. We observed the necessity for an alternative approach in hospitals with high staff turnover and low attendance of educational sessions.

The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

Directory of Open Access Journals (Sweden)

Francis Quek

2004-09-01

Full Text Available The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to “whole gesture” recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

Multimodal approach to identifying malingered posttraumatic stress disorder: a review.

Science.gov (United States)

Ali, Shahid; Jabeen, Shagufta; Alam, Farzana

2015-01-01

The primary aim of this article is to aid clinicians in differentiating true posttraumatic stress disorder from malingered posttraumatic stress disorder. Posttraumatic stress disorder and malingering are defined, and prevalence rates are explored. Similarities and differences in diagnostic criteria between the fourth and fifth editions of the Diagnostic and Statistical Manual of Mental Disorders are described for posttraumatic stress disorder. Possible motivations for malingering posttraumatic stress disorder are discussed, and common characteristics of malingered posttraumatic stress disorder are described. A multimodal approach is described for evaluating posttraumatic stress disorder, including interview techniques, collection of collateral data, and psychometric and physiologic testing, that should allow clinicians to distinguish between those patients who are truly suffering from posttraumatic disorder and those who are malingering the illness.

EXPLICITATION AND ADDITION TECHNIQUES IN AUDIOVISUAL TRANSLATION: A MULTIMODAL APPROACH OF ENGLISHINDONESIAN SUBTITLES

Directory of Open Access Journals (Sweden)

Ichwan Suyudi

2017-12-01

Full Text Available In audiovisual translation, the multimodality of the audiovisual text is both a challenge and a resource for subtitlers. This paper illustrates how multi-modes provide information that helps subtitlers to gain a better understanding of meaning-making practices that will influence them to make a decision-making in translating a certain verbal text. Subtitlers may explicit, add, and condense the texts based on the multi-modes as seen on the visual frames. Subtitlers have to consider the distribution and integration of the meanings of multi-modes in order to create comprehensive equivalence between the source and target texts. Excerpts of visual frames in this paper are taken from English films Forrest Gump (drama, 1996, and James Bond (thriller, 2010.

Critical Multimodal Hip Hop Production: A Social Justice Approach to African American Language and Literacy Practices

Science.gov (United States)

Turner, K. C. Nat; Hayes, Nini, Visaya; Way, Kate

2013-01-01

This article features key findings from a study that highlights the transformative impact of a pedagogical approach that employs Critical Multimodal Hip Hop Production (CMHHP). The study took place in an extended day program in a northern California public middle school among a group of 30, urban, African American, Chicano/a/Latino/a, and Asian…

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

Science.gov (United States)

Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

2017-06-01

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment

Adaptive Multiview Nonnegative Matrix Factorization Algorithm for Integration of Multimodal Biomedical Data

Directory of Open Access Journals (Sweden)

Bisakha Ray

2017-08-01

have applied our proposed approach to multimodal molecular data for tumors, but it is generally applicable to dimensionality reduction and joint analysis of any type of multimodal data.

Recent developments in multimodality fluorescence imaging probes

Directory of Open Access Journals (Sweden)

Jianhong Zhao

2018-05-01

Full Text Available Multimodality optical imaging probes have emerged as powerful tools that improve detection sensitivity and accuracy, important in disease diagnosis and treatment. In this review, we focus on recent developments of optical fluorescence imaging (OFI probe integration with other imaging modalities such as X-ray computed tomography (CT, magnetic resonance imaging (MRI, positron emission tomography (PET, single-photon emission computed tomography (SPECT, and photoacoustic imaging (PAI. The imaging technologies are briefly described in order to introduce the strengths and limitations of each techniques and the need for further multimodality optical imaging probe development. The emphasis of this account is placed on how design strategies are currently implemented to afford physicochemically and biologically compatible multimodality optical fluorescence imaging probes. We also present studies that overcame intrinsic disadvantages of each imaging technique by multimodality approach with improved detection sensitivity and accuracy. KEY WORDS: Optical imaging, Fluorescence, Multimodality, Near-infrared fluorescence, Nanoprobe, Computed tomography, Magnetic resonance imaging, Positron emission tomography, Single-photon emission computed tomography, Photoacoustic imaging

Multimodal Estimation of Distribution Algorithms.

Science.gov (United States)

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.

Damage classification of pipelines under water flow operation using multi-mode actuated sensing technology

International Nuclear Information System (INIS)

Lee, Changgil; Park, Seunghee

2011-01-01

In a structure, several types of damage can occur, ranging from micro-cracking to corrosion or loose bolts. This makes identifying the damage difficult with a single mode of sensing. Therefore, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In self-sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this experimental study, a pipeline system under water flow operation was examined to verify the effectiveness and robustness of the proposed structural health monitoring approach. Different types of structural damage were inflicted artificially on the pipeline system. To classify the multiple types of structural damage, supervised learning-based statistical pattern recognition was implemented by composing a three-dimensional space using the damage indices extracted from the impedance and guided wave features as well as temperature variations. For a more systematic damage classification, several control parameters were optimized to determine an optimal decision boundary for the supervised learning-based pattern recognition. Further research issues are also discussed for real-world implementations of the proposed approach

Implications of Multimodal Learning Models for foreign language teaching and learning

Directory of Open Access Journals (Sweden)

Miguel Farías

2011-04-01

Full Text Available This literature review article approaches the topic of information and communications technologies from the perspective of their impact on the language learning process, with particular emphasis on the most appropriate designs of multimodal texts as informed by models of multimodal learning. The first part contextualizes multimodality within the fields of discourse studies, the psychology of learning and CALL; the second, deals with multimodal conceptions of reading and writing by discussing hypertextuality and literacy. A final section outlines the possible implications of multimodal learning models for foreign language teaching and learning.

Alcohol sensor based on single-mode-multimode-single-mode fiber structure

Science.gov (United States)

Mefina Yulias, R.; Hatta, A. M.; Sekartedjo, Sekartedjo

2016-11-01

Alcohol sensor based on Single-mode -Multimode-Single-mode (SMS) fiber structure is being proposed to sense alcohol concentration in alcohol-water mixtures. This proposed sensor uses refractive index sensing as its sensing principle. Fabricated SMS fiber structure had 40 m of multimode length. With power input -6 dBm and wavelength 1550 nm, the proposed sensor showed good response with sensitivity 1,983 dB per % v/v with measurement range 05 % v/v and measurement span 0,5% v/v.

Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System

Directory of Open Access Journals (Sweden)

Defiana Sulaeman

2016-12-01

Full Text Available Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation, motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS. This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.

When to Intervene in Selective Mutism: The Multimodal Treatment of a Case of Persistent Selective Mutism.

Science.gov (United States)

Powell, Shawn; Dalley, Mahlono

1995-01-01

An identification and treatment model differentiating transient mutism from persistent selective mutism is proposed. The case study of a six-year-old girl is presented, who was treated with a multimodal approach combining behavioral techniques with play therapy and family involvement. At posttreatment and follow-up, she was talking in a manner…

Interaction between visual and chemical cues in a Liolaemus lizard: a multimodal approach.

Science.gov (United States)

Vicente, Natalin S; Halloy, Monique

2017-12-01

Multimodal communication involves the use of signals and cues across two or more sensory modalities. The genus Liolaemus (Iguania: Liolaemidae) offers a great potential for studies on the ecology and evolution of multimodal communication, including visual and chemical signals. In this study, we analyzed the response of male and female Liolaemus pacha to chemical, visual and combined (multimodal) stimuli. Using cue-isolation tests, we registered the number of tongue flicks and headbob displays from exposure to signals in each modality. Number of tongue flicks was greater when a chemical stimulus was presented alone than in the presence of visual or multimodal stimuli. In contrast, headbob displays were fewer in number with visual and chemical stimuli alone, but significantly higher in number when combined. Female signallers triggered significantly more tongue flicks than male signallers, suggesting that chemical cues are involved in sexual recognition. We did not find an inhibition between chemical and visual cues. On the contrary, we observed a dominance of the chemical modality, because when presented with visual stimuli, lizards also responded with more tongue flicks than headbob displays. The total response produced by multimodal stimuli was similar to that of the chemical stimuli alone, possibly suggesting non-redundancy. We discuss whether the visual component of a multimodal signal could attract attention at a distance, increasing the effectiveness of transmission and reception of the information in chemical cues. Copyright © 2017 Elsevier GmbH. All rights reserved.

Seizure Onset Detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) System

DEFF Research Database (Denmark)

Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

2010-01-01

An automatic Uni- or Multi-modal Inteligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic...... algorithm on motion data is extracting features as “log-sum” measures of discrete wavelet components. Classification into the two groups “seizure” versus “nonseizure” is made based on the support vector machine (SVM) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1...... second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multimodal approach, as compared...

Composition at Washington State University: Building a Multimodal Bricolage

Science.gov (United States)

Ericsson, Patricia; Hunter, Leeann Downing; Macklin, Tialitha Michelle; Edwards, Elizabeth Sue

2016-01-01

Multimodal pedagogy is increasingly accepted among composition scholars. However, putting such pedagogy into practice presents significant challenges. In this profile of Washington State University's first-year composition program, we suggest a multi-vocal and multi-theoretical approach to addressing the challenges of multimodal pedagogy. Patricia…

Multimodal physiotherapy treatment based on a biobehavioral approach for patients with chronic cervico-craniofacial pain: a prospective case series.

Science.gov (United States)

Marcos-Martín, Fernando; González-Ferrero, Luis; Martín-Alcocer, Noelia; Paris-Alemany, Alba; La Touche, Roy

2018-01-17

The purpose of this prospective case series was to observe and describe changes in patients with chronic cervico-craniofacial pain of muscular origin treated with multimodal physiotherapy based on a biobehavioral approach. Nine patients diagnosed with chronic myofascial temporomandibular disorder and neck pain were treated with 6 sessions over the course of 2 weeks including: (1) orthopedic manual physiotherapy (joint mobilizations, neurodynamic mobilization, and dynamic soft tissue mobilizations); (2) therapeutic exercises (motor control and muscular endurance exercises); and (3) patient education. The outcome measures of craniofacial (CF-PDI) and neck disability (NDI), kinesiophobia (TSK-11) and catastrophizing (PCS), and range of cervical and mandibular motion (ROM) and posture were collected at baseline, and at 2 and 14 weeks post-baseline. Compared to baseline, statistically significant (p posture were observed following a multimodal physiotherapy treatment based on a biobehavioral approach.

Multimodal aspects of CSR communication related to gender empowerment and environmental protection

DEFF Research Database (Denmark)

Maier, Carmen Daniela

Purpose – This paper explores how the multimodal persuasive strategies of CSR communication related to Coca-Cola’s “5 by 20” succeed to highlight the company’s continuous commitment to gender empowerment and environmental protection. Launched in 2010, “5 by 20” is a program designed to empower 5...... million female entrepreneurs throughout the company’s global business system by 2020. The program has recently received 2013 Catalyst Award for its accomplishments. According to the company’s homepage, hundreds of thousands of women around the world are building stronger businesses, families...... and communities due to the implementation of this program. The environmental concerns are embedded in their activities. Approach – Drawing on an interdisciplinary methodological framework related to CSR communication, multimodal discourse analysis, gender theory and environmental communication, the paper proposes...

Multimodal training between agents

DEFF Research Database (Denmark)

Rehm, Matthias

2003-01-01

In the system Locator1, agents are treated as individual and autonomous subjects that are able to adapt to heterogenous user groups. Applying multimodal information from their surroundings (visual and linguistic), they acquire the necessary concepts for a successful interaction. This approach has...

An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

KAUST Repository

Li, Huibin

2015-07-29

We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

KAUST Repository

Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming

2015-01-01

We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

The Big Five: Addressing Recurrent Multimodal Learning Data Challenges

NARCIS (Netherlands)

Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik

2018-01-01

The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in

Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling

Directory of Open Access Journals (Sweden)

Wenkai Zhang

2017-12-01

Full Text Available In recent years, Fully Convolutional Networks (FCN have led to a great improvement of semantic labeling for various applications including multi-modal remote sensing data. Although different fusion strategies have been reported for multi-modal data, there is no in-depth study of the reasons of performance limits. For example, it is unclear, why an early fusion of multi-modal data in FCN does not lead to a satisfying result. In this paper, we investigate the contribution of individual layers inside FCN and propose an effective fusion strategy for the semantic labeling of color or infrared imagery together with elevation (e.g., Digital Surface Models. The sensitivity and contribution of layers concerning classes and multi-modal data are quantified by recall and descent rate of recall in a multi-resolution model. The contribution of different modalities to the pixel-wise prediction is analyzed explaining the reason of the poor performance caused by the plain concatenation of different modalities. Finally, based on the analysis an optimized scheme for the fusion of layers with image and elevation information into a single FCN model is derived. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset (infrared and RGB imagery as well as elevation and the Potsdam dataset (RGB imagery and elevation. Comprehensive evaluations demonstrate the potential of the proposed approach.

Graduate Education and Simulation Training for CBRNE Disasters Using a Multimodal Approach to Learning. Part 2: Education and Training from the Perspectives of Educators and Students

Science.gov (United States)

2013-08-01

quantify learning effectiveness and retention rates by comparing didactic lectures, reading, audiovisual presentations, demonstrations, discussion...Graduate Education and Simulation Training   for CBRNE Disasters Using a Multimodal  Approach to  Learning   Part 2: Education and Training from the...TITLE AND SUBTITLE Graduate Education and Simulation Training for CBRNE Disasters Using a Multimodal 5a. CONTRACT NUMBER Approach to Learning

Fiber-Optic Vibration Sensor Based on Multimode Fiber

Directory of Open Access Journals (Sweden)

I. Lujo

2008-06-01

Full Text Available The purpose of this paper is to present a fiberoptic vibration sensor based on the monitoring of the mode distribution in a multimode optical fiber. Detection of vibrations and their parameters is possible through observation of the output speckle pattern from the multimode optical fiber. A working experimental model has been built in which all used components are widely available and cheap: a CCD camera (a simple web-cam, a multimode laser in visible range as a light source, a length of multimode optical fiber, and a computer for signal processing. Measurements have shown good agreement with the actual frequency of vibrations, and promising results were achieved with the amplitude measurements although they require some adaptation of the experimental model. Proposed sensor is cheap and lightweight and therefore presents an interesting alternative for monitoring large smart structures.

FUSION BASED MULTIMODAL AUTHENTICATION IN BIOMETRICS USING CONTEXT-SENSITIVE EXPONENT ASSOCIATIVE MEMORY MODEL : A NOVEL APPROACH

OpenAIRE

P. E. S. N. Krishna Prasad; Pavan Kumar K; M. V. Ramakrishna; B. D. C. N. Prasad

2013-01-01

Biometrics is one of the primary key concepts of real application domains such as aadhar card, passport, pan card, etc. In such applications user can provide two to three biometrics patterns like face, finger, palm, signature, iris data, and so on. We considered face and finger patterns for encoding and then also for verification. Using this data we proposed a novel model for authentication in multimodal biometrics often called Context-Sensitive Exponent Associative Memory Mode...

Multimodal network design and assessment

NARCIS (Netherlands)

Brands, Ties; Alkim, T.P.; van Eck, Gijs; van Arem, Bart; Arentze, T.

2010-01-01

A framework is proposed for the design of an optimal multimodal transport network for the Randstad area. This research framework consists of a multi-objective optimization heuristic and a fast network assessment module, which results in a set of Pareto optimal solutions. Subsequently, a proper

Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion

Directory of Open Access Journals (Sweden)

Long Binh Tran

2017-01-01

Full Text Available In this paper, the authors present a novel personal verification system based on the likelihood ratio test for fusion of match scores from multiple biometric matchers (face, fingerprint, hand shape, and palm print. In the proposed system, multimodal features are extracted by Zernike Moment (ZM. After matching, the match scores from multiple biometric matchers are fused based on the likelihood ratio test. A finite Gaussian mixture model (GMM is used for estimating the genuine and impostor densities of match scores for personal verification. Our approach is also compared to some different famous approaches such as the support vector machine and the sum rule with min-max. The experimental results have confirmed that the proposed system can achieve excellent identification performance for its higher level in accuracy than different famous approaches and thus can be utilized for more application related to person verification.

Spectral space-time coding for optical communications through a multimode fiber

NARCIS (Netherlands)

Alonso, A.; Berghmans, F.; Thienpont, H.; Danckaert, J.; Desmet, L.

2001-01-01

We propose a method for coding the mode structure of a multimode optical fiber by spectral coding mixed with space-time modulation. With this system we can improve the data carrying capacity of a multimode fiber for optical communications and optical interconnects, and encode and decode the

Multimodal quantitative phase and fluorescence imaging of cell apoptosis

Science.gov (United States)

Fu, Xinye; Zuo, Chao; Yan, Hao

2017-06-01

Fluorescence microscopy, utilizing fluorescence labeling, has the capability to observe intercellular changes which transmitted and reflected light microscopy techniques cannot resolve. However, the parts without fluorescence labeling are not imaged. Hence, the processes simultaneously happen in these parts cannot be revealed. Meanwhile, fluorescence imaging is 2D imaging where information in the depth is missing. Therefore the information in labeling parts is also not complete. On the other hand, quantitative phase imaging is capable to image cells in 3D in real time through phase calculation. However, its resolution is limited by the optical diffraction and cannot observe intercellular changes below 200 nanometers. In this work, fluorescence imaging and quantitative phase imaging are combined to build a multimodal imaging system. Such system has the capability to simultaneously observe the detailed intercellular phenomenon and 3D cell morphology. In this study the proposed multimodal imaging system is used to observe the cell behavior in the cell apoptosis. The aim is to highlight the limitations of fluorescence microscopy and to point out the advantages of multimodal quantitative phase and fluorescence imaging. The proposed multimodal quantitative phase imaging could be further applied in cell related biomedical research, such as tumor.

Learning of Multimodal Representations With Random Walks on the Click Graph.

Science.gov (United States)

Wu, Fei; Lu, Xinyan; Song, Jun; Yan, Shuicheng; Zhang, Zhongfei Mark; Rui, Yong; Zhuang, Yueting

2016-02-01

In multimedia information retrieval, most classic approaches tend to represent different modalities of media in the same feature space. With the click data collected from the users' searching behavior, existing approaches take either one-to-one paired data (text-image pairs) or ranking examples (text-query-image and/or image-query-text ranking lists) as training examples, which do not make full use of the click data, particularly the implicit connections among the data objects. In this paper, we treat the click data as a large click graph, in which vertices are images/text queries and edges indicate the clicks between an image and a query. We consider learning a multimodal representation from the perspective of encoding the explicit/implicit relevance relationship between the vertices in the click graph. By minimizing both the truncated random walk loss as well as the distance between the learned representation of vertices and their corresponding deep neural network output, the proposed model which is named multimodal random walk neural network (MRW-NN) can be applied to not only learn robust representation of the existing multimodal data in the click graph, but also deal with the unseen queries and images to support cross-modal retrieval. We evaluate the latent representation learned by MRW-NN on a public large-scale click log data set Clickture and further show that MRW-NN achieves much better cross-modal retrieval performance on the unseen queries/images than the other state-of-the-art methods.

Comprehensive Context Recognizer Based on Multimodal Sensors in a Smartphone

Directory of Open Access Journals (Sweden)

Sungyoung Lee

2012-09-01

Full Text Available Recent developments in smartphones have increased the processing capabilities and equipped these devices with a number of built-in multimodal sensors, including accelerometers, gyroscopes, GPS interfaces, Wi-Fi access, and proximity sensors. Despite the fact that numerous studies have investigated the development of user-context aware applications using smartphones, these applications are currently only able to recognize simple contexts using a single type of sensor. Therefore, in this work, we introduce a comprehensive approach for context aware applications that utilizes the multimodal sensors in smartphones. The proposed system is not only able to recognize different kinds of contexts with high accuracy, but it is also able to optimize the power consumption since power-hungry sensors can be activated or deactivated at appropriate times. Additionally, the system is able to recognize activities wherever the smartphone is on a human’s body, even when the user is using the phone to make a phone call, manipulate applications, play games, or listen to music. Furthermore, we also present a novel feature selection algorithm for the accelerometer classification module. The proposed feature selection algorithm helps select good features and eliminates bad features, thereby improving the overall accuracy of the accelerometer classifier. Experimental results show that the proposed system can classify eight activities with an accuracy of 92.43%.

OAM-enhanced transmission for multimode short-range links

DEFF Research Database (Denmark)

Tatarczak, Anna; Usuga Castaneda, Mario A.; Tafur Monroy, Idelfonso

2015-01-01

We propose, experimentally demonstrate, and evaluate the performance of a multimode (MM) transmission fiber data link which is based on orbital angular momentum (OAM) modes. The proposed scheme uses OAM modes to increase capacity or reach without recurring to mode division multiplexing (MDM...

Percorsi linguistici e semiotici: Critical Multimodal Analysis of Digital Discourse

Directory of Open Access Journals (Sweden)

edited by Ilaria Moschini

2014-12-01

Full Text Available The language section of LEA - edited by Ilaria Moschini - is dedicated to the Critical Multimodal Analysis of Digital Discourse, an approach that encompasses the linguistic and semiotic detailed investigation of texts within a socio-cultural perspective. It features an interview with Professor Theo van Leeuwen by Ilaria Moschini and four essays: “Retwitting, reposting, repinning; reshaping identities online: Towards a social semiotic multimodal analysis of digital remediation” by Elisabetta Adami; “Multimodal aspects of corporate social responsibility communication” by Carmen Daniela Maier; “Pervasive Technologies and the Paradoxes of Multimodal Digital Communication” by Sandra Petroni and “Can the powerless speak? Linguistic and multimodal corporate media manipulation in digital environments: the case of Malala Yousafzai” by Maria Grazia Sindoni. 

Investigating multimodal communication in virtual meetings

DEFF Research Database (Denmark)

Persson, John Stouby; Mathiassen, Lars

2014-01-01

recordings of their oral exchanges and video recordings of their shared dynamic representation of the project’s status and plans, our analysis reveals how their interrelating of visual and verbal communication acts enabled effective communication and coordination. In conclusion, we offer theoretical......To manage distributed work, organizations increasingly rely on virtual meetings based on multimodal, synchronous communication technologies. However, despite technological advances, it is still challenging to coordinate knowledge through these meetings with spatial and cultural separation. Against...... propositions that explain how interrelating of verbal and visual acts based on shared dynamic representations enable communication repairs during virtual meetings. We argue the proposed framework provides researchers with a novel and practical approach to investigate the complex data involved in virtual...

Multimodality treatment strategies have changed prognosis of peritoneal metastases

Science.gov (United States)

Lungoci, Corneliu; Mironiuc, Aurel Ion; Muntean, Valentin; Oniu, Traian; Leebmann, Hubert; Mayr, Max; Piso, Pompiliu

2016-01-01

For a long time, treatment of peritoneal metastases (PM) was mostly palliative and thus, this status was link with “terminal status/despair”. The current multimodal treatment strategy, consisting of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC), has been strenuously achieved over time, but seems to be the best treatment option for PM patients. As we reviewed the literature data, we could emphasize some milestones and also, controversies in the history of proposed multimodal treatment and thus, outline the philosophy of this approach, which seems to be an unusual one indeed. Initially marked by nihilism and fear, but benefiting from a remarkable joint effort of human and material resources (multi-center and -institutional research), over a period of 30 years, CRS and HIPEC found their place in the treatment of PM. The next 4 years were dedicated to the refinement of the multimodal treatment, by launching research pathways. In selected patients, with requires training, it demonstrated a significant survival results (similar to the Hepatic Metastases treatment), with acceptable risks and costs. The main debates regarding CRS and HIPEC treatment were based on the oncologists’ perspective and the small number of randomized clinical trials. It is important to statement the PM patient has the right to be informed of the existence of CRS and HIPEC, as a real treatment resource, the decision being made by multidisciplinary teams. PMID:26798438

Multi-modal RGB–Depth–Thermal Human Body Segmentation

DEFF Research Database (Denmark)

Palmero, Cristina; Clapés, Albert; Bahnsen, Chris

2016-01-01

This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB-Depth-Thermal dataset along with a multi-modal seg- mentation baseline. The several modalities are registered us- ing a calibration...... to other state-of-the-art meth- ods, obtaining an overlap above 75% on the novel dataset when compared to the manually annotated ground-truth of human segmentations....

Multimodal Hyper-connectivity Networks for MCI Classification.

Science.gov (United States)

Li, Yang; Gao, Xinqiang; Jie, Biao; Yap, Pew-Thian; Kim, Min-Jeong; Wee, Chong-Yaw; Shen, Dinggang

2017-09-01

Hyper-connectivity network is a network where every edge is connected to more than two nodes, and can be naturally denoted using a hyper-graph. Hyper-connectivity brain network, either based on structural or functional interactions among the brain regions, has been used for brain disease diagnosis. However, the conventional hyper-connectivity network is constructed solely based on single modality data, ignoring potential complementary information conveyed by other modalities. The integration of complementary information from multiple modalities has been shown to provide a more comprehensive representation about the brain disruptions. In this paper, a novel multimodal hyper-network modelling method was proposed for improving the diagnostic accuracy of mild cognitive impairment (MCI). Specifically, we first constructed a multimodal hyper-connectivity network by simultaneously considering information from diffusion tensor imaging and resting-state functional magnetic resonance imaging data. We then extracted different types of network features from the hyper-connectivity network, and further exploited a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Our proposed multimodal hyper-connectivity network demonstrated a better MCI classification performance than the conventional single modality based hyper-connectivity networks.

Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems

Directory of Open Access Journals (Sweden)

Kryszczuk Krzysztof

2007-01-01

Full Text Available We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature and multimodal (speech and face systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.

Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

Science.gov (United States)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

2014-05-01

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

Patient-tailored multimodal neuroimaging, visualization and quantification of human intra-cerebral hemorrhage

Science.gov (United States)

Goh, Sheng-Yang M.; Irimia, Andrei; Vespa, Paul M.; Van Horn, John D.

2016-03-01

In traumatic brain injury (TBI) and intracerebral hemorrhage (ICH), the heterogeneity of lesion sizes and types necessitates a variety of imaging modalities to acquire a comprehensive perspective on injury extent. Although it is advantageous to combine imaging modalities and to leverage their complementary benefits, there are difficulties in integrating information across imaging types. Thus, it is important that efforts be dedicated to the creation and sustained refinement of resources for multimodal data integration. Here, we propose a novel approach to the integration of neuroimaging data acquired from human patients with TBI/ICH using various modalities; we also demonstrate the integrated use of multimodal magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data for TBI analysis based on both visual observations and quantitative metrics. 3D models of healthy-appearing tissues and TBIrelated pathology are generated, both of which are derived from multimodal imaging data. MRI volumes acquired using FLAIR, SWI, and T2 GRE are used to segment pathology. Healthy tissues are segmented using user-supervised tools, and results are visualized using a novel graphical approach called a `connectogram', where brain connectivity information is depicted within a circle of radially aligned elements. Inter-region connectivity and its strength are represented by links of variable opacities drawn between regions, where opacity reflects the percentage longitudinal change in brain connectivity density. Our method for integrating, analyzing and visualizing structural brain changes due to TBI and ICH can promote knowledge extraction and enhance the understanding of mechanisms underlying recovery.

Coherent noise reduction in digital holographic microscopy by averaging multiple holograms recorded with a multimode laser.

Science.gov (United States)

Pan, Feng; Yang, Lizhi; Xiao, Wen

2017-09-04

In digital holographic microscopy (DHM), it is undesirable to observe coherent noise in the reconstructed images. The sources of the noise are mainly the parasitic interference fringes caused by multiple reflections and the speckle pattern caused by the optical scattering on the object surface. Here we propose a noise reduction approach in DHM by averaging multiple holograms recorded with a multimode laser. Based on the periodicity of the temporal coherence of a multimode semiconductor laser, we acquire a series of holograms by changing the optical path length difference between the reference beam and object beam. Because of the use of low coherence light, we can remove the parasitic interference fringes caused by multiple reflections in the holograms. In addition, the coherent noise patterns change in this process due to the different optical paths. Therefore, the coherent noise can be reduced by averaging the multiple reconstructions with uncorrelated noise patterns. Several experiments have been carried out to validate the effectiveness of the proposed approach for coherent noise reduction in DHM. It is shown a remarkable improvement both in amplitude imaging quality and phase measurement accuracy.

Modality. Commitment, Truth Value and Reality Claims Across Modes in Multimodal Novels

DEFF Research Database (Denmark)

Nørgaard, Nina

2010-01-01

to the description and analysis of literary texts which – in addition to wording – make use of other semiotic modes such as typography, visual images, colour and layout for their meaning-making. The approach to multimodality deployed and examined is that proposed, for instance, by Kress and van Leeuwen (e.g. 1996...... to the analysis of two explicitly multimodal novels, with particular focus on the realisation of modality in visual images and typography. The texts put up for analysis are Alexander Masters’ Stuart. A Life Backwards and Jonathan Safran Foer’s Extremely Loud and Incredibly Close. While Kress and van Leeuwen...... of Masters’ and Foer’s sporadic use of special typography, in turn, reveals that although some of Kress and van Leeuwen’s modality parameters may be applicable to typography, the descriptive system is clearly less adequate in a typographic context where further work is needed before workable tools can...

Image evaluation of HIV encephalopathy: a multimodal approach using quantitative MR techniques

Energy Technology Data Exchange (ETDEWEB)

Prado, Paulo T.C.; Escorsi-Rosset, Sara [University of Sao Paulo, Radiology Section, Internal Medicine Department, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Cervi, Maria C. [University of Sao Paulo, Department of Pediatrics, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Santos, Antonio Carlos [University of Sao Paulo, Radiology Section, Internal Medicine Department, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Hospital das Clinicas da FMRP-USP, Ribeirao Preto, SP (Brazil)

2011-11-15

A multimodal approach of the human immunodeficiency virus (HIV) encephalopathy using quantitative magnetic resonance (MR) techniques can demonstrate brain changes not detectable only with conventional magnetic resonance imaging (MRI). The aim of this study was to compare conventional MRI and MR quantitative techniques, such as magnetic resonance spectroscopy (MRS) and relaxometry and to determine whether quantitative techniques are more sensitive than conventional imaging for brain changes caused by HIV infection. We studied prospectively nine HIV positive children (mean age 6 years, from 5 to 8 years old) and nine controls (mean age 7.3 years; from 3 to 10 years), using MRS and relaxometry. Examinations were carried on 1.5-T equipment. HIV-positive patients presented with only minor findings and all control patients had normal conventional MR findings. MRS findings showed an increase in choline to creatine (CHO/CRE) ratios bilaterally in both frontal gray and white matter, in the left parietal white matter, and in total CHO/CRE ratio. In contrast, N-acetylaspartate to creatine (NAA/CRE) ratios did not present with any significant difference between both groups. Relaxometry showed significant bilateral abnormalities, with lengthening of the relaxation time in HIV positive in many regions. Conventional MRI is not sensitive for early brain changes caused by HIV infection. Quantitative techniques such as MRS and relaxometry appear as valuable tools in the diagnosis of these early changes. Therefore, a multimodal quantitative study can be useful in demonstrating and understanding the physiopathology of the disease. (orig.)

ANALYSIS OF MULTIMODAL FUSION TECHNIQUES FOR AUDIO-VISUAL SPEECH RECOGNITION

Directory of Open Access Journals (Sweden)

D.V. Ivanko

2016-05-01

Full Text Available The paper deals with analytical review, covering the latest achievements in the field of audio-visual (AV fusion (integration of multimodal information. We discuss the main challenges and report on approaches to address them. One of the most important tasks of the AV integration is to understand how the modalities interact and influence each other. The paper addresses this problem in the context of AV speech processing and speech recognition. In the first part of the review we set out the basic principles of AV speech recognition and give the classification of audio and visual features of speech. Special attention is paid to the systematization of the existing techniques and the AV data fusion methods. In the second part we provide a consolidated list of tasks and applications that use the AV fusion based on carried out analysis of research area. We also indicate used methods, techniques, audio and video features. We propose classification of the AV integration, and discuss the advantages and disadvantages of different approaches. We draw conclusions and offer our assessment of the future in the field of AV fusion. In the further research we plan to implement a system of audio-visual Russian continuous speech recognition using advanced methods of multimodal fusion.

Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

Directory of Open Access Journals (Sweden)

Dane Brown

2017-07-01

Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

Concepts for space nuclear multi-mode reactors

International Nuclear Information System (INIS)

Myrabo, L.; Botts, T.E.; Powell, J.R.

1983-01-01

A number of nuclear multi-mode reactor power plants are conceptualized for use with solid core, fixed particle bed and rotating particle bed reactors. Multi-mode systems generate high peak electrical power in the open cycle mode, with MHD generator or turbogenerator converters and cryogenically stored coolants. Low level stationkeeping power and auxiliary reactor cooling (i.e., for the removal of reactor afterheat) are provided in a closed cycle mode. Depending on reactor design, heat transfer to the low power converters can be accomplished by heat pipes, liquid metal coolants or high pressure gas coolants. Candidate low power conversion cycles include Brayton turbogenerator, Rankine turbogenerator, thermoelectric and thermionic approaches. A methodology is suggested for estimating the system mass of multi-mode nuclear power plants as a function of peak electric power level and required mission run time. The masses of closed cycle nuclear and open cycle chemical power systems are briefly examined to identify the regime of superiority for nuclear multi-mode systems. Key research and technology issues for such power plants are also identified

A Quantitative and Systematic Methodology to Investigate Energy Consumption Issues in Multimodal Intercity Transportation Systems

Directory of Open Access Journals (Sweden)

Lili Du

2015-09-01

Full Text Available Energy issues in transportation systems have garnered increasing attention recently. This study proposes a systematic methodology for policy-makers to minimize energy consumption in multimodal intercity transportation systems considering suppliers’ operational constraints and travelers’ mobility requirements. A bi-level optimization model is developed for this purpose and considers the air, rail, private auto, and transit modes. The upper-level model is a mixed integer nonlinear program aiming to minimize energy consumption subject to transportation suppliers’ operational constraints and traffic demand distribution to paths resulting from the lower-level model. The lower-level model is a linear program seeking to maximize the trip utilities of travelers. The interactions between the multimodal transportation suppliers and intercity traffic demand are considered under the goal of minimizing system energy consumption. The proposed bi-level mixed integer model is relaxed and transformed into a mathematical program with complementarity constraints, and solved using a customized branch-and-bound algorithm. Numerical experiments, conducted using multimodal travel options between Lafayette, Indiana and Washington, D.C. reiterate that shifting traffic demand from private cars to the transit and rail modes significantly reduce energy consumption. Moreover, the proposed methodology provides tools to quantitatively analyze system energy consumption and traffic demand distribution among transportation modes under specific policy instruments. The results illustrate the need to systematically incorporate the interactions among traveler preferences, network structure, and supplier operational schemes to provide policy-makers insights for developing traffic demand shift mechanisms to minimize system energy consumption. Hence, the proposed methodology provide policy-makers the capability to analyze energy consumption in the transportation sector by a

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

Science.gov (United States)

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Design and Applications of a Multimodality Image Data Warehouse Framework

Science.gov (United States)

Wong, Stephen T.C.; Hoo, Kent Soo; Knowlton, Robert C.; Laxer, Kenneth D.; Cao, Xinhau; Hawkins, Randall A.; Dillon, William P.; Arenson, Ronald L.

2002-01-01

A comprehensive data warehouse framework is needed, which encompasses imaging and non-imaging information in supporting disease management and research. The authors propose such a framework, describe general design principles and system architecture, and illustrate a multimodality neuroimaging data warehouse system implemented for clinical epilepsy research. The data warehouse system is built on top of a picture archiving and communication system (PACS) environment and applies an iterative object-oriented analysis and design (OOAD) approach and recognized data interface and design standards. The implementation is based on a Java CORBA (Common Object Request Broker Architecture) and Web-based architecture that separates the graphical user interface presentation, data warehouse business services, data staging area, and backend source systems into distinct software layers. To illustrate the practicality of the data warehouse system, the authors describe two distinct biomedical applications—namely, clinical diagnostic workup of multimodality neuroimaging cases and research data analysis and decision threshold on seizure foci lateralization. The image data warehouse framework can be modified and generalized for new application domains. PMID:11971885

An Efficient Human Identification through MultiModal Biometric System

Directory of Open Access Journals (Sweden)

K. Meena

Full Text Available ABSTRACT Human identification is essential for proper functioning of society. Human identification through multimodal biometrics is becoming an emerging trend, and one of the reasons is to improve recognition accuracy. Unimodal biometric systems are affected by various problemssuch as noisy sensor data,non-universality, lack of individuality, lack of invariant representation and susceptibility to circumvention.A unimodal system has limited accuracy. Hence, Multimodal biometric systems by combining more than one biometric feature in different levels are proposed in order to enhance the performance of the system. A supervisor module combines the different opinions or decisions delivered by each subsystem and then make a final decision. In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. Biometric features are extracted by Local Derivative Ternary Pattern (LDTP in Contourlet domain and an extensive evaluation of LDTP is done using Support Vector Machine and Nearest Neighborhood Classifier. The experimental evaluations are performed on a public dataset demonstrating the accuracy of the proposed system compared with the existing systems. It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time.

Recognition of emotions using multimodal physiological signals and an ensemble deep learning model.

Science.gov (United States)

Yin, Zhong; Zhao, Mengyuan; Wang, Yongxiong; Yang, Jingdong; Zhang, Jianhua

2017-03-01

Using deep-learning methodologies to analyze multimodal physiological signals becomes increasingly attractive for recognizing human emotions. However, the conventional deep emotion classifiers may suffer from the drawback of the lack of the expertise for determining model structure and the oversimplification of combining multimodal feature abstractions. In this study, a multiple-fusion-layer based ensemble classifier of stacked autoencoder (MESAE) is proposed for recognizing emotions, in which the deep structure is identified based on a physiological-data-driven approach. Each SAE consists of three hidden layers to filter the unwanted noise in the physiological features and derives the stable feature representations. An additional deep model is used to achieve the SAE ensembles. The physiological features are split into several subsets according to different feature extraction approaches with each subset separately encoded by a SAE. The derived SAE abstractions are combined according to the physiological modality to create six sets of encodings, which are then fed to a three-layer, adjacent-graph-based network for feature fusion. The fused features are used to recognize binary arousal or valence states. DEAP multimodal database was employed to validate the performance of the MESAE. By comparing with the best existing emotion classifier, the mean of classification rate and F-score improves by 5.26%. The superiority of the MESAE against the state-of-the-art shallow and deep emotion classifiers has been demonstrated under different sizes of the available physiological instances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Testing nonclassicality in multimode fields: A unified derivation of classical inequalities

International Nuclear Information System (INIS)

Miranowicz, Adam; Bartkowiak, Monika; Wang Xiaoguang; Liu Yuxi; Nori, Franco

2010-01-01

We consider a way to generate operational inequalities to test nonclassicality (or quantumness) of multimode bosonic fields (or multiparty bosonic systems) that unifies the derivation of many known inequalities and allows to propose new ones. The nonclassicality criteria are based on Vogel's criterion corresponding to analyzing the positivity of multimode P functions or, equivalently, the positivity of matrices of expectation values of, e.g., creation and annihilation operators. We analyze not only monomials but also polynomial functions of such moments, which can sometimes enable simpler derivations of physically relevant inequalities. As an example, we derive various classical inequalities which can be violated only by nonclassical fields. In particular, we show how the criteria introduced here easily reduce to the well-known inequalities describing (a) multimode quadrature squeezing and its generalizations, including sum, difference, and principal squeezing; (b) two-mode one-time photon-number correlations, including sub-Poisson photon-number correlations and effects corresponding to violations of the Cauchy-Schwarz and Muirhead inequalities; (c) two-time single-mode photon-number correlations, including photon antibunching and hyperbunching; and (d) two- and three-mode quantum entanglement. Other simple inequalities for testing nonclassicality are also proposed. We have found some general relations between the nonclassicality and entanglement criteria, in particular those resulting from the Cauchy-Schwarz inequality. It is shown that some known entanglement inequalities can be derived as nonclassicality inequalities within our formalism, while some other known entanglement inequalities can be seen as sums of more than one inequality derived from the nonclassicality criterion. This approach enables a deeper analysis of the entanglement for a given nonclassicality.

A novel multimode hybrid energy storage system and its energy management strategy for electric vehicles

Science.gov (United States)

Wang, Bin; Xu, Jun; Cao, Binggang; Zhou, Xuan

2015-05-01

This paper proposes a novel topology of multimode hybrid energy storage system (HESS) and its energy management strategy for electric vehicles (EVs). Compared to the conventional HESS, the proposed multimode HESS has more operating modes and thus it could in further enhance the efficiency of the system. The rule-based control strategy and the power-balancing strategy are developed for the energy management strategy to realize mode selection and power distribution. Generally, the DC-DC converter will operate at peak efficiency to convey the energy from the batteries to the UCs. Otherwise, the pure battery mode or the pure ultracapacitors (UCs) mode will be utilized without the DC-DC converter. To extend the battery life, the UCs have the highest priority to recycle the energy and the batteries are isolated from being recharged directly during regenerative braking. Simulations and experiments are established to validate the proposed multimode HESS and its energy management strategy. The results reveal that the energy losses in the DC-DC converter, the total energy consumption and the overall system efficiency of the proposed multimode HESS are improved compared to the conventional HESS.

MODELING PARTICLE SIZE DISTRIBUTION IN HETEROGENEOUS POLYMERIZATION SYSTEMS USING MULTIMODAL LOGNORMAL FUNCTION

Directory of Open Access Journals (Sweden)

J. C. Ferrari

Full Text Available Abstract This work evaluates the usage of the multimodal lognormal function to describe Particle Size Distributions (PSD of emulsion and suspension polymerization processes, including continuous reactions with particle re-nucleation leading to complex multimodal PSDs. A global optimization algorithm, namely Particle Swarm Optimization (PSO, was used for parameter estimation of the proposed model, minimizing the objective function defined by the mean squared errors. Statistical evaluation of the results indicated that the multimodal lognormal function could describe distinctive features of different types of PSDs with accuracy and consistency.

Multi-mode operations for on-line uninterruptible power supply

DEFF Research Database (Denmark)

Lu, Jinghang; Savaghebi, Mehdi; Guan, Yajuan

2018-01-01

In this paper, the multi-mode operation of the on-line UPS system is investigated and corresponding control strategies are proposed. The proposed control strategies are able to achieve the seamless transition in traditional normal mode, PV-aided normal mode, enhanced eco-mode and burn-in test mod...

Scenemash: multimodal route summarization for city exploration

NARCIS (Netherlands)

Berg, J. van den; Rudinac, S.; Worring, M.

2016-01-01

The potential of mining tourist information from social multimedia data gives rise to new applications offering much richer impressions of the city. In this paper we propose Scenemash, a system that generates multimodal summaries of multiple alternative routes between locations in a city. To get

An agent-based architecture for multimodal interaction

NARCIS (Netherlands)

Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

An agent-based architecture for multimodal interaction

NARCIS (Netherlands)

Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

2001-01-01

In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

Teleportation of continuous variable multimode Greeberger-Horne-Zeilinger entangled states

International Nuclear Information System (INIS)

He Guangqiang; Zhang Jingtao; Zeng Guihua

2008-01-01

Quantum teleportation protocols of continuous variable (CV) Greeberger-Horne-Zeilinger (GHZ) and Einstein-Podolsky-Rosen (EPR) entangled states are proposed, and are generalized to teleportation of arbitrary multimode GHZ entangled states described by Van Loock and Braunstein (2000 Phys. Rev. Lett. 84 3482). Each mode of a multimode entangled state is teleported using a CV EPR entangled pair and classical communication. The analytical expression of fidelity for the multimode Gaussian states which evaluates the teleportation quality is presented. The analytical results show that the fidelity is a function of both the squeezing parameter r, which characterizes the multimode entangled state to be teleported, and the channel parameter p, which characterizes the EPR pairs shared by Alice and Bob. The fidelity increases with increasing p, but decreases with increasing r, i.e., it is more difficult to teleport the more perfect multimode entangled states. The entanglement degree of the teleported multimode entangled states increases with increasing both r and p. In addition, the fact is proved that our teleportation protocol of EPR entangled states using parallel EPR pairs as quantum channels is the best case of the protocol using four-mode entangled states (Adhikari et al 2008 Phys. Rev. A 77 012337).

Influence of Blood Contamination During Multimode Adhesive ...

African Journals Online (AJOL)

2018-01-30

Jan 30, 2018 ... (μTBS) of multimode adhesives to dentin when using the self‑etch approach. Materials and Methods: ... adhesion, the collagen fibers collapse during the. Introduction ..... The failure mode was determined using an optical.

Advanced Multimodal Solutions for Information Presentation

Science.gov (United States)

Wenzel, Elizabeth M.; Godfroy-Cooper, Martine

2018-01-01

possible solution, adaptive systems have been proposed in which the information presented to the user changes as a function of taskcontext-dependent factors. However, this presupposes that adequate methods for detecting andor predicting such factors are developed. Further, research in adaptive systems for aviation suggests that they can sometimes serve to increase workload and reduce situational awareness. It will be critical to develop multimodal display guidelines that include consideration of smart systems that can select the best display method for a particular contextsituation.The scope of the current work is an analysis of potential multimodal display technologies for long duration missions and, in particular, will focus on their potential role in EVA activities. The review will address multimodal (combined visual, auditory andor tactile) displays investigated by NASA, industry, and DoD (Dept. of Defense). It also considers the need for adaptive information systems to accommodate a variety of operational contexts such as crew status (e.g., fatigue, workload level) and task environment (e.g., EVA, habitat, rover, spacecraft). Current approaches to guidelines and best practices for combining modalities for the most effective information displays are also reviewed. Potential issues in developing interface guidelines for the Exploration Information System (EIS) are briefly considered.

Multimodal biometric system using rank-level fusion approach.

Science.gov (United States)

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

Super-Gaussian, super-diffusive transport of multi-mode active matter

OpenAIRE

Hahn, Seungsoo; Song, Sanggeun; Kim, Dae Hyun; Yang, Gil-Suk; Lee, Kang Taek; Sung, Jaeyoung

2017-01-01

Living cells exhibit multi-mode transport that switches between an active, self-propelled motion and a seemingly passive, random motion. Cellular decision-making over transport mode switching is a stochastic process that depends on the dynamics of the intracellular chemical network regulating the cell migration process. Here, we propose a theory and an exactly solvable model of multi-mode active matter. Our exact model study shows that the reversible transition between a passive mode and an a...

Simplified Multimodal Biometric Identification

Directory of Open Access Journals (Sweden)

Abhijit Shete

2014-03-01

Full Text Available Multibiometric systems are expected to be more reliable than unimodal biometric systems for personal identification due to the presence of multiple, fairly independent pieces of evidence e.g. Unique Identification Project "Aadhaar" of Government of India. In this paper, we present a novel wavelet based technique to perform fusion at the feature level and score level by considering two biometric modalities, face and fingerprint. The results indicate that the proposed technique can lead to substantial improvement in multimodal matching performance. The proposed technique is simple because of no preprocessing of raw biometric traits as well as no feature and score normalization.

Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon

Science.gov (United States)

Ashok, Praveen C.; Praveen, Bavishna B.; Bellini, Nicola; Riches, Andrew; Dholakia, Kishan; Herrington, C. Simon

2013-01-01

We report a multimodal optical approach using both Raman spectroscopy and optical coherence tomography (OCT) in tandem to discriminate between colonic adenocarcinoma and normal colon. Although both of these non-invasive techniques are capable of discriminating between normal and tumour tissues, they are unable individually to provide both the high specificity and high sensitivity required for disease diagnosis. We combine the chemical information derived from Raman spectroscopy with the texture parameters extracted from OCT images. The sensitivity obtained using Raman spectroscopy and OCT individually was 89% and 78% respectively and the specificity was 77% and 74% respectively. Combining the information derived using the two techniques increased both sensitivity and specificity to 94% demonstrating that combining complementary optical information enhances diagnostic accuracy. These data demonstrate that multimodal optical analysis has the potential to achieve accurate non-invasive cancer diagnosis. PMID:24156073

An Efficient Quality-Related Fault Diagnosis Method for Real-Time Multimode Industrial Process

Directory of Open Access Journals (Sweden)

Kaixiang Peng

2017-01-01

Full Text Available Focusing on quality-related complex industrial process performance monitoring, a novel multimode process monitoring method is proposed in this paper. Firstly, principal component space clustering is implemented under the guidance of quality variables. Through extraction of model tags, clustering information of original training data can be acquired. Secondly, according to multimode characteristics of process data, the monitoring model integrated Gaussian mixture model with total projection to latent structures is effective after building the covariance description form. The multimode total projection to latent structures (MTPLS model is the foundation of problem solving about quality-related monitoring for multimode processes. Then, a comprehensive statistics index is defined which is based on the posterior probability of the monitored samples belonging to each Gaussian component in the Bayesian theory. After that, a combined index is constructed for process monitoring. Finally, motivated by the application of traditional contribution plot in fault diagnosis, a gradient contribution rate is applied for analyzing the variation of variable contribution rate along samples. Our method can ensure the implementation of online fault monitoring and diagnosis for multimode processes. Performances of the whole proposed scheme are verified in a real industrial, hot strip mill process (HSMP compared with some existing methods.

Multimodality and Ambient Intelligence

NARCIS (Netherlands)

Nijholt, Antinus; Verhaegh, W.; Aarts, E.; Korst, J.

2004-01-01

In this chapter we discuss multimodal interface technology. We present eexamples of multimodal interfaces and show problems and opportunities. Fusion of modalities is discussed and some roadmap discussions on research in multimodality are summarized. This chapter also discusses future developments

MULTIMODAL FEEDBACK PROVISION IN IMPROVING PRE-SERVICE TEACHERS’ COMPETENCE

Directory of Open Access Journals (Sweden)

Fazri Nur Yusuf

2017-09-01

Full Text Available Studies on potentials of feedback over English language teaching seem not to have not been well-revealed, including studies on the use of feedback to improve English pre-service teachers’ competence. The present study investigates to what extent a multimodal feedback can influence pre-service teachers’ teaching, and which teaching aspects are influenced. Twenty five pre-service teachers taking Microteaching Course served as respondents supervised by a course advisor. The data were collected by teacher observation in a rating-scale form, self-appraisal, and interviews. The data were analyzed by using correlated sample t-test and the eight teaching components proposed by Brown (2001. The results showed that after multimodal feedback provision, pre-service teachers indicated an improvement significantly in seven out of eight teaching aspects. The provision of multimodal feedback could improve their teaching competence on preparation, instructional objective elicitation, mastery of instructional materials, use of media, and classroom management, including classroom language. But, the results do not indicate that they perform well on reflection and follow-up due to some reasons. In addition, the results evince that multimodal feedback provision could improve pre-service teachers’ pedagogical competence when the multimodal feedback is integrated with content, interpersonal relationship, and management.

Multimodality imaging of the postoperative shoulder

Energy Technology Data Exchange (ETDEWEB)

Woertler, Klaus [Technische Universitaet Muenchen, Department of Radiology, Munich (Germany)

2007-12-15

Multimodality imaging of the postoperative shoulder includes radiography, magnetic resonance (MR) imaging, MR arthrography, computed tomography (CT), CT arthrography, and ultrasound. Target-oriented evaluation of the postoperative shoulder necessitates familiarity with surgical techniques, their typical complications and sources of failure, knowledge of normal and abnormal postoperative findings, awareness of the advantages and weaknesses with the different radiologic techniques, and clinical information on current symptoms and function. This article reviews the most commonly used surgical procedures for treatment of anterior glenohumeral instability, lesions of the labral-bicipital complex, subacromial impingement, and rotator cuff lesions and highlights the significance of imaging findings with a view to detection of recurrent lesions and postoperative complications in a multimodality approach. (orig.)

Multimodality and children's participation in classrooms: Instances of ...

African Journals Online (AJOL)

Multimodality and children's participation in classrooms: Instances of research. ... deficit models of children, drawing on their everyday experiences and their existing ... It outlines the theoretical framework supporting the pedagogical approach, ...

Interactive multimodal ambulatory monitoring to investigate the association between physical activity and affect

Directory of Open Access Journals (Sweden)

Ulrich W. Ebner-Priemer

2013-01-01

Full Text Available Although there is a wealth of evidence that physical activity has positive effects on psychological health, a large proportion of people are inactive. Data regarding counts, steps, and movement patterns are limited in their ability to explain why people remain inactive. We propose that multimodal ambulatory monitoring, which combines the assessment of physical activity with the assessment of psychological variables, helps to elucidate real world physical activity. Whereas physical activity can be monitored continuously, psychological variables can only be assessed at discrete intervals, such as every hour. Moreover, the assessment of psychological variables must be linked to the activity of interest. For example, if an inactive and overweight person is physically active once a week, psychological variables should be assessed during this episode. Linking the assessment of psychological variables to episodes of an activity of interest can be achieved with interactive monitoring. The primary aim of our interactive multimodal ambulatory monitoring approach was to intentionally increase the number of e-diary assessments during active episodes.We developed and tested an interactive monitoring algorithm that continuously monitors physical activity in everyday life. When predefined thresholds are surpassed, the algorithm triggers a signal for participants to answer questions in their electronic diary.Using data from 70 participants wearing an accelerative device for 24 hours each, we found that our algorithm quadrupled the frequency of e-diary assessments during the activity episodes of interest compared to random sampling. Multimodal interactive ambulatory monitoring appears to be a promising approach to enhancing our understanding of real world physical activity and movement.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Science.gov (United States)

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging

Design, Performance and Optimization for Multimodal Radar Operation

Directory of Open Access Journals (Sweden)

Surendra S. Bhat

2012-09-01

Full Text Available This paper describes the underlying methodology behind an adaptive multimodal radar sensor that is capable of progressively optimizing its range resolution depending upon the target scattering features. It consists of a test-bed that enables the generation of linear frequency modulated waveforms of various bandwidths. This paper discusses a theoretical approach to optimizing the bandwidth used by the multimodal radar. It also discusses the various experimental results obtained from measurement. The resolution predicted from theory agrees quite well with that obtained from experiments for different target arrangements.

A Multimodal Imaging Approach for Longitudinal Evaluation of Bladder Tumor Development in an Orthotopic Murine Model.

Directory of Open Access Journals (Sweden)

Chantal Scheepbouwer

Full Text Available Bladder cancer is the fourth most common malignancy amongst men in Western industrialized countries with an initial response rate of 70% for the non-muscle invasive type, and improving therapy efficacy is highly needed. For this, an appropriate, reliable animal model is essential to gain insight into mechanisms of tumor growth for use in response monitoring of (new agents. Several animal models have been described in previous studies, but so far success has been hampered due to the absence of imaging methods to follow tumor growth non-invasively over time. Recent developments of multimodal imaging methods for use in animal research have substantially strengthened these options of in vivo visualization of tumor growth. In the present study, a multimodal imaging approach was addressed to investigate bladder tumor proliferation longitudinally. The complementary abilities of Bioluminescence, High Resolution Ultrasound and Photo-acoustic Imaging permit a better understanding of bladder tumor development. Hybrid imaging modalities allow the integration of individual strengths to enable sensitive and improved quantification and understanding of tumor biology, and ultimately, can aid in the discovery and development of new therapeutics.

Object recognition through a multi-mode fiber

Science.gov (United States)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

Directory of Open Access Journals (Sweden)

Ku-young Chung

2017-07-01

Full Text Available Polysomnography (PSG is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Multimodal medical information retrieval with unsupervised rank fusion.

Science.gov (United States)

Mourão, André; Martins, Flávio; Magalhães, João

2015-01-01

Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical. Copyright © 2014 Elsevier Ltd. All rights reserved.

Source signature estimation from multimode surface waves via mode-separated virtual real source method

Science.gov (United States)

Gao, Lingli; Pan, Yudi

2018-05-01

The correct estimation of the seismic source signature is crucial to exploration geophysics. Based on seismic interferometry, the virtual real source (VRS) method provides a model-independent way for source signature estimation. However, when encountering multimode surface waves, which are commonly seen in the shallow seismic survey, strong spurious events appear in seismic interferometric results. These spurious events introduce errors in the virtual-source recordings and reduce the accuracy of the source signature estimated by the VRS method. In order to estimate a correct source signature from multimode surface waves, we propose a mode-separated VRS method. In this method, multimode surface waves are mode separated before seismic interferometry. Virtual-source recordings are then obtained by applying seismic interferometry to each mode individually. Therefore, artefacts caused by cross-mode correlation are excluded in the virtual-source recordings and the estimated source signatures. A synthetic example showed that a correct source signature can be estimated with the proposed method, while strong spurious oscillation occurs in the estimated source signature if we do not apply mode separation first. We also applied the proposed method to a field example, which verified its validity and effectiveness in estimating seismic source signature from shallow seismic shot gathers containing multimode surface waves.

A multimodal physical therapy approach to the management of a patient with temporomandibular dysfunction and head and neck lymphedema: a case report.

Science.gov (United States)

Crane, Patricia; Feinberg, Lauren; Morris, John

2015-02-01

There is a paucity of research that investigates therapeutic interventions of patients with concurrent head and neck lymphedema and temporomandibular dysfunction (TMD). The purpose of this case report is to describe the management and outcomes of a patient with head and neck lymphedema and TMD using a multimodal physical therapy approach. A 74-year-old male with a past medical history of head and neck lymphedema and TMD was referred to physical therapy with chief complaints of inability to open his mouth in order to eat solid food, increased neck lymphedema, temporomadibular joint pain, and inability to speak for prolonged periods of time. The patient was treated for three visits over 4 weeks. Treatment included complete decongestive therapy (CDT), manual therapy, therapeutic exercise, and a home exercise program. Upon discharge, the patient had improved mandibular depression, decreased head and neck lymphedema, improved deep neck flexor endurance, decreased pain, and improved function on the Patient Specific Functional Scale (PSFS). Utilization of a multimodal physical therapy approach to treat a patient with a complex presentation yielded positive outcomes. Further research on outcomes and treatment approaches in patients with TMD and head and neck lymphedema is warranted.

Experimental evaluation of user performance in a pursuit tracking task with multimodal feedback

Directory of Open Access Journals (Sweden)

Obrenović Željko

2004-01-01

Full Text Available In this paper we describe the results of experimental evaluation of user performance in a pursuit-tracking task with multimodal feedback. Our experimental results indicate that audio can significantly improve the accuracy of pursuit tracking. Experiments with 19 participants have shown that addition of acoustic modalities reduces the error during pursuit tracking for up to 19%. Moreover, experiments indicated the existence of perceptual boundaries of multimodal HCI for different scene complexity and target speeds. We have also shown that the most appealing paradigms are not the most effective ones, which necessitates a careful quantitative analysis of proposed multimodal HCI paradigms.

Multimodal approaches including three-dimensional conformal re-irradiation for recurrent or persistent esophageal cancer. Preliminary results

International Nuclear Information System (INIS)

Yamaguchi, Shinsaku; Ohguri, Takayuki; Imada, Hajime

2011-01-01

The purpose of this study was to assess the toxicity and efficacy of multimodal approaches, including three-dimensional conformal re-irradiation, for patients with recurrent or persistent esophageal cancer after radiotherapy. Thirty-one patients with esophageal cancer treated with three-dimensional conformal re-irradiation were retrospectively analyzed. Of the 31 patients, 27 patients received concurrent chemotherapy, and 14 patients underwent regional hyperthermia during the re-irradiation. We divided the patients into two groups on the basis of their clinical condition: the curative group (n=11) or the palliative group (n=20). Severe toxicities were detected in one patient with Grade 3 esophageal perforation in the curative group, and 5 patients had a Grade 3 or higher toxicity of the esophagus in the palliative group. Advanced T stage at the time of re-irradiation was found to be significantly correlated with Grade 3 or higher toxicity in the esophagus. For the curative group, 10 (91%) of 11 patients had an objective response. For the palliative group, symptom relief was recognized in 8 (57%) of 14 patients with obvious swallowing difficulty. In conclusion, in the curative group with early-stage recurrent or persistent esophageal cancer, the multimodal approaches, including three-dimensional conformal re-irradiation, may be feasible, showing acceptable toxicity and a potential value of promising results, although further evaluations especially for the toxicities of the organs at risk are required. In the palliative group, the benefit of our therapy may be restrictive because severe esophageal toxicities were not uncommon in the patients with advanced T stage at the time of re-irradiation. (author)

Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

Directory of Open Access Journals (Sweden)

Yong Yang

2014-01-01

Full Text Available Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT, the fast discrete curvelet transform (FDCT, and the dual tree complex wavelet transform (DTCWT based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

Construction of Common Interpretive Spaces through Intertextual Loops--How Teachers Interpret Multimodal Learning Materials

Science.gov (United States)

Poyas, Yael; Eilam, Billie

2012-01-01

This study draws on several theoretical domains: intertextuality, multimodality, and the pedagogy of multiliteracies. We introduced multimodal textbook materials to eleven experienced teachers and examined, through in-depth interviews, their approach to juxtapositions of literary texts and visual artwork. Our analysis revealed (a) three attitudes…

[Multimodal medical image registration using cubic spline interpolation method].

Science.gov (United States)

He, Yuanlie; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

2007-12-01

Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.

Study on multimodal transport route under low carbon background

Science.gov (United States)

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.

Context-Aware Multimodal FIDO Authenticator for Sustainable IT Services

Directory of Open Access Journals (Sweden)

Seung-Hyun Kim

2018-05-01

Full Text Available Existing sustainable IT services have several problems related to user authentication such as the inefficiency of managing the system security, low security, and low usability. In this paper, we propose a Fast IDentity Online (FIDO authenticator that performs continuous authentication with implicit authentication based on user context and multimodal authentication. The proposed FIDO authenticator, a context-aware multimodal FIDO authentication (CAMFA method, combines information such as the user context, state of the mobile device, and user biometrics, then applies implicit and explicit authentication methods to meet the level of authentication required by the service provider. This reduces the user’s explicit authentication burden and continually authenticates users at risk during the session. Moreover, it is able to respond to attacks such as the theft of the authentication method or session hijacking. To study the effectiveness of CAMFA, we ran a user study by collecting data from 22 participants over 42 days of activity on a practical Android platform. The result of the user study demonstrates that the number of explicit authentication requests could be reduced by half. Based on the results of this study, an advanced user authentication that provides multimodal and continuous authentication could be applied to sustainable IT services.

Quantitative multimodality imaging in cancer research and therapy.

Science.gov (United States)

Yankeelov, Thomas E; Abramson, Richard G; Quarles, C Chad

2014-11-01

Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.

Elimination of mode coupling in multimode continuous-variable key distribution

International Nuclear Information System (INIS)

Filip, Radim; Mista, Ladislav; Marek, Petr

2005-01-01

A multimode channel can be utilized to substantially increase the capacity of quantum continuous-variable key distribution. Beyond losses in the channel, an uncontrollable coupling between the modes of the channel typically degrades the capacity of multimode channels. For the key distribution protocol with simultaneous measurement of both complementary quadratures we propose a feasible method to eliminate any undesirable mode coupling by only the receiver's appropriate measurement and data manipulation. It can be used to substantially increase the capacity of the channel, which has an important application in practical continuous-variable quantum cryptography

Multimodality

DEFF Research Database (Denmark)

Buhl, Mie

2010-01-01

In this paper, I address an ongoing discussion in Danish E-learning research about how to take advantage of the fact that digital media facilitate other communication forms than text, so-called ‘multimodal' communication, which should not be confused with the term ‘multimedia'. While multimedia...... on their teaching and learning situations. The choices they make involve e-learning resources like videos, social platforms and mobile devices, not just as digital artefacts we interact with, but the entire practice of using digital media. In a life-long learning perspective, multimodality is potentially very...

Multimodal imaging in health, disease, and man-made disasters

International Nuclear Information System (INIS)

Papineni, Rao V.L.

2012-01-01

Significant advances in the fields of molecular and functional imaging are rapidly emerging as potential advance research tools in health, Disease and drug discovery. Notable are the approaches utilizing multi-modal imaging strategies in preclinical studies that are becoming extremely useful in assessing the efficacy of the novel target molecules. This talk will focus on our efforts in bringing the multimodality to preclinical research with Optical, X-ray, and noninvasive nuclear imaging. The concepts and methods in molecular imaging to support drug targeting and drug discovery will be discussed along with a focus on its utilization in radiation induced changes in the bone physiology. Also, will discuss how such approaches can be employed in future as a biodosimetry for radiation disasters or in radiation threat. (author)

Reading Multimodal Texts for Learning – a Model for Cultivating Multimodal Literacy

Directory of Open Access Journals (Sweden)

Kristina Danielsson

2016-08-01

Full Text Available The re-conceptualisation of texts over the last 20 years, as well as the development of a multimodal understanding of communication and representation of knowledge, has profound consequences for the reading and understanding of multimodal texts, not least in educational contexts. However, if teachers and students are given tools to “unwrap” multimodal texts, they can develop a deeper understanding of texts, information structures, and the textual organisation of knowledge. This article presents a model for working with multimodal texts in education with the intention to highlight mutual multimodal text analysis in relation to the subject content. Examples are taken from a Singaporean science textbook as well as a Chilean science textbook, in order to demonstrate that the framework is versatile and applicable across different cultural contexts. The model takes into account the following aspects of texts: the general structure, how different semiotic resources operate, the ways in which different resources are combined (including coherence, the use of figurative language, and explicit/implicit values. Since learning operates on different dimensions – such as social and affective dimensions besides the cognitive ones – our inclusion of figurative language and values as components for textual analysis is a contribution to multimodal text analysis for learning.

Multimode-singlemode-multimode optical fiber sensor coated with novolac resin for detecting liquid phase alcohol

Science.gov (United States)

Marfu'ah, Amalia, Niza Rosyda; Hatta, Agus Muhamad; Pratama, Detak Yan

2018-04-01

Alcohol sensor based on multimode-singlemode-multimode (MSM) optical fiber with novolac resin as the external medium is proposed and demonstrated experimentally. Novolac resin swells when it is exposed by the alcohol. This effect causes a change in the polymer density leading to the refractive index's variation. The transmission light of the sensor depends on the refractive index of external medium. Based on the results, alcohol sensor based on MSM optical fiber structure using novolac resin has a higher sensitivity compared to the sensor without using novolac resin in the mixture of alcohol and distilled water. Alcohol sensor based on MSM optical fiber structure using novolac resin in the mixture of alcohol and distilled water with a singlemode fiber length of 5 mm has a sensitivity of 0.028972 dBm per % V/V, and in the mixture of alcohol and sugar solution of 10% w/w has a sensitivity of 0.005005 dBm per % V/V.

Evaluation of multimodal ground cues

DEFF Research Database (Denmark)

Nordahl, Rolf; Lecuyer, Anatole; Serafin, Stefania

2012-01-01

This chapter presents an array of results on the perception of ground surfaces via multiple sensory modalities,with special attention to non visual perceptual cues, notably those arising from audition and haptics, as well as interactions between them. It also reviews approaches to combining...... synthetic multimodal cues, from vision, haptics, and audition, in order to realize virtual experiences of walking on simulated ground surfaces or other features....

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

Science.gov (United States)

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

A new piezoelectric energy harvesting design concept: multimodal energy harvesting skin.

Science.gov (United States)

Lee, Soobum; Youn, Byeng D

2011-03-01

This paper presents an advanced design concept for a piezoelectric energy harvesting (EH), referred to as multimodal EH skin. This EH design facilitates the use of multimodal vibration and enhances power harvesting efficiency. The multimodal EH skin is an extension of our previous work, EH skin, which was an innovative design paradigm for a piezoelectric energy harvester: a vibrating skin structure and an additional thin piezoelectric layer in one device. A computational (finite element) model of the multilayered assembly - the vibrating skin structure and piezoelectric layer - is constructed and the optimal topology and/or shape of the piezoelectric layer is found for maximum power generation from multiple vibration modes. A design rationale for the multimodal EH skin was proposed: designing a piezoelectric material distribution and external resistors. In the material design step, the piezoelectric material is segmented by inflection lines from multiple vibration modes of interests to minimize voltage cancellation. The inflection lines are detected using the voltage phase. In the external resistor design step, the resistor values are found for each segment to maximize power output. The presented design concept, which can be applied to any engineering system with multimodal harmonic-vibrating skins, was applied to two case studies: an aircraft skin and a power transformer panel. The excellent performance of multimodal EH skin was demonstrated, showing larger power generation than EH skin without segmentation or unimodal EH skin.

Multimodal Dialogue Management - State of the art

NARCIS (Netherlands)

Bui Huu Trung, B.H.T.

This report is about the state of the art in dialogue management. We first introduce an overview of a multimodal dialogue system and its components. Second, four main approaches to dialogue management are described (finite-state and frame-based, information-state based and probabilistic, plan-based,

Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

International Nuclear Information System (INIS)

Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

2015-01-01

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 as 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

Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

Energy Technology Data Exchange (ETDEWEB)

Tajaldini, Mehdi [School of Physics, Universiti Sains Malaysia, 11800 Pulau Pinang (Malaysia); Young Researchers and Elite Club, Baft Branch, Islamic Azad University, Baft (Iran, Islamic Republic of); Jafri, Mohd Zubir Mat [School of Physics, Universiti Sains Malaysia, 11800 Pulau Pinang (Malaysia)

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 as 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.

Gestures and multimodal input

OpenAIRE

Keates, Simeon; Robinson, Peter

1999-01-01

For users with motion impairments, the standard keyboard and mouse arrangement for computer access often presents problems. Other approaches have to be adopted to overcome this. In this paper, we will describe the development of a prototype multimodal input system based on two gestural input channels. Results from extensive user trials of this system are presented. These trials showed that the physical and cognitive loads on the user can quickly become excessive and detrimental to the interac...

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

Science.gov (United States)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

Analysis and synthesis of multi-qubit, multi-mode quantum devices

Energy Technology Data Exchange (ETDEWEB)

Solgun, Firat

2015-03-27

In this thesis we propose new methods in multi-qubit multi-mode circuit quantum electrodynamics (circuit-QED) architectures. First we describe a direct parity measurement method for three qubits, which can be realized in 2D circuit-QED with a possible extension to four qubits in a 3D circuit-QED setup for the implementation of the surface code. In Chapter 3 we show how to derive Hamiltonians and compute relaxation rates of the multi-mode superconducting microwave circuits consisting of single Josephson junctions using an exact impedance synthesis technique (the Brune synthesis) and applying previous formalisms for lumped element circuit quantization. In the rest of the thesis we extend our method to multi-junction (multi-qubit) multi-mode circuits through the use of state-space descriptions which allows us to quantize any multiport microwave superconducting circuit with a reciprocal lossy impedance response.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

Science.gov (United States)

Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

2018-01-01

In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

Directory of Open Access Journals (Sweden)

Yoshinobu Hagiwara

2018-03-01

Full Text Available In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA. Object recognition results using convolutional neural network (CNN, hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL, and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

A multimodal stress monitoring system with canonical correlation analysis.

Science.gov (United States)

Unsoo Ha; Changhyeon Kim; Yongsu Lee; Hyunki Kim; Taehwan Roh; Hoi-Jun Yoo

2015-08-01

The multimodal stress monitoring headband is proposed for mobile stress management system. It is composed of headband and earplugs. Electroencephalography (EEG), hemoencephalography (HEG) and heart-rate variability (HRV) can be achieved simultaneously in the proposed system for user status estimation. With canonical correlation analysis (CCA) and temporal-kernel CCA (tkCCA) algorithm, those different signals can be combined for maximum correlation. Thanks to the proposed combination algorithm, the accuracy of the proposed system increased up to 19 percentage points than unimodal monitoring system in n-back task.

A Software Framework for Multimodal Human-Computer Interaction Systems

NARCIS (Netherlands)

Shen, Jie; Pantic, Maja

2009-01-01

This paper describes a software framework we designed and implemented for the development and research in the area of multimodal human-computer interface. The proposed framework is based on publish / subscribe architecture, which allows developers and researchers to conveniently configure, test and

Critical Analysis of Multimodal Discourse

DEFF Research Database (Denmark)

van Leeuwen, Theo

2013-01-01

This is an encyclopaedia article which defines the fields of critical discourse analysis and multimodality studies, argues that within critical discourse analysis more attention should be paid to multimodality, and within multimodality to critical analysis, and ends reviewing a few examples of re...

Extended feature-fusion guidelines to improve image-based multi-modal biometrics

CSIR Research Space (South Africa)

Brown, Dane

2016-09-01

Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

Multimodal designs for learning in contexts of diversity

Directory of Open Access Journals (Sweden)

Arlene Archer

2014-12-01

Full Text Available This paper aims to identify multimodal designs for learning in diverse and developing contexts, where access to resources remains vastly unequal. Using case studies from South African education, the paper explores ways of surfacing the range of students’ resources which are often not noticed or valued in formal educational settings. The studies showcased here demonstrate how ethnographic and textually-based approaches can be combined. Opening up the semiotic space of the classroom through multimodal designs for learning is important for finding innovative ways of addressing access, diversity, and past inequalities. This is of relevance not only to South Africa, but a range of global contexts. The paper argues that multimodal designs for learning can involve interrogating the relation between ‘tradition’ and ‘modernity’; harnessing students’ creative practices as resources for pedagogy; developing metalanguages for critical reflection; creating less regulated pedagogical spaces in order to enable useful teaching and learning practices.

Influence of Blood Contamination During Multimode Adhesive ...

African Journals Online (AJOL)

Objectives: 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. Materials and Methods: Seventy-five molars were randomly assigned to three adhesive groups ...

Exploring multimodal robotic interaction through storytelling for aphasics

NARCIS (Netherlands)

Mubin, O.; Al Mahmud, A.; Abuelma'atti, O.; England, D.

2008-01-01

In this poster, we propose the design of a multimodal robotic interaction mechanism that is intended to be used by Aphasics for storytelling. Through limited physical interaction, mild to moderate aphasic people can interact with a robot that may help them to be more active in their day to day

A Practical and Robust Execution Time-Frame Procedure for the Multi-Mode Resource-Constrained Project Scheduling Problem with Minimal and Maximal Time Lags

Directory of Open Access Journals (Sweden)

Angela Hsiang-Ling Chen

2016-09-01

Full Text Available Modeling and optimizing organizational processes, such as the one represented by the Resource-Constrained Project Scheduling Problem (RCPSP, improve outcomes. Based on assumptions and simplification, this model tackles the allocation of resources so that organizations can continue to generate profits and reinvest in future growth. Nonetheless, despite all of the research dedicated to solving the RCPSP and its multi-mode variations, there is no standardized procedure that can guide project management practitioners in their scheduling tasks. This is mainly because many of the proposed approaches are either based on unrealistic/oversimplified scenarios or they propose solution procedures not easily applicable or even feasible in real-life situations. In this study, we solve a more true-to-life and complex model, Multimode RCPSP with minimal and maximal time lags (MRCPSP/max. The complexity of the model solved is presented, and the practicality of the proposed approach is justified depending on only information that is available for every project regardless of its industrial context. The results confirm that it is possible to determine a robust makespan and to calculate an execution time-frame with gaps lower than 11% between their lower and upper bounds. In addition, in many instances, the solved lower bound obtained was equal to the best-known optimum.

A Multi-Modality Mobility Concept for a Small Package Delivery UAV

Science.gov (United States)

Young, L. A.

2017-01-01

This paper will discuss a different approach to the typical notional small package delivery drone concept. Most delivery drone concepts employ a point-to-point aerial delivery CONOPS (Concept of Operations) from a warehouse directly to the front or back yards of a customers residence or a commercial office space. Instead, the proposed approach is somewhat analogous to current postal deliveries: a small aerial vehicle flies from a warehouse to designated neighborhood VTOL (Vertical Take-Off and Landing) landing spots where the aerial vehicle then converts to a "roadable" (ground-mobility) vehicle that then transits on sidewalks and/or bicycle paths till it arrives to the residence/office drop-off points. This concept and associated platform or vehicle will be referred in this paper as MICHAEL (Multimodal Intra-City Hauling and Aerial-Effected Logistics) concept. It is suggested that the MICHAEL concept potentially results in a more community friendly "delivery drone" approach.

The dynamics of multimodal integration: The averaging diffusion model.

Science.gov (United States)

Turner, Brandon M; Gao, Juan; Koenig, Scott; Palfy, Dylan; L McClelland, James

2017-12-01

We combine extant theories of evidence accumulation and multi-modal integration to develop an integrated framework for modeling multimodal integration as a process that unfolds in real time. Many studies have formulated sensory processing as a dynamic process where noisy samples of evidence are accumulated until a decision is made. However, these studies are often limited to a single sensory modality. Studies of multimodal stimulus integration have focused on how best to combine different sources of information to elicit a judgment. These studies are often limited to a single time point, typically after the integration process has occurred. We address these limitations by combining the two approaches. Experimentally, we present data that allow us to study the time course of evidence accumulation within each of the visual and auditory domains as well as in a bimodal condition. Theoretically, we develop a new Averaging Diffusion Model in which the decision variable is the mean rather than the sum of evidence samples and use it as a base for comparing three alternative models of multimodal integration, allowing us to assess the optimality of this integration. The outcome reveals rich individual differences in multimodal integration: while some subjects' data are consistent with adaptive optimal integration, reweighting sources of evidence as their relative reliability changes during evidence integration, others exhibit patterns inconsistent with optimality.

Multimodal Biometric System- Fusion Of Face And Fingerprint Biometrics At Match Score Fusion Level

Directory of Open Access Journals (Sweden)

Grace Wangari Mwaura

2017-04-01

Full Text Available Biometrics has developed to be one of the most relevant technologies used in Information Technology IT security. Unimodal biometric systems have a variety of problems which decreases the performance and accuracy of these system. One way to overcome the limitations of the unimodal biometric systems is through fusion to form a multimodal biometric system. Generally biometric fusion is defined as the use of multiple types of biometric data or ways of processing the data to improve the performance of biometric systems. This paper proposes to develop a model for fusion of the face and fingerprint biometric at the match score fusion level. The face and fingerprint unimodal in the proposed model are built using scale invariant feature transform SIFT algorithm and the hamming distance to measure the distance between key points. To evaluate the performance of the multimodal system the FAR and FRR of the multimodal are compared along those of the individual unimodal systems. It has been established that the multimodal has a higher accuracy of 92.5 compared to the face unimodal system at 90 while the fingerprint unimodal system is at 82.5.

Applying Connectivist Principles and the Task-Based Approach to the Design of a Multimodal Didactic Unit

Directory of Open Access Journals (Sweden)

Yeraldine Aldana Gutiérrez

2012-12-01

Full Text Available This article describes the pedagogical intervention developed in a public school as part of the research “Exploring Communications Practices through Facebook as a Mediatic Device”, framed within the computer mediated communications field. Twelve ninth graders’ communications practices were explored and addressed by means of multimodal technological resources and tasks based on the connectivist learning view. As a result, a didactic unit was designed in the form of the digital book Diverface. This one in turn displayed information through different media channels and semiotic elements to support its multimodal features. Teachers and students might thus need to reconstruct an alternative multimodal literacy so that they can produce and interpret texts of the same nature in online environments.

Chronic sacroiliac joint and pelvic girdle dysfunction in a 35-year-old nulliparous woman successfully managed with multimodal and multidisciplinary approach.

Science.gov (United States)

Jonely, Holly; Brismée, Jean-Michel; Desai, Mehul J; Reoli, Rachel

2015-02-01

Sacroiliac joint pain and dysfunction affect 15-25% of patients reporting low back pain, including reports of spontaneous, idiopathic, traumatic, and non-traumatic onsets. The poor reliability and validity associated with diagnostic clinical and imaging techniques leads to challenges in diagnosing and managing sacroiliac joint dysfunction. A 35-year-old nulliparous female with a 14-year history of right sacroiliac joint dysfunction was managed using a multimodal and multidisciplinary approach when symptoms failed to resolve after 2 months of physical therapy. The plan of care included four prolotherapy injections, sacroiliac joint manipulation into nutation, pelvic girdle belting, and specific stabilization exercises. The patient completed 20 physical therapy sessions over a 12-month period. At 6 months, the patient's Oswestry Disability Questionnaire score was reduced from 34% to 14%. At 1-year follow-up, her score was 0%. The patient's rating of pain on a numeric rating scale decreased to an average of 4/10 at 6 months and 0/10 at 1-year follow-up. A multidisciplinary and multimodal approach for the management of chronic sacroiliac joint dysfunction appeared successful in a single-case design at 1-year follow-up.

Real-time multimodal sensing in nano/bio environment

Science.gov (United States)

Song, Bo

As a sensing device in nano-scale, scanning probe microscopy (SPM) is a powerful tool for exploring nano world. Nevertheless two fundamental problems tackle the development and application of SPM based imaging and measurement: slow imaging/measurement speed and inaccuracy of motion or position control. Usually, SPM imaging/properties measuring speed is too slow to capture a dynamic observation on sample surface. In addition, Both SPM imaging and properties measurement always experience positioning inaccuracy problems caused by hysteresis and creep of the piezo scanner. This dissertation will try to solve these issues and proposed a SPM based real-time multimodal sensing system which can be used in nano/bio environment. First, a compressive sensing based video rate fast SPM imaging system is shown as an efficient method to dynamically capture the sample surface change with the imaging speed 1.5 frame/s with the scan size of 500 nm * 500 nm. Besides topography imaging, a new additional modal of SPM: vibration mode, will be introduced, and it is developed by us to investigate the subsurface mechanical properties of the elastic sample such as cells and bacteria. A followed up study of enzymatic hydrolysis will demonstrate the ability of in situ observation of single molecule event using video rate SPM. After that we will introduce another modal of this SPM sensing system: accurate electrical properties measurement. In this electrical properties measurement mode, a compressive feedbacks based non-vector space control approach is proposed in order to improve the accuracy of SPM based nanomanipulations. Instead of sensors, the local images are used as both the input and feedback of a non-vector space closed-loop controller. A followed up study will also be introduced to shown the important role of non-vector space control in the study of conductivity distribution of multi-wall carbon nanotubes. At the end of this dissertation, some future work will be also proposed to

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

Science.gov (United States)

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.

A Robust Multimodal Bio metric Authentication Scheme with Voice and Face Recognition

International Nuclear Information System (INIS)

Kasban, H.

2017-01-01

This paper proposes a multimodal biometric scheme for human authentication based on fusion of voice and face recognition. For voice recognition, three categories of features (statistical coefficients, cepstral coefficients and voice timbre) are used and compared. The voice identification modality is carried out using Gaussian Mixture Model (GMM). For face recognition, three recognition methods (Eigenface, Linear Discriminate Analysis (LDA), and Gabor filter) are used and compared. The combination of voice and face biometrics systems into a single multimodal biometrics system is performed using features fusion and scores fusion. This study shows that the best results are obtained using all the features (cepstral coefficients, statistical coefficients and voice timbre features) for voice recognition, LDA face recognition method and scores fusion for the multimodal biometrics system

The Multimodal Possibilities of Online Instructions

DEFF Research Database (Denmark)

Kampf, Constance

2006-01-01

The WWW simplifies the process of delivering online instructions through multimodal channels because of the ease of use for voice, video, pictures, and text modes of communication built into it.  Given that instructions are being produced in multimodal format for the WWW, how do multi-modal analy......The WWW simplifies the process of delivering online instructions through multimodal channels because of the ease of use for voice, video, pictures, and text modes of communication built into it.  Given that instructions are being produced in multimodal format for the WWW, how do multi...

Modelling multimodal expression of emotion in a virtual agent.

Science.gov (United States)

Pelachaud, Catherine

2009-12-12

Over the past few years we have been developing an expressive embodied conversational agent system. In particular, we have developed a model of multimodal behaviours that includes dynamism and complex facial expressions. The first feature refers to the qualitative execution of behaviours. Our model is based on perceptual studies and encompasses several parameters that modulate multimodal behaviours. The second feature, the model of complex expressions, follows a componential approach where a new expression is obtained by combining facial areas of other expressions. Lately we have been working on adding temporal dynamism to expressions. So far they have been designed statically, typically at their apex. Only full-blown expressions could be modelled. To overcome this limitation, we have defined a representation scheme that describes the temporal evolution of the expression of an emotion. It is no longer represented by a static definition but by a temporally ordered sequence of multimodal signals.

Percorsi linguistici e semiotici: Critical Multimodal Analysis of Digital Discourse

OpenAIRE

edited by Ilaria Moschini

2014-01-01

The language section of LEA - edited by Ilaria Moschini - is dedicated to the Critical Multimodal Analysis of Digital Discourse, an approach that encompasses the linguistic and semiotic detailed investigation of texts within a socio-cultural perspective. It features an interview with Professor Theo van Leeuwen by Ilaria Moschini and four essays: “Retwitting, reposting, repinning; reshaping identities online: Towards a social semiotic multimodal analysis of digital remediation” by Elisabetta A...

Multimodal segmentation of optic disc and cup from stereo fundus and SD-OCT images

Science.gov (United States)

Miri, Mohammad Saleh; Lee, Kyungmoo; Niemeijer, Meindert; Abràmoff, Michael D.; Kwon, Young H.; Garvin, Mona K.

2013-03-01

Glaucoma is one of the major causes of blindness worldwide. One important structural parameter for the diagnosis and management of glaucoma is the cup-to-disc ratio (CDR), which tends to become larger as glaucoma progresses. While approaches exist for segmenting the optic disc and cup within fundus photographs, and more recently, within spectral-domain optical coherence tomography (SD-OCT) volumes, no approaches have been reported for the simultaneous segmentation of these structures within both modalities combined. In this work, a multimodal pixel-classification approach for the segmentation of the optic disc and cup within fundus photographs and SD-OCT volumes is presented. In particular, after segmentation of other important structures (such as the retinal layers and retinal blood vessels) and fundus-to-SD-OCT image registration, features are extracted from both modalities and a k-nearest-neighbor classification approach is used to classify each pixel as cup, rim, or background. The approach is evaluated on 70 multimodal image pairs from 35 subjects in a leave-10%-out fashion (by subject). A significant improvement in classification accuracy is obtained using the multimodal approach over that obtained from the corresponding unimodal approach (97.8% versus 95.2%; p < 0:05; paired t-test).

Towards emotion detection in educational scenarios from facial expressions and body movements through multimodal approaches.

Science.gov (United States)

Saneiro, Mar; Santos, Olga C; Salmeron-Majadas, Sergio; Boticario, Jesus G

2014-01-01

We report current findings when considering video recordings of facial expressions and body movements to provide affective personalized support in an educational context from an enriched multimodal emotion detection approach. In particular, we describe an annotation methodology to tag facial expression and body movements that conform to changes in the affective states of learners while dealing with cognitive tasks in a learning process. The ultimate goal is to combine these annotations with additional affective information collected during experimental learning sessions from different sources such as qualitative, self-reported, physiological, and behavioral information. These data altogether are to train data mining algorithms that serve to automatically identify changes in the learners' affective states when dealing with cognitive tasks which help to provide emotional personalized support.

Towards Emotion Detection in Educational Scenarios from Facial Expressions and Body Movements through Multimodal Approaches

Directory of Open Access Journals (Sweden)

Mar Saneiro

2014-01-01

Full Text Available We report current findings when considering video recordings of facial expressions and body movements to provide affective personalized support in an educational context from an enriched multimodal emotion detection approach. In particular, we describe an annotation methodology to tag facial expression and body movements that conform to changes in the affective states of learners while dealing with cognitive tasks in a learning process. The ultimate goal is to combine these annotations with additional affective information collected during experimental learning sessions from different sources such as qualitative, self-reported, physiological, and behavioral information. These data altogether are to train data mining algorithms that serve to automatically identify changes in the learners’ affective states when dealing with cognitive tasks which help to provide emotional personalized support.

Multi-criteria appraisal of multi-modal urban public transport systems

NARCIS (Netherlands)

Keyvan Ekbatani, M.; Cats, O.

2015-01-01

This study proposes a multi-criteria decision making (MCDM) modelling framework for the appraisal of multi-modal urban public transportation services. MCDM is commonly used to obtain choice alternatives that satisfy a range of performance indicators. The framework embraces both compensatory and

The future of multimodal corpora O futuro dos corpora modais

Directory of Open Access Journals (Sweden)

Dawn Knight

2011-01-01

Full Text Available This paper takes stock of the current state-of-the-art in multimodal corpus linguistics, and proposes some projections of future developments in this field. It provides a critical overview of key multimodal corpora that have been constructed over the past decade and presents a wish-list of future technological and methodological advancements that may help to increase the availability, utility and functionality of such corpora for linguistic research.Este artigo apresenta um balanço do estado da arte da linguística de corpus multimodal e propõe a projeção de desenvolvimentos futuros nessa área. Um resumo crítico dos corpora multimodais-chave que foram construídos na última década é apresentado, assim como uma lista de desenvolvimentos tecnológicos e metodológicos futuros que podem auxiliar na disponibilização e utilização, bem como na funcionalidade, de tais corpora para a pesquisa linguística.

High-resolution multimodal clinical multiphoton tomography of skin

Science.gov (United States)

König, Karsten

2011-03-01

This review focuses on multimodal multiphoton tomography based on near infrared femtosecond lasers. Clinical multiphoton tomographs for 3D high-resolution in vivo imaging have been placed into the market several years ago. The second generation of this Prism-Award winning High-Tech skin imaging tool (MPTflex) was introduced in 2010. The same year, the world's first clinical CARS studies have been performed with a hybrid multimodal multiphoton tomograph. In particular, non-fluorescent lipids and water as well as mitochondrial fluorescent NAD(P)H, fluorescent elastin, keratin, and melanin as well as SHG-active collagen has been imaged with submicron resolution in patients suffering from psoriasis. Further multimodal approaches include the combination of multiphoton tomographs with low-resolution wide-field systems such as ultrasound, optoacoustical, OCT, and dermoscopy systems. Multiphoton tomographs are currently employed in Australia, Japan, the US, and in several European countries for early diagnosis of skin cancer, optimization of treatment strategies, and cosmetic research including long-term testing of sunscreen nanoparticles as well as anti-aging products.

Toward multimodal signal detection of adverse drug reactions.

Science.gov (United States)

Harpaz, Rave; DuMouchel, William; Schuemie, Martijn; Bodenreider, Olivier; Friedman, Carol; Horvitz, Eric; Ripple, Anna; Sorbello, Alfred; White, Ryen W; Winnenburg, Rainer; Shah, Nigam H

2017-12-01

Improving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Four data sources are investigated; FDA's adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. Limited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04 to 0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 7-22 months relative to labeling revision dates from a time-indexed benchmark. The results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Multimodal fluorescence imaging spectroscopy

NARCIS (Netherlands)

Stopel, Martijn H W; Blum, Christian; Subramaniam, Vinod; Engelborghs, Yves; Visser, Anthonie J.W.G.

2014-01-01

Multimodal fluorescence imaging is a versatile method that has a wide application range from biological studies to materials science. Typical observables in multimodal fluorescence imaging are intensity, lifetime, excitation, and emission spectra which are recorded at chosen locations at the sample.

All-silicon thermal independent Mach-Zehnder interferometer with multimode waveguides

DEFF Research Database (Denmark)

Guan, Xiaowei; Frandsen, Lars Hagedorn

2016-01-01

A novel all-silicon thermal independent Mach-Zehnder interferometer consisting of two multimode waveguide arms having equal lengths and widths but transmitting different modes is proposed and experimentally demonstrated. The interferometer has a temperature sensitivity smaller than 8pm/°C in a wa...

Inorganic Nanoparticles for Multimodal Molecular Imaging

Directory of Open Access Journals (Sweden)

Magdalena Swierczewska

2011-01-01

Full Text Available Multimodal molecular imaging can offer a synergistic improvement of diagnostic ability over a single imaging modality. Recent development of hybrid imaging systems has profoundly impacted the pool of available multimodal imaging probes. In particular, much interest has been focused on biocompatible, inorganic nanoparticle-based multimodal probes. Inorganic nanoparticles offer exceptional advantages to the field of multimodal imaging owing to their unique characteristics, such as nanometer dimensions, tunable imaging properties, and multifunctionality. Nanoparticles mainly based on iron oxide, quantum dots, gold, and silica have been applied to various imaging modalities to characterize and image specific biologic processes on a molecular level. A combination of nanoparticles and other materials such as biomolecules, polymers, and radiometals continue to increase functionality for in vivo multimodal imaging and therapeutic agents. In this review, we discuss the unique concepts, characteristics, and applications of the various multimodal imaging probes based on inorganic nanoparticles.

OpenLMD, multimodal monitoring and control of LMD processing

Science.gov (United States)

Rodríguez-Araújo, Jorge; García-Díaz, Antón

2017-02-01

This paper presents OpenLMD, a novel open-source solution for on-line multimodal monitoring of Laser Metal Deposition (LMD). The solution is also applicable to a wider range of laser-based applications that require on-line control (e.g. laser welding). OpenLMD is a middleware that enables the orchestration and virtualization of a LMD robot cell, using several open-source frameworks (e.g. ROS, OpenCV, PCL). The solution also allows reconfiguration by easy integration of multiple sensors and processing equipment. As a result, OpenLMD delivers significant advantages over existing monitoring and control approaches, such as improved scalability, and multimodal monitoring and data sharing capabilities.

vECTlab-A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

International Nuclear Information System (INIS)

Peter, Joerg; Semmler, Wolfhard

2007-01-01

Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems

Composite multi-modal vibration control for a stiffened plate using non-collocated acceleration sensor and piezoelectric actuator

International Nuclear Information System (INIS)

Li, Shengquan; Li, Juan; Mo, Yueping; Zhao, Rong

2014-01-01

A novel active method for multi-mode vibration control of an all-clamped stiffened plate (ACSP) is proposed in this paper, using the extended-state-observer (ESO) approach based on non-collocated acceleration sensors and piezoelectric actuators. Considering the estimated capacity of ESO for system state variables, output superposition and control coupling of other modes, external excitation, and model uncertainties simultaneously, a composite control method, i.e., the ESO based vibration control scheme, is employed to ensure the lumped disturbances and uncertainty rejection of the closed-loop system. The phenomenon of phase hysteresis and time delay, caused by non-collocated sensor/actuator pairs, degrades the performance of the control system, even inducing instability. To solve this problem, a simple proportional differential (PD) controller and acceleration feed-forward with an output predictor design produce the control law for each vibration mode. The modal frequencies, phase hysteresis loops and phase lag values due to non-collocated placement of the acceleration sensor and piezoelectric patch actuator are experimentally obtained, and the phase lag is compensated by using the Smith Predictor technology. In order to improve the vibration control performance, the chaos optimization method based on logistic mapping is employed to auto-tune the parameters of the feedback channel. The experimental control system for the ACSP is tested using the dSPACE real-time simulation platform. Experimental results demonstrate that the proposed composite active control algorithm is an effective approach for suppressing multi-modal vibrations. (paper)

Quality dependent fusion of intramodal and multimodal biometric experts

Science.gov (United States)

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.

Multimodality in organization studies

DEFF Research Database (Denmark)

Van Leeuwen, Theo

2017-01-01

This afterword reviews the chapters in this volume and reflects on the synergies between organization and management studies and multimodality studies that emerge from the volume. These include the combination of strong sociological theorizing and detailed multimodal analysis, a focus on material...

Multimodal interaction in image and video applications

CERN Document Server

Sappa, Angel D

2013-01-01

Traditional Pattern Recognition (PR) and Computer Vision (CV) technologies have mainly focused on full automation, even though full automation often proves elusive or unnatural in many applications, where the technology is expected to assist rather than replace the human agents. However, not all the problems can be automatically solved being the human interaction the only way to tackle those applications. Recently, multimodal human interaction has become an important field of increasing interest in the research community. Advanced man-machine interfaces with high cognitive capabilities are a hot research topic that aims at solving challenging problems in image and video applications. Actually, the idea of computer interactive systems was already proposed on the early stages of computer science. Nowadays, the ubiquity of image sensors together with the ever-increasing computing performance has open new and challenging opportunities for research in multimodal human interaction. This book aims to show how existi...

Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

Science.gov (United States)

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2013-01-01

Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

Multi-Mode Operation for On-line Uninterruptible Power Supply System

DEFF Research Database (Denmark)

Lu, Jinghang; Savaghebi, Mehdi; Golestan, Saeed

2018-01-01

To enhance the robustness and disturbance rejection ability of an on-line uninterruptible power supply (UPS) system, an Internal Model Control (IMC)-based DC-link voltage regulation method is proposed in this paper. Furthermore, the multi-mode operations of the on-line UPS system are investigated...

An Adaptive Large Neighborhood Search Algorithm for the Multi-mode RCPSP

DEFF Research Database (Denmark)

Muller, Laurent Flindt

We present an Adaptive Large Neighborhood Search algorithm for the Multi-mode Resource-Constrained Project Scheduling Problem (MRCPSP). We incorporate techniques for deriving additional precedence relations and propose a new method, so-called mode-diminution, for removing modes during execution...

Towards automatic generation of multimodal answers to medical questions: a cognitive engineering approach

NARCIS (Netherlands)

van Hooijdonk, Charlotte; Krahmer, Emiel; Maes, Alfons; Bosma, W.E.; van der Sluis, I; Theune, Mariet; Reiter, E.; Krahmer, E.

2007-01-01

This paper describes a production experiment carried out to determine which modalities people choose to answer different types of questions. In this experiment participants had to create (multimodal) presentations of answers to general medical questions. The collected answer presentations were coded

Multimodal interaction with W3C standards toward natural user interfaces to everything

CERN Document Server

2017-01-01

This book presents new standards for multimodal interaction published by the W3C and other standards bodies in straightforward and accessible language, while also illustrating the standards in operation through case studies and chapters on innovative implementations. The book illustrates how, as smart technology becomes ubiquitous, and appears in more and more different shapes and sizes, vendor-specific approaches to multimodal interaction become impractical, motivating the need for standards. This book covers standards for voice, emotion, natural language understanding, dialog, and multimodal architectures. The book describes the standards in a practical manner, making them accessible to developers, students, and researchers. Comprehensive resource that explains the W3C standards for multimodal interaction clear and straightforward way; Includes case studies of the use of the standards on a wide variety of devices, including mobile devices, tablets, wearables and robots, in applications such as assisted livi...

A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

Directory of Open Access Journals (Sweden)

Arvind Selwal

2016-09-01

Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

Science.gov (United States)

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.

A multilingual and multimodal approach to literacy teaching and learning in urban education: a collaborative inquiry project in an inner city elementary school.

Science.gov (United States)

Ntelioglou, Burcu Yaman; Fannin, Jennifer; Montanera, Mike; Cummins, Jim

2014-01-01

This paper presents findings from a collaborative inquiry project that explored teaching approaches that highlight the significance of multilingualism, multimodality, and multiliteracies in classrooms with high numbers of English language learners (ELLs). The research took place in an inner city elementary school with a large population of recently arrived and Canadian-born linguistically and culturally diverse students from Gambian, Indian, Mexican, Sri Lankan, Tibetan and Vietnamese backgrounds, as well as a recent wave of Roma students from Hungary. A high number of these students were from families with low-SES. The collaboration between two Grade 3 teachers and university-based researchers sought to create instructional approaches that would support students' academic engagement and literacy learning. In this paper, we described one of the projects that took place in this class, exploring how a descriptive writing unit could be implemented in a way that connected with students' lives and enabled them to use their home languages, through the creation of multiple texts, using creative writing, digital technologies, and drama pedagogy. This kind of multilingual and multimodal classroom practice changed the classroom dynamics and allowed the students access to identity positions of expertise, increasing their literacy investment, literacy engagement and learning.

Automatic lip reading by using multimodal visual features

Science.gov (United States)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

Multimodal strategies to improve surgical outcome

DEFF Research Database (Denmark)

Kehlet, Henrik; Wilmore, Douglas W

2002-01-01

OBJECTIVE: To evaluate the effect of modifying perioperative care in noncardiac surgical patients on morbidity, mortality, and other outcome measures. BACKGROUND: New approaches in pain control, introduction of techniques that reduce the perioperative stress response, and the more frequent use...... anesthesia in elective operations, and pilot studies of fast track surgical procedures using the multimodality approach. RESULTS: The introduction of newer approaches to perioperative care has reduced both morbidity and mortality in surgical patients. In the future, most elective operations will become day...... surgical procedures or require only 1 to 2 days of postoperative hospitalization. Reorganization of the perioperative team (anesthesiologists, surgeons, nurses, and physical therapists) will be essential to achieve successful fast track surgical programs. CONCLUSIONS: Understanding perioperative...

Multi-modal Social Networks: A MRF Learning Approach

Science.gov (United States)

2016-06-20

Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

Automatic Evolution of Multimodal Behavior with Multi-Brain HyperNEAT

DEFF Research Database (Denmark)

Schrum, Jacob; Lehman, Joel; Risi, Sebastian

2016-01-01

indirect encoding. A previous multimodal approach called situational policy geometry assumes that multiple brains benefit from being embedded within an explicit geometric space. However, this paper introduces HyperNEAT extensions for evolving many brains without assuming geometric relationships between...

Multimodality imaging of pulmonary infarction

International Nuclear Information System (INIS)

Bray, T.J.P.; Mortensen, K.H.; Gopalan, D.

2014-01-01

Highlights: • A plethora of pulmonary and systemic disorders, often associated with grave outcomes, may cause pulmonary infarction. • A stereotypical infarct is a peripheral wedge shaped pleurally based opacity but imaging findings can be highly variable. • Multimodality imaging is key to diagnosing the presence, aetiology and complications of pulmonary infarction. • Multimodality imaging of pulmonary infarction together with any ancillary features often guide to early targeted treatment. • CT remains the principal imaging modality with MRI increasingly used alongside nuclear medicine studies and ultrasound. - Abstract: The impact of absent pulmonary arterial and venous flow on the pulmonary parenchyma depends on a host of factors. These include location of the occlusive insult, the speed at which the occlusion develops and the ability of the normal dual arterial supply to compensate through increased bronchial arterial flow. Pulmonary infarction occurs when oxygenation is cut off secondary to sudden occlusion with lack of recruitment of the dual supply arterial system. Thromboembolic disease is the commonest cause of such an insult but a whole range of disease processes intrinsic and extrinsic to the pulmonary arterial and venous lumen may also result in infarcts. Recognition of the presence of infarction can be challenging as imaging manifestations often differ from the classically described wedge shaped defect and a number of weighty causes need consideration. This review highlights aetiologies and imaging appearances of pulmonary infarction, utilising cases to illustrate the essential role of a multimodality imaging approach in order to arrive at the appropriate diagnosis

Multimodality imaging of pulmonary infarction

Energy Technology Data Exchange (ETDEWEB)

Bray, T.J.P., E-mail: timothyjpbray@gmail.com [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom); Mortensen, K.H., E-mail: mortensen@doctors.org.uk [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom); University Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Box 318, Cambridge CB2 0QQ (United Kingdom); Gopalan, D., E-mail: deepa.gopalan@btopenworld.com [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom)

2014-12-15

Highlights: • A plethora of pulmonary and systemic disorders, often associated with grave outcomes, may cause pulmonary infarction. • A stereotypical infarct is a peripheral wedge shaped pleurally based opacity but imaging findings can be highly variable. • Multimodality imaging is key to diagnosing the presence, aetiology and complications of pulmonary infarction. • Multimodality imaging of pulmonary infarction together with any ancillary features often guide to early targeted treatment. • CT remains the principal imaging modality with MRI increasingly used alongside nuclear medicine studies and ultrasound. - Abstract: The impact of absent pulmonary arterial and venous flow on the pulmonary parenchyma depends on a host of factors. These include location of the occlusive insult, the speed at which the occlusion develops and the ability of the normal dual arterial supply to compensate through increased bronchial arterial flow. Pulmonary infarction occurs when oxygenation is cut off secondary to sudden occlusion with lack of recruitment of the dual supply arterial system. Thromboembolic disease is the commonest cause of such an insult but a whole range of disease processes intrinsic and extrinsic to the pulmonary arterial and venous lumen may also result in infarcts. Recognition of the presence of infarction can be challenging as imaging manifestations often differ from the classically described wedge shaped defect and a number of weighty causes need consideration. This review highlights aetiologies and imaging appearances of pulmonary infarction, utilising cases to illustrate the essential role of a multimodality imaging approach in order to arrive at the appropriate diagnosis.

Multimodal imaging of vascular network and blood microcirculation by optical diagnostic techniques

International Nuclear Information System (INIS)

Kuznetsov, Yu L; Kalchenko, V V; Meglinski, I V

2011-01-01

We present a multimodal optical diagnostic approach for simultaneous non-invasive in vivo imaging of blood and lymphatic microvessels, utilising a combined use of fluorescence intravital microscopy and a method of dynamic light scattering. This approach makes it possible to renounce the use of fluorescent markers for visualisation of blood vessels and, therefore, significantly (tenfold) reduce the toxicity of the technique and minimise side effects caused by the use of contrast fluorescent markers. We demonstrate that along with the ability to obtain images of lymph and blood microvessels with a high spatial resolution, current multimodal approach allows one to observe in real time permeability of blood vessels. This technique appears to be promising in physiology studies of blood vessels, and especially in the study of peripheral cardiovascular system in vivo. (optical technologies in biophysics and medicine)

A Novel Multimodal Biometrics Recognition Model Based on Stacked ELM and CCA Methods

Directory of Open Access Journals (Sweden)

Jucheng Yang

2018-04-01

Full Text Available Multimodal biometrics combine a variety of biological features to have a significant impact on identification performance, which is a newly developed trend in biometrics identification technology. This study proposes a novel multimodal biometrics recognition model based on the stacked extreme learning machines (ELMs and canonical correlation analysis (CCA methods. The model, which has a symmetric structure, is found to have high potential for multimodal biometrics. The model works as follows. First, it learns the hidden-layer representation of biological images using extreme learning machines layer by layer. Second, the canonical correlation analysis method is applied to map the representation to a feature space, which is used to reconstruct the multimodal image feature representation. Third, the reconstructed features are used as the input of a classifier for supervised training and output. To verify the validity and efficiency of the method, we adopt it for new hybrid datasets obtained from typical face image datasets and finger-vein image datasets. Our experimental results demonstrate that our model performs better than traditional methods.

Manifold regularized multitask feature learning for multimodality disease classification.

Science.gov (United States)

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-02-01

Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. © 2014 Wiley Periodicals, Inc.

Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

Science.gov (United States)

Jie, Biao; Cheng, Bo

2014-01-01

Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

Science.gov (United States)

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Multimodal Feature Learning for Video Captioning

Directory of Open Access Journals (Sweden)

Sujin Lee

2018-01-01

Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

Nuevas alfabetizaciones en un entorno multimodal: nuevas necesidades lectoras para un entorno textual múltiple

Directory of Open Access Journals (Sweden)

Juan Patricio Sánchez-Claros

2016-01-01

Full Text Available The new technologies of information, the development of the media and the massive presence of multimedia devices have brought a renewal of the traditional concept of literacy. Multimodality in the media, in the dissemination of knowledge and the communicat ion formats have brought a change in the system of reception of media objects and each of its integral elements. This multimodal environment is part of the daily life of students who access through a scenario of screens and images across a virtual environm ent in which both textual and visual are integrated as an informational continuum that requires to users new interpretation skills. And, consequently, a new approach to media literacy should be the subject of attention from educators. Media literac y implies the need to address new visual skills, new reading skills and especially new skills for integration and analysis, among those who cannot be set aside on the critical apparatus necessary. This paper discusses the content of these skills, some cri tical tools for multimodal approach speech as well as the role the four substrata of discourse, design, production and distribution , typical ofCritical Analysis of Multimodal Discourse are analysed .

Multimodal sequence learning.

Science.gov (United States)

Kemény, Ferenc; Meier, Beat

2016-02-01

While sequence learning research models complex phenomena, previous studies have mostly focused on unimodal sequences. The goal of the current experiment is to put implicit sequence learning into a multimodal context: to test whether it can operate across different modalities. We used the Task Sequence Learning paradigm to test whether sequence learning varies across modalities, and whether participants are able to learn multimodal sequences. Our results show that implicit sequence learning is very similar regardless of the source modality. However, the presence of correlated task and response sequences was required for learning to take place. The experiment provides new evidence for implicit sequence learning of abstract conceptual representations. In general, the results suggest that correlated sequences are necessary for implicit sequence learning to occur. Moreover, they show that elements from different modalities can be automatically integrated into one unitary multimodal sequence. Copyright © 2015 Elsevier B.V. All rights reserved.

Multimodal imaging in cerebral gliomas and its neuropathological correlation

Energy Technology Data Exchange (ETDEWEB)

Gempt, Jens, E-mail: jens.gempt@lrz.tum.de [Neurochirurgische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Soehngen, Eric [Abteilung für Neuroradiologie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Abteilung für Neuropathologie des Instituts für Allgemeine Pathologie und Pathologische Anatomie, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Förster, Stefan [Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Ryang, Yu-Mi [Neurochirurgische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Schlegel, Jürgen [Abteilung für Neuropathologie des Instituts für Allgemeine Pathologie und Pathologische Anatomie, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); and others

2014-05-15

Introduction: Concerning the preoperative clinical diagnostic work-up of glioma patients, tumor heterogeneity challenges the oncological therapy. The current study assesses the performance of a multimodal imaging approach to differentiate between areas in malignant gliomas and to investigate the extent to which such a combinatorial imaging approach might predict the underlying histology. Methods: Prior to surgical resection, patients harboring intracranial gliomas underwent MRIs (MR-S, PWI) and {sup 18}F-FET-PETs. Intratumoral and peritumoral biopsy targets were defined, by MRI only, by FET-PET only, and by MRI and FET-PET combined, and biopsied prior to surgical resection and which then received separate histopathological examinations. Results: In total, 38 tissue samples were acquired (seven glioblastomas, one anaplastic astrocytoma, one anaplastic oligoastrocytoma, one diffuse astrocytoma, and one oligoastrocytoma) and underwent histopathological analysis. The highest mean values of Mib1 and CD31 were found in the target point “T’ defined by MRI and FET-PET combined. A significant correlation between NAA/Cr and PET tracer uptake (−0.845, p < 0.05) as well as Cho/Cr ratio and cell density (0.742, p < 0.05) and NAA/Cr ratio and MIB-1 (−0761, p < 0.05) was disclosed for this target point, though not for target points defined by MRI and FET-PET alone. Conclusion: Multimodal-imaging-guided stereotactic biopsy correlated more with histological malignancy indices, such as cell density and MIB-1 labeling, than targets that were based solely on the highest amino acid uptake or contrast enhancement on MRI. The results of our study indicate that a combined PET-MR multimodal imaging approach bears potential benefits in detecting glioma heterogeneity.

Online probabilistic operational safety assessment of multi-mode engineering systems using Bayesian methods

International Nuclear Information System (INIS)

Lin, Yufei; Chen, Maoyin; Zhou, Donghua

2013-01-01

In the past decades, engineering systems become more and more complex, and generally work at different operational modes. Since incipient fault can lead to dangerous accidents, it is crucial to develop strategies for online operational safety assessment. However, the existing online assessment methods for multi-mode engineering systems commonly assume that samples are independent, which do not hold for practical cases. This paper proposes a probabilistic framework of online operational safety assessment of multi-mode engineering systems with sample dependency. To begin with, a Gaussian mixture model (GMM) is used to characterize multiple operating modes. Then, based on the definition of safety index (SI), the SI for one single mode is calculated. At last, the Bayesian method is presented to calculate the posterior probabilities belonging to each operating mode with sample dependency. The proposed assessment strategy is applied in two examples: one is the aircraft gas turbine, another is an industrial dryer. Both examples illustrate the efficiency of the proposed method

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Directory of Open Access Journals (Sweden)

Yeong Gon Kim

2012-09-01

Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

Multimodal Processes Rescheduling

DEFF Research Database (Denmark)

Bocewicz, Grzegorz; Banaszak, Zbigniew A.; Nielsen, Peter

2013-01-01

Cyclic scheduling problems concerning multimodal processes are usually observed in FMSs producing multi-type parts where the Automated Guided Vehicles System (AGVS) plays a role of a material handling system. Schedulability analysis of concurrently flowing cyclic processes (SCCP) exe-cuted in the......Cyclic scheduling problems concerning multimodal processes are usually observed in FMSs producing multi-type parts where the Automated Guided Vehicles System (AGVS) plays a role of a material handling system. Schedulability analysis of concurrently flowing cyclic processes (SCCP) exe...

Recent Progress in Synthesis and Functionalization of Multimodal Fluorescent-Magnetic Nanoparticles for Biological Applications

Directory of Open Access Journals (Sweden)

Raquel Serrano García

2018-01-01

Full Text Available There is a great interest in the development of new nanomaterials for multimodal imaging applications in biology and medicine. Multimodal fluorescent-magnetic based nanomaterials deserve particular attention as they can be used as diagnostic and drug delivery tools, which could facilitate the diagnosis and treatment of cancer and many other diseases. This review focuses on the recent developments of magnetic-fluorescent nanocomposites and their biomedical applications. The recent advances in synthetic strategies and approaches for the preparation of fluorescent-magnetic nanocomposites are presented. The main biomedical uses of multimodal fluorescent-magnetic nanomaterials, including biological imaging, cancer therapy and drug delivery, are discussed, and prospects of this field are outlined.

Multimodal Resources in Transnational Adoption

DEFF Research Database (Denmark)

Raudaskoski, Pirkko Liisa

The paper discusses an empirical analysis which highlights the multimodal nature of identity construction. A documentary on transnational adoption provides real life incidents as research material. The incidents involve (or from them emerge) various kinds of multimodal resources and participants...

Pedestrian detection from thermal images: A sparse representation based approach

Science.gov (United States)

Qi, Bin; John, Vijay; Liu, Zheng; Mita, Seiichi

2016-05-01

Pedestrian detection, a key technology in computer vision, plays a paramount role in the applications of advanced driver assistant systems (ADASs) and autonomous vehicles. The objective of pedestrian detection is to identify and locate people in a dynamic environment so that accidents can be avoided. With significant variations introduced by illumination, occlusion, articulated pose, and complex background, pedestrian detection is a challenging task for visual perception. Different from visible images, thermal images are captured and presented with intensity maps based objects' emissivity, and thus have an enhanced spectral range to make human beings perceptible from the cool background. In this study, a sparse representation based approach is proposed for pedestrian detection from thermal images. We first adopted the histogram of sparse code to represent image features and then detect pedestrian with the extracted features in an unimodal and a multimodal framework respectively. In the unimodal framework, two types of dictionaries, i.e. joint dictionary and individual dictionary, are built by learning from prepared training samples. In the multimodal framework, a weighted fusion scheme is proposed to further highlight the contributions from features with higher separability. To validate the proposed approach, experiments were conducted to compare with three widely used features: Haar wavelets (HWs), histogram of oriented gradients (HOG), and histogram of phase congruency (HPC) as well as two classification methods, i.e. AdaBoost and support vector machine (SVM). Experimental results on a publicly available data set demonstrate the superiority of the proposed approach.

Multimodality therapy approaches, local and systemic treatment, compared with chemotherapy alone in recurrent glioblastoma

International Nuclear Information System (INIS)

Scorsetti, Marta; Navarria, Pierina; Pessina, Federico; Ascolese, Anna Maria; D’Agostino, Giuseppe; Tomatis, Stefano; De Rose, Fiorenza; Villa, Elisa; Maggi, Giulia; Simonelli, Matteo; Clerici, Elena; Soffietti, Riccardo; Santoro, Armando; Cozzi, Luca; Bello, Lorenzo

2015-01-01

Long-term local control in Glioblastoma is rarely achieved and nearly all patients relapse. In this study we evaluated the clinical effect of different treatment approaches in recurrent patients. Forty-three patients, with median age of 51 years were evaluated for salvage treatment: re-resection and/or re-irradiation plus chemotherapy or chemotherapy alone. Response was recorded using the Response Assessment in Neuro-Oncology criteria. Hematologic and non-hematologic toxicities were graded according to Common Terminology Criteria for Adverse Events 4.0. Twenty-one patients underwent chemotherapy combined with local treatment, surgery and/or radiation therapy, and 22 underwent chemotherapy only. The median follow up was 7 months (range 3–28 months). The 1 and 2-years Progression Free Survival was 65 and 10 % for combined treatment and 22 and 0 % for chemotherapy alone (p < 0.01). The 1 and 2-years overall survival was 69 and 29 % for combined and 26 and 0 % for chemotherapy alone (p < 0.01). No toxicity greater than grade 2 was recorded. These data showed that in glioblastoma recurrence the combination of several approaches in a limited group of patients is more effective than a single treatment alone. This stress the importance of multimodality treatment whenever clinically feasible

Hearing and Seeing Tone through Color: An Efficacy Study of Web-Based, Multimodal Chinese Tone Perception Training

Science.gov (United States)

Godfroid, Aline; Lin, Chin-Hsi; Ryu, Catherine

2017-01-01

Multimodal approaches have been shown to be effective for many learning tasks. In this study, we compared the effectiveness of five multimodal methods for second language (L2) Mandarin tone perception training: three single-cue methods (number, pitch contour, color) and two dual-cue methods (color and number, color and pitch contour). A total of…

A Novel Technique for Prealignment in Multimodality Medical Image Registration

Directory of Open Access Journals (Sweden)

Wu Zhou

2014-01-01

Full Text Available Image pair is often aligned initially based on a rigid or affine transformation before a deformable registration method is applied in medical image registration. Inappropriate initial registration may compromise the registration speed or impede the convergence of the optimization algorithm. In this work, a novel technique was proposed for prealignment in both monomodality and multimodality image registration based on statistical correlation of gradient information. A simple and robust algorithm was proposed to determine the rotational differences between two images based on orientation histogram matching accumulated from local orientation of each pixel without any feature extraction. Experimental results showed that it was effective to acquire the orientation angle between two unregistered images with advantages over the existed method based on edge-map in multimodalities. Applying the orientation detection into the registration of CT/MR, T1/T2 MRI, and monomadality images with respect to rigid and nonrigid deformation improved the chances of finding the global optimization of the registration and reduced the search space of optimization.

Multimodal Diversity of Postmodernist Fiction Text

Directory of Open Access Journals (Sweden)

U. I. Tykha

2016-12-01

Full Text Available The article is devoted to the analysis of structural and functional manifestations of multimodal diversity in postmodernist fiction texts. Multimodality is defined as the coexistence of more than one semiotic mode within a certain context. Multimodal texts feature a diversity of semiotic modes in the communication and development of their narrative. Such experimental texts subvert conventional patterns by introducing various semiotic resources – verbal or non-verbal.

A multimodal logistics service network design with time windows and environmental concerns.

Science.gov (United States)

Zhang, Dezhi; He, Runzhong; Li, Shuangyan; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained.

Experiments in Multimodal Information Presentation

NARCIS (Netherlands)

van Hooijdonk, Charlotte; Bosma, W.E.; Krahmer, Emiel; Maes, Alfons; Theune, Mariet; van den Bosch, Antal; Bouma, Gosse

In this chapter we describe three experiments investigating multimodal information presentation in the context of a medical QA system. In Experiment 1, we wanted to know how non-experts design (multimodal) answers to medical questions, distinguishing between what questions and how questions. In

Modeling multimodal human-computer interaction

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.

2004-01-01

Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze

Multimodal Discourse Analysis of the Movie "Argo"

Science.gov (United States)

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…

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

Science.gov (United States)

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.

A multimodal 3D framework for fire characteristics estimation

Science.gov (United States)

Toulouse, T.; Rossi, L.; Akhloufi, M. A.; Pieri, A.; Maldague, X.

2018-02-01

In the last decade we have witnessed an increasing interest in using computer vision and image processing in forest fire research. Image processing techniques have been successfully used in different fire analysis areas such as early detection, monitoring, modeling and fire front characteristics estimation. While the majority of the work deals with the use of 2D visible spectrum images, recent work has introduced the use of 3D vision in this field. This work proposes a new multimodal vision framework permitting the extraction of the three-dimensional geometrical characteristics of fires captured by multiple 3D vision systems. The 3D system is a multispectral stereo system operating in both the visible and near-infrared (NIR) spectral bands. The framework supports the use of multiple stereo pairs positioned so as to capture complementary views of the fire front during its propagation. Multimodal registration is conducted using the captured views in order to build a complete 3D model of the fire front. The registration process is achieved using multisensory fusion based on visual data (2D and NIR images), GPS positions and IMU inertial data. Experiments were conducted outdoors in order to show the performance of the proposed framework. The obtained results are promising and show the potential of using the proposed framework in operational scenarios for wildland fire research and as a decision management system in fighting.

Multimodal approaches for emotion recognition: a survey

Science.gov (United States)

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.

HCI^2 Framework: A software framework for multimodal human-computer interaction systems

NARCIS (Netherlands)

Shen, Jie; Pantic, Maja

2013-01-01

This paper presents a novel software framework for the development and research in the area of multimodal human-computer interface (MHCI) systems. The proposed software framework, which is called the HCI∧2 Framework, is built upon publish/subscribe (P/S) architecture. It implements a

Multimodal exemplification: The expansion of meaning in electronic ...

African Journals Online (AJOL)

Functional Multimodal Discourse Analysis (SF-MDA) and argues for improving their exemplifica-tion multimodally. Multimodal devices, if well coordinated, can help optimize e-dictionary exam-ples in informativity, diversity, dynamicity and ...

Multimodal route choice models of public transport passengers in the Greater Copenhagen Area

DEFF Research Database (Denmark)

Anderson, Marie Karen; Nielsen, Otto Anker; Prato, Carlo Giacomo

2014-01-01

Understanding route choice behavior is crucial to explain travelers’ preferences and to predict traffic flows under different scenarios. A growing body of literature has concentrated on public transport users without, however, concentrating on multimodal public transport networks because......,641 public transport users in the Greater Copenhagen Area.A two-stage approach consisting of choice set generation and route choice model estimation allowed uncovering the preferences of the users of this multimodal large-scale public transport network. The results illustrate the rates of substitution...... not only of the in-vehicle times for different public transport modes, but also of the other time components (e.g., access, walking, waiting, transfer) composing the door-to-door experience of using a multimodal public transport network, differentiating by trip length and purpose, and accounting...

Contemporary approach to neurologic prognostication of coma after cardiac arrest.

Science.gov (United States)

Ben-Hamouda, Nawfel; Taccone, Fabio S; Rossetti, Andrea O; Oddo, Mauro

2014-11-01

Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.

The Impact of Multimodal Texts on Reading Achievement: A Study of Iranian Secondary School Learners

Directory of Open Access Journals (Sweden)

Bahareh Baharani

2015-07-01

Full Text Available This study was designed to investigate the impact of multimodal text on reading comprehension test performance of Iranian intermediate learners. A total of 80 students participated in this study. All of them were Iranian female EFL learners with the age ranging from 16 to 18. They were selected from a boarding high school in Nasr Abad, Torbat Jam in Khorasan e Razavi, Iran. The students were randomly settled in four groups, who received different instructional approaches through using linear texts, multimodal printed texts, non-printed multimodal texts, and both multimodal printed and non-printed texts.  A pre-test and post-test were used to find out the differences before and after the experimental treatment.  The results reflected that the printed and non-printed multimodal texts had significant impact on reading comprehension test performance. In contrast, applying linear texts or traditional texts did not exert significant influence on reading comprehension ability of the participants. The findings provide useful hints for language instructors to improve effectiveness of instructional reading curriculums and reading ability of language learners. The participants who learned reading comprehension through using multimodal printed and non-printed texts enjoy reading programs and develop their intrinsic and extrinsic motivation for improving reading ability.

Behavioural Models for Route Choice of Passengers in Multimodal Public Transport Networks

DEFF Research Database (Denmark)

Anderson, Marie Karen

in the estimation of route choice models of public transport users based upon observed choices. Public transport route choice models have not benefitted from the same technological enhancements as car models because of the necessity (i) to collect additional information concerning lines and transfers, and (ii...... modes, public transport modes, lines, transfers, egress modes) is large. This thesis proposes a doubly stochastic approach for generating alternative routes that are relevant to travellers, since the method allows accounting for both perceived costs of the network elements and heterogeneity......The subject of this thesis is behavioural models for route choice of passengers in multimodal public transport networks. While research in sustainable transport has dedicated much attention toward the determinants of choice between car and sustainable travel options, it has devoted less attention...

Architecture of the Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet)

Energy Technology Data Exchange (ETDEWEB)

Aiken, R.J.; Carlson, R.A.; Foster, I.T. [and others

1997-01-01

The research and education (R&E) community requires persistent and scaleable network infrastructure to concurrently support production and research applications as well as network research. In the past, the R&E community has relied on supporting parallel network and end-node infrastructures, which can be very expensive and inefficient for network service managers and application programmers. The grand challenge in networking is to provide support for multiple, concurrent, multi-layer views of the network for the applications and the network researchers, and to satisfy the sometimes conflicting requirements of both while ensuring one type of traffic does not adversely affect the other. Internet and telecommunications service providers will also benefit from a multi-modal infrastructure, which can provide smoother transitions to new technologies and allow for testing of these technologies with real user traffic while they are still in the pre-production mode. The authors proposed approach requires the use of as much of the same network and end system infrastructure as possible to reduce the costs needed to support both classes of activities (i.e., production and research). Breaking the infrastructure into segments and objects (e.g., routers, switches, multiplexors, circuits, paths, etc.) gives the capability to dynamically construct and configure the virtual active networks to address these requirements. These capabilities must be supported at the campus, regional, and wide-area network levels to allow for collaboration by geographically dispersed groups. The Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet) described in this report is an initial architecture and framework designed to identify and support the capabilities needed for the proposed combined infrastructure and to address related research issues.

Exploring the requirements for multimodal interaction for mobile devices in an end-to-end journey context.

Science.gov (United States)

Krehl, Claudia; Sharples, Sarah

2012-01-01

The paper investigates the requirements for multimodal interaction on mobile devices in an end-to-end journey context. Traditional interfaces are deemed cumbersome and inefficient for exchanging information with the user. Multimodal interaction provides a different user-centred approach allowing for more natural and intuitive interaction between humans and computers. It is especially suitable for mobile interaction as it can overcome additional constraints including small screens, awkward keypads, and continuously changing settings - an inherent property of mobility. This paper is based on end-to-end journeys where users encounter several contexts during their journeys. Interviews and focus groups explore the requirements for multimodal interaction design for mobile devices by examining journey stages and identifying the users' information needs and sources. Findings suggest that multimodal communication is crucial when users multitask. Choosing suitable modalities depend on user context, characteristics and tasks.

Demonstration of analyzers for multimode photonic time-bin qubits

Science.gov (United States)

Jin, Jeongwan; Agne, Sascha; Bourgoin, Jean-Philippe; Zhang, Yanbao; Lütkenhaus, Norbert; Jennewein, Thomas

2018-04-01

We demonstrate two approaches for unbalanced interferometers as time-bin qubit analyzers for quantum communication, robust against mode distortions and polarization effects as expected from free-space quantum communication systems including wavefront deformations, path fluctuations, pointing errors, and optical elements. Despite strong spatial and temporal distortions of the optical mode of a time-bin qubit, entangled with a separate polarization qubit, we verify entanglement using the Negative Partial Transpose, with the measured visibility of up to 0.85 ±0.01 . The robustness of the analyzers is further demonstrated for various angles of incidence up to 0 .2∘ . The output of the interferometers is coupled into multimode fiber yielding a high system throughput of 0.74. Therefore, these analyzers are suitable and efficient for quantum communication over multimode optical channels.

A Multimodal Approach to Post-Operative Pain Relief in Children Undergoing Ambulatory Eye Surgery

Directory of Open Access Journals (Sweden)

V V Jaichandran

2008-01-01

Full Text Available This study was carried to assess the efficacy of multimodal analgesia using ketorolac and fentanyl, for post-operative pain relief in children undergoing ambulatory eye surgery. Total of 161 children, aged 1 to 5 years, were randomly stratified to three different analgesic regimens: Group A Ketorolac 0.75 mg.kg -1 I.M. , Group B Fentanyl 0.75 µg.kg -1 I.V. and Group C Ketorolac 0.50mg.kg -1 I.M. and Fentanyl 0.50µg.kg -1 I.V. Ketorolac I.M. was given 45 minutes before extubation and fentanyl I.V. was given soon after extubation in the respective groups. Post-operative pain was assessed in a double blinded manner using Children′s Hospital of Eastern Onatario Pain Scale (CHEOPS scoring system and by recording the heart rate at 10, 30 and 60 minutes. If the score was above 8, the child was left with the parents. In case the score did not improve and persisted to be greater than 8, fentanyl 0.50µg.kg -1 I.V. was given as the rescue analgesia. The incidence of nausea, vomiting, sleep disturbances or any other complaints were recorded by a staff nurse 24 hours post operatively. Mean CHEOPS score at 10, 30 and 60 minutes and mean heart rate at 10 and 30 minutes were significantly higher for Group A compared with Group C. Mean pain score emerged significantly higher for Group B compared with Group C at 30 and 60 minutes, (P< 0.01. Rescue analgesia required was significantly higher in Group A compared to Groups B and C, (P< 0.0001. Post-operatively, significant incidence of drowsiness was reported in children in Group B compared to Groups A and C, (P< 0.01. A multimodal approach using both ketorolac and fentanyl at low doses produce effective and safe analgesia in children undergoing ambula-tory eye surgery.

A multilingual and multimodal approach to literacy teaching and learning in urban education: a collaborative inquiry project in an urban inner city elementary school

Directory of Open Access Journals (Sweden)

Burcu eYaman Ntelioglou

2014-06-01

Full Text Available This paper presents findings from a collaborative inquiry project that explored teaching approaches that highlight the significance of multilingualism, multimodality and multiliteracies in classrooms with high numbers of English language learners (ELLs. The research took place in an inner city elementary school with a large population of recently arrived and Canadian-born linguistically and culturally diverse students from Gambian, Indian, Mexican, Sri Lankan, Tibetan and Vietnamese backgrounds, as well as a recent wave of Roma students from Hungary. A high number of these students were from families with low-SES. The collaboration between two Grade 3 teachers and university-based researchers sought to create instructional approaches that would support students’ academic engagement and literacy learning. In this paper, we described one of the projects that took place in this class, exploring how a descriptive writing unit could be implemented in a way that connected with students’ lives and enabled them to use their home languages, through the creation of multiple texts, using creative writing, digital technologies and drama pedagogy. This kind of multilingual and multimodal classroom practice changed the classroom dynamics and allowed the students access to identity positions of expertise, increasing their literacy investment, literacy engagement and learning.

Image recovery from defocused 2D fluorescent images in multimodal digital holographic microscopy.

Science.gov (United States)

Quan, Xiangyu; Matoba, Osamu; Awatsuji, Yasuhiro

2017-05-01

A technique of three-dimensional (3D) intensity retrieval from defocused, two-dimensional (2D) fluorescent images in the multimodal digital holographic microscopy (DHM) is proposed. In the multimodal DHM, 3D phase and 2D fluorescence distributions are obtained simultaneously by an integrated system of an off-axis DHM and a conventional epifluorescence microscopy, respectively. This gives us more information of the target; however, defocused fluorescent images are observed due to the short depth of field. In this Letter, we propose a method to recover the defocused images based on the phase compensation and backpropagation from the defocused plane to the focused plane using the distance information that is obtained from a 3D phase distribution. By applying Zernike polynomial phase correction, we brought back the fluorescence intensity to the focused imaging planes. The experimental demonstration using fluorescent beads is presented, and the expected applications are suggested.

Semiotic Work: Applied Linguistics and a Social Semiotic Account of Multimodality

Science.gov (United States)

Kress, Gunther

2015-01-01

This article imagines a tussle between Multimodality, focused on "modes," and Applied Linguistics (AL), based on "language." A Social Semiotic approach to MM treats "speech" and "writing" as modes with distinct affordances, and, as all modes, treats them as "partial" means of communication. The…

Cross-Discipline Bio-Nanostructured Enhanced Photonic Multimode-Sensor Science

Science.gov (United States)

2017-05-23

AFRL-AFOSR-CL-TR-2017-0007 Multimode bio-nano sensor Fernando Danilo Gonzalez-Nilo UNIVERSIDAD NACIONAL ANDRES BELLO Final Report 05/23/2017...5e.  TASK NUMBER 5f.  WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) UNIVERSIDAD NACIONAL ANDRES BELLO REPUBLICA 237 SANTIAGO...Ciencias Biologicas Universidad Andres Bello Avenida Republica 239, Santiago, Chile. Objective: The proposed cross-discipline experimental study aims to

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

Science.gov (United States)

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

Gestational Trophoblastic Disease: A Multimodality Imaging Approach with Impact on Diagnosis and Management

Directory of Open Access Journals (Sweden)

Sunita Dhanda

2014-01-01

Full Text Available Gestational trophoblastic disease is a condition of uncertain etiology, comprised of hydatiform mole (complete and partial, invasive mole, choriocarcinoma, and placental site trophoblastic tumor. It arises from abnormal proliferation of trophoblastic tissue. Early diagnosis of gestational trophoblastic disease and its potential complications is important for timely and successful management of the condition with preservation of fertility. Initial diagnosis is based on a multimodality approach: encompassing clinical features, serial quantitative β-hCG titers, and pelvic ultrasonography. Pelvic magnetic resonance imaging (MRI is sometimes used as a problem-solving tool to assess the depth of myometrial invasion and extrauterine disease spread in equivocal and complicated cases. Chest radiography, body computed tomography (CT, and brain MRI have been recommended as investigative tools for overall disease staging. Angiography has a role in management of disease complications and metastases. Efficacy of PET (positron emission tomography and PET/CT in the evaluation of recurrent or metastatic disease has not been adequately investigated yet. This paper discusses the imaging features of gestational trophoblastic disease on various imaging modalities and the role of different imaging techniques in the diagnosis and management of this entity.

New developments in multimodal clinical multiphoton tomography

Science.gov (United States)

König, Karsten

2011-03-01

80 years ago, the PhD student Maria Goeppert predicted in her thesis in Goettingen, Germany, two-photon effects. It took 30 years to prove her theory, and another three decades to realize the first two-photon microscope. With the beginning of this millennium, first clinical multiphoton tomographs started operation in research institutions, hospitals, and in the cosmetic industry. The multiphoton tomograph MPTflexTM with its miniaturized flexible scan head became the Prism-Award 2010 winner in the category Life Sciences. Multiphoton tomographs with its superior submicron spatial resolution can be upgraded to 5D imaging tools by adding spectral time-correlated single photon counting units. Furthermore, multimodal hybrid tomographs provide chemical fingerprinting and fast wide-field imaging. The world's first clinical CARS studies have been performed with a hybrid multimodal multiphoton tomograph in spring 2010. In particular, nonfluorescent lipids and water as well as mitochondrial fluorescent NAD(P)H, fluorescent elastin, keratin, and melanin as well as SHG-active collagen have been imaged in patients with dermatological disorders. Further multimodal approaches include the combination of multiphoton tomographs with low-resolution imaging tools such as ultrasound, optoacoustic, OCT, and dermoscopy systems. Multiphoton tomographs are currently employed in Australia, Japan, the US, and in several European countries for early diagnosis of skin cancer (malignant melanoma), optimization of treatment strategies (wound healing, dermatitis), and cosmetic research including long-term biosafety tests of ZnO sunscreen nanoparticles and the measurement of the stimulated biosynthesis of collagen by anti-ageing products.

Entanglement and Wigner Function Negativity of Multimode Non-Gaussian States

Science.gov (United States)

Walschaers, Mattia; Fabre, Claude; Parigi, Valentina; Treps, Nicolas

2017-11-01

Non-Gaussian operations are essential to exploit the quantum advantages in optical continuous variable quantum information protocols. We focus on mode-selective photon addition and subtraction as experimentally promising processes to create multimode non-Gaussian states. Our approach is based on correlation functions, as is common in quantum statistical mechanics and condensed matter physics, mixed with quantum optics tools. We formulate an analytical expression of the Wigner function after the subtraction or addition of a single photon, for arbitrarily many modes. It is used to demonstrate entanglement properties specific to non-Gaussian states and also leads to a practical and elegant condition for Wigner function negativity. Finally, we analyze the potential of photon addition and subtraction for an experimentally generated multimode Gaussian state.

Multi-focus beam shaping of high power multimode lasers

Science.gov (United States)

Laskin, Alexander; Volpp, Joerg; Laskin, Vadim; Ostrun, Aleksei

2017-08-01

Beam shaping of powerful multimode fiber lasers, fiber-coupled solid-state and diode lasers is of great importance for improvements of industrial laser applications. Welding, cladding with millimetre scale working spots benefit from "inverseGauss" intensity profiles; performance of thick metal sheet cutting, deep penetration welding can be enhanced when distributing the laser energy along the optical axis as more efficient usage of laser energy, higher edge quality and reduction of the heat affected zone can be achieved. Building of beam shaping optics for multimode lasers encounters physical limitations due to the low beam spatial coherence of multimode fiber-coupled lasers resulting in big Beam Parameter Products (BPP) or M² values. The laser radiation emerging from a multimode fiber presents a mixture of wavefronts. The fiber end can be considered as a light source which optical properties are intermediate between a Lambertian source and a single mode laser beam. Imaging of the fiber end, using a collimator and a focusing objective, is a robust and widely used beam delivery approach. Beam shaping solutions are suggested in form of optics combining fiber end imaging and geometrical separation of focused spots either perpendicular to or along the optical axis. Thus, energy of high power lasers is distributed among multiple foci. In order to provide reliable operation with multi-kW lasers and avoid damages the optics are designed as refractive elements with smooth optical surfaces. The paper presents descriptions of multi-focus optics as well as examples of intensity profile measurements of beam caustics and application results.

Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

Science.gov (United States)

Morishima, Shigeo; Nakamura, Satoshi

2004-12-01

We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

Reference resolution in multi-modal interaction: Preliminary observations

NARCIS (Netherlands)

González González, G.R.; Nijholt, Antinus

2002-01-01

In this paper we present our research on multimodal interaction in and with virtual environments. The aim of this presentation is to emphasize the necessity to spend more research on reference resolution in multimodal contexts. In multi-modal interaction the human conversational partner can apply

Reference Resolution in Multi-modal Interaction: Position paper

NARCIS (Netherlands)

Fernando, T.; Nijholt, Antinus

2002-01-01

In this position paper we present our research on multimodal interaction in and with virtual environments. The aim of this presentation is to emphasize the necessity to spend more research on reference resolution in multimodal contexts. In multi-modal interaction the human conversational partner can

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

Science.gov (United States)

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.

Reconfigurable Bandpass Sigma-Delta Modulator With Programmable NTF for Low-IF Multi-Mode Receivers

DEFF Research Database (Denmark)

Zhang, Ke; Mikkelsen, Jan H.; Shen, Ming

2012-01-01

transfer function of the loop while still maintaining stability. Compared with conventional multi-mode BPSDM, employing cascade structures and multi-bit sub-ADCs, the proposed modulator features many attractive advantages, such as (1) avoiding coefficient mismatch between analog and digital components...

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun; Wu, Chunho; Mok, Ricky; Peng, Chengbin; Zhang, Zhaolei

2012-01-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun

2012-07-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Multimode-singlemode-multimode fiber sensor for alcohol sensing application

Science.gov (United States)

Rofi'ah, Iftihatur; Hatta, A. M.; Sekartedjo, Sekartedjo

2016-11-01

Alcohol is volatile and flammable liquid which is soluble substances both on polar and non polar substances that has been used in some industrial sectors. Alcohol detection method now widely used one of them is the optical fiber sensor. In this paper used fiber optic sensor based on Multimode-Single-mode-Multimode (MSM) to detect alcohol solution at a concentration range of 0-3%. The working principle of sensor utilizes the modal interference between the core modes and the cladding modes, thus make the sensor sensitive to environmental changes. The result showed that characteristic of the sensor not affect the length of the single-mode fiber (SMF). We obtain that the sensor with a length of 5 mm of single-mode can sensing the alcohol with a sensitivity of 0.107 dB/v%.

Multimodal pain management after arthroscopic surgery

DEFF Research Database (Denmark)

Rasmussen, Sten

Multimodal Pain Management after Arthroscopic Surgery By Sten Rasmussen, M.D. The thesis is based on four randomized controlled trials. The main hypothesis was that multimodal pain treatment provides faster recovery after arthroscopic surgery. NSAID was tested against placebo after knee arthroscopy...

A robo-pigeon based on an innovative multi-mode telestimulation system.

Science.gov (United States)

Yang, Junqing; Huai, Ruituo; Wang, Hui; Lv, Changzhi; Su, Xuecheng

2015-01-01

In this paper, we describe a new multi-mode telestimulation system for brain-microstimulation for the navigation of a robo-pigeon, a new type of bio-robot based on Brain-Computer Interface (BCI) techniques. The multi-mode telestimulation system overcomes neuron adaptation that was a key shortcoming of the previous single-mode stimulation by the use of non-steady TTL biphasic pulses accomplished by randomly alternating pulse modes. To improve efficiency, a new behavior model ("virtual fear") is proposed and applied to the robo-pigeon. Unlike the previous "virtual reward" model, the "virtual fear" behavior model does not require special training. The performance and effectiveness of the system to alleviate the adaptation of neurons was verified by a robo-pigeon navigation test, simultaneously confirming the practicality of the "virtual fear" behavioral model.

Multimodality, creativity and children's meaning-making: Drawings ...

African Journals Online (AJOL)

Multimodality, creativity and children's meaning-making: Drawings, writings, imaginings. ... Framed by social semiotic theories of communication, multimodal ... to create imaginary worlds and express meanings according to their interests.

360-Degree Rhetorical Analysis of Job Hunting: A Four-Part, Multimodal Project

Science.gov (United States)

Ding, Huiling; Ding, Xin

2013-01-01

This article proposes the use of a four-component multimodal employment project that offers students a 360-degree understanding of the rhetorical situations surrounding job searches. More specifically, we argue for the use of the four deliverables of written resumes and cover letters, mock oral onsite interview, video resume analysis, and peer…

A novel image fusion algorithm based on 2D scale-mixing complex wavelet transform and Bayesian MAP estimation for multimodal medical images

Directory of Open Access Journals (Sweden)

Abdallah Bengueddoudj

2017-05-01

Full Text Available In this paper, we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform (2D-SMCWT. The fusion of the detail 2D-SMCWT coefficients is performed via a Bayesian Maximum a Posteriori (MAP approach by considering a trivariate statistical model for the local neighboring of 2D-SMCWT coefficients. For the approximation coefficients, a new fusion rule based on the Principal Component Analysis (PCA is applied. We conduct several experiments using three different groups of multimodal medical images to evaluate the performance of the proposed method. The obtained results prove the superiority of the proposed method over the state of the art fusion methods in terms of visual quality and several commonly used metrics. Robustness of the proposed method is further tested against different types of noise. The plots of fusion metrics establish the accuracy of the proposed fusion method.

Multimodal manifold-regularized transfer learning for MCI conversion prediction.

Science.gov (United States)

Cheng, Bo; Liu, Mingxia; Suk, Heung-Il; Shen, Dinggang; Zhang, Daoqiang

2015-12-01

As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk pre-symptomatically. Unlike most previous methods that used only the samples from a target domain to train a classifier, in this paper, we propose a novel multimodal manifold-regularized transfer learning (M2TL) method that jointly utilizes samples from another domain (e.g., AD vs. normal controls (NC)) as well as unlabeled samples to boost the performance of the MCI conversion prediction. Specifically, the proposed M2TL method includes two key components. The first one is a kernel-based maximum mean discrepancy criterion, which helps eliminate the potential negative effect induced by the distributional difference between the auxiliary domain (i.e., AD and NC) and the target domain (i.e., MCI converters (MCI-C) and MCI non-converters (MCI-NC)). The second one is a semi-supervised multimodal manifold-regularized least squares classification method, where the target-domain samples, the auxiliary-domain samples, and the unlabeled samples can be jointly used for training our classifier. Furthermore, with the integration of a group sparsity constraint into our objective function, the proposed M2TL has a capability of selecting the informative samples to build a robust classifier. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database validate the effectiveness of the proposed method by significantly improving the classification accuracy of 80.1 % for MCI conversion prediction, and also outperforming the state-of-the-art methods.

Fiber Optic Pressure Sensor using Multimode Interference

International Nuclear Information System (INIS)

Ruiz-Perez, V I; Sanchez-Mondragon, J J; Basurto-Pensado, M A; LiKamWa, P; May-Arrioja, D A

2011-01-01

Based on the theory of multimode interference (MMI) and self-image formation, we developed a novel intrinsic optical fiber pressure sensor. The sensing element consists of a section of multimode fiber (MMF) without cladding spliced between two single mode fibers (SMF). The MMI pressure sensor is based on the intensity changes that occur in the transmitted light when the effective refractive index of the MMF is changed. Basically, a thick layer of Polydimethylsiloxane (PDMS) is placed in direct contact with the MMF section, such that the contact area between the PDMS and the fiber will change proportionally with the applied pressure, which results in a variation of the transmitted light intensity. Using this configuration, a good correlation between the measured intensity variations and the applied pressure is obtained. The sensitivity of the sensor is 3 μV/psi, for a range of 0-60 psi, and the maximum resolution of our system is 0.25 psi. Good repeatability is also observed with a standard deviation of 0.0019. The key feature of the proposed pressure sensor is its low fabrication cost, since the cost of the MMF is minimal.

Fiber Optic Pressure Sensor using Multimode Interference

Energy Technology Data Exchange (ETDEWEB)

Ruiz-Perez, V I; Sanchez-Mondragon, J J [INAOE, Apartado Postal 51 y 216, Puebla 72000 (Mexico); Basurto-Pensado, M A [CIICAp, Universidad Autonoma del Estado de Morelos (Mexico); LiKamWa, P [CREOL, University of Central Florida, Orlando, FL 32816 (United States); May-Arrioja, D A, E-mail: iruiz@inaoep.mx, E-mail: mbasurto@uaem.mx, E-mail: delta_dirac@hotmail.com, E-mail: daniel_may_arrioja@hotmail.com [UAT Reynosa Rodhe, Universidad Autonoma de Tamaulipas (Mexico)

2011-01-01

Based on the theory of multimode interference (MMI) and self-image formation, we developed a novel intrinsic optical fiber pressure sensor. The sensing element consists of a section of multimode fiber (MMF) without cladding spliced between two single mode fibers (SMF). The MMI pressure sensor is based on the intensity changes that occur in the transmitted light when the effective refractive index of the MMF is changed. Basically, a thick layer of Polydimethylsiloxane (PDMS) is placed in direct contact with the MMF section, such that the contact area between the PDMS and the fiber will change proportionally with the applied pressure, which results in a variation of the transmitted light intensity. Using this configuration, a good correlation between the measured intensity variations and the applied pressure is obtained. The sensitivity of the sensor is 3 {mu}V/psi, for a range of 0-60 psi, and the maximum resolution of our system is 0.25 psi. Good repeatability is also observed with a standard deviation of 0.0019. The key feature of the proposed pressure sensor is its low fabrication cost, since the cost of the MMF is minimal.

Feature-based Alignment of Volumetric Multi-modal Images

Science.gov (United States)

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

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

Science.gov (United States)

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.

Deep assessment: an exploratory study of game-based, multimodal learning in Epidemic

Directory of Open Access Journals (Sweden)

Jennifer Jenson

2016-03-01

Full Text Available n this study, we examine what and how intermediate age students learned from playing in a health-focused game-based digital learning environment, Epidemic. Epidemic is a playful interactive environment designed to deliver factual knowledge, invite critical understanding, and encourage effective self-care practices in dealing with viral contagious diseases, using a social networking interface to integrate both serious games and game-like multimodal design projects. Epidemic invites a playful approach to its deadly serious core concern – communicable disease – in order to see what happens when students are encouraged to critically approach information from multiple or contradictory perspectives. To identify what participants learned while interacting within Epidemic, we deployed two instructional and assessment models, noting the differences each instructional approach could potentially make, and what approach to assessment might help us evaluate game-based learning. We found that each approach provided importantly different perspectives on what and how students learned, and on the very meaning of student success. Recognizing that traditional assessment tools based in print-cultural literacy may prove increasingly ill-suited for assessing emergent multimodal literacies in game-based learning environments, this study seeks to contribute to a growing body of work on the development of novel assessments for learning.

Multi-Modality Registration And Fusion Of Medical Image Data

International Nuclear Information System (INIS)

Kassak, P.; Vencko, D.; Cerovsky, I.

2008-01-01

Digitalisation of health care providing facilities allows US to maximize the usage of digital data from one patient obtained by various modalities. Complex view on to the problem can be achieved from the site of morphology as well as functionality. Multi-modal registration and fusion of medical image data is one of the examples that provides improved insight and allows more precise approach and treatment. (author)

Multimodal Classification of Violent Online Political Extremism Content with Graph Convolutional Networks

NARCIS (Netherlands)

Rudinac, S.; Gornishka, I.; Worring, M.

2017-01-01

In this paper we present a multimodal approach to categorizing user posts based on their discussion topic. To integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform, we deploy graph convolutional

Revisiting persuasion in oral academic and professional genres: Towards a methodological framework for Multimodal Discourse Analysis of research dissemination talks

Directory of Open Access Journals (Sweden)

Julia Valeiras-Jurado

2018-04-01

Full Text Available Previous work on oral genres (Kress & Van Leeuwen, 2001; Kress, 2010; Bateman, 2011 as well as on persuasion (O’Keefe, 2002; Perloff, 2003; Poggi & Pelachaud, 2008 has indicated that effective persuasive oral communication depends heavily on the use of a wide range of different semiotic modes including words, gestures and intonation. However, little attention has been paid so far to how speakers convey their communicative intentions orchestrating different modes into a coherent multimodal ensemble (Kress, 2010. In this paper we propose a methodological framework for Multimodal Discourse Analysis (MDA of persuasion in oral academic and professional genres. Drawing on previous studies on persuasion (Fuertes-Olivera et al., 2001; O’Keefe, 2002; Perloff, 2003; Virtanen & Halmari, 2005; Dafouz-Milne, 2008, our framework combines earlier proposals for MDA (Querol-Julián, 2011; Querol-Julián & Fortanet-Gómez, 2014 with an ethnographic perspective (Rubin & Rubin, 1995. Our study focuses specifically on the analysis of persuasive strategies used in dissemination talks. The proposed MDA caters for the following modes: words, intonation, head movements and gestures. Preliminary findings hint at a relation between persuasion and so-called modal density (Norris, 2004. Finally, we propose a tentative taxonomy of persuasive strategies and how they are realised multimodally.

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

Science.gov (United States)

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)

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

Science.gov (United States)

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.

(Re-)Examination of Multimodal Augmented Reality

NARCIS (Netherlands)

Rosa, N.E.; Werkhoven, P.J.; Hürst, W.O.

2016-01-01

The majority of augmented reality (AR) research has been concerned with visual perception, however the move towards multimodality is imminent. At the same time, there is no clear vision of what multimodal AR is. The purpose of this position paper is to consider possible ways of examining AR other

(In)Flexibility of Constituency in Japanese in Multi-Modal Categorial Grammar with Structured Phonology

Science.gov (United States)

Kubota, Yusuke

2010-01-01

This dissertation proposes a theory of categorial grammar called Multi-Modal Categorial Grammar with Structured Phonology. The central feature that distinguishes this theory from the majority of contemporary syntactic theories is that it decouples (without completely segregating) two aspects of syntax--hierarchical organization (reflecting…

Multimodal integration of anatomy and physiology classes: How instructors utilize multimodal teaching in their classrooms

Science.gov (United States)

McGraw, Gerald M., Jr.

Multimodality is the theory of communication as it applies to social and educational semiotics (making meaning through the use of multiple signs and symbols). The term multimodality describes a communication methodology that includes multiple textual, aural, and visual applications (modes) that are woven together to create what is referred to as an artifact. Multimodal teaching methodology attempts to create a deeper meaning to course content by activating the higher cognitive areas of the student's brain, creating a more sustained retention of the information (Murray, 2009). The introduction of multimodality educational methodologies as a means to more optimally engage students has been documented within educational literature. However, studies analyzing the distribution and penetration into basic sciences, more specifically anatomy and physiology, have not been forthcoming. This study used a quantitative survey design to determine the degree to which instructors integrated multimodality teaching practices into their course curricula. The instrument used for the study was designed by the researcher based on evidence found in the literature and sent to members of three associations/societies for anatomy and physiology instructors: the Human Anatomy and Physiology Society; the iTeach Anatomy & Physiology Collaborate; and the American Physiology Society. Respondents totaled 182 instructor members of two- and four-year, private and public higher learning colleges collected from the three organizations collectively with over 13,500 members in over 925 higher learning institutions nationwide. The study concluded that the expansion of multimodal methodologies into anatomy and physiology classrooms is at the beginning of the process and that there is ample opportunity for expansion. Instructors continue to use lecture as their primary means of interaction with students. Email is still the major form of out-of-class communication for full-time instructors. Instructors with

Multimodality Imaging Approach towards Primary Aortic Sarcomas Arising after Endovascular Abdominal Aortic Aneurysm Repair: Case Series Report

Energy Technology Data Exchange (ETDEWEB)

Kamran, Mudassar, E-mail: kamranm@mir.wustl.edu; Fowler, Kathryn J., E-mail: fowlerk@mir.wustl.edu; Mellnick, Vincent M., E-mail: mellnickv@mir.wustl.edu [Washington University School of Medicine, Mallinckrodt Institute of Radiology (United States); Sicard, Gregorio A., E-mail: sicard@wudosis.wustl.edu [Washington University School of Medicine, Department of Surgery (United States); Narra, Vamsi R., E-mail: narrav@mir.wustl.edu [Washington University School of Medicine, Mallinckrodt Institute of Radiology (United States)

2016-06-15

Primary aortic neoplasms are rare. Aortic sarcoma arising after endovascular aneurysm repair (EVAR) is a scarce subset of primary aortic malignancies, reports of which are infrequent in the published literature. The diagnosis of aortic sarcoma is challenging due to its non-specific clinical presentation, and the prognosis is poor due to delayed diagnosis, rapid proliferation, and propensity for metastasis. Post-EVAR, aortic sarcomas may mimic other more common aortic processes on surveillance imaging. Radiologists are rarely knowledgeable about this rare entity for which multimodality imaging and awareness are invaluable in early diagnosis. A series of three pathologically confirmed cases are presented to display the multimodality imaging features and clinical presentations of aortic sarcoma arising after EVAR.

Multimodale trafiknet i GIS (Multimodal Traffic Network in GIS)

DEFF Research Database (Denmark)

Kronbak, Jacob; Brems, Camilla Riff

1996-01-01

The report introduces the use of multi-modal traffic networks within a geographical Information System (GIS). The necessary theory of modelling multi-modal traffic network is reviewed and applied to the ARC/INFO GIS by an explorative example.......The report introduces the use of multi-modal traffic networks within a geographical Information System (GIS). The necessary theory of modelling multi-modal traffic network is reviewed and applied to the ARC/INFO GIS by an explorative example....

HCIDL: Human-computer interface description language for multi-target, multimodal, plastic user interfaces

Directory of Open Access Journals (Sweden)

Lamia Gaouar

2018-06-01

Full Text Available From the human-computer interface perspectives, the challenges to be faced are related to the consideration of new, multiple interactions, and the diversity of devices. The large panel of interactions (touching, shaking, voice dictation, positioning … and the diversification of interaction devices can be seen as a factor of flexibility albeit introducing incidental complexity. Our work is part of the field of user interface description languages. After an analysis of the scientific context of our work, this paper introduces HCIDL, a modelling language staged in a model-driven engineering approach. Among the properties related to human-computer interface, our proposition is intended for modelling multi-target, multimodal, plastic interaction interfaces using user interface description languages. By combining plasticity and multimodality, HCIDL improves usability of user interfaces through adaptive behaviour by providing end-users with an interaction-set adapted to input/output of terminals and, an optimum layout. Keywords: Model driven engineering, Human-computer interface, User interface description languages, Multimodal applications, Plastic user interfaces

A data-driven approach for evaluating multi-modal therapy in traumatic brain injury.

Science.gov (United States)

Haefeli, Jenny; Ferguson, Adam R; Bingham, Deborah; Orr, Adrienne; Won, Seok Joon; Lam, Tina I; Shi, Jian; Hawley, Sarah; Liu, Jialing; Swanson, Raymond A; Massa, Stephen M

2017-02-16

Combination therapies targeting multiple recovery mechanisms have the potential for additive or synergistic effects, but experimental design and analyses of multimodal therapeutic trials are challenging. To address this problem, we developed a data-driven approach to integrate and analyze raw source data from separate pre-clinical studies and evaluated interactions between four treatments following traumatic brain injury. Histologic and behavioral outcomes were measured in 202 rats treated with combinations of an anti-inflammatory agent (minocycline), a neurotrophic agent (LM11A-31), and physical therapy consisting of assisted exercise with or without botulinum toxin-induced limb constraint. Data was curated and analyzed in a linked workflow involving non-linear principal component analysis followed by hypothesis testing with a linear mixed model. Results revealed significant benefits of the neurotrophic agent LM11A-31 on learning and memory outcomes after traumatic brain injury. In addition, modulations of LM11A-31 effects by co-administration of minocycline and by the type of physical therapy applied reached statistical significance. These results suggest a combinatorial effect of drug and physical therapy interventions that was not evident by univariate analysis. The study designs and analytic techniques applied here form a structured, unbiased, internally validated workflow that may be applied to other combinatorial studies, both in animals and humans.

Assessing Digital Student Productions, a Design-Based Research Study on the Development of a Criteria-Based Assessment Tool for Students’ Digital Multimodal Productions

DEFF Research Database (Denmark)

Hoffmeyer, Mikkeline; Jensen, Jesper Juellund; Olsen, Marie Veisegaard

2017-01-01

Digital multimodal production is becoming increasingly important as a 21st century skill and as a learning condition in school (K-12). Moreover, there is a growing attention to the significance of criteria-based assessment for learning. Nevertheless, assessment of students’ digital multimodal...... productions is often vague or lacking. Therefore, the research project aims at developing a tool to support assessment of student’s digital multimodal productions through a design-based research method. This paper presents a proposal for issues to be considered through a prototyping phase, based on interviews...

From academic research articles to academic visual and video essays: Only a multimodal transition?

DEFF Research Database (Denmark)

Maier, Carmen Daniela

Drawing on an interdisciplinary theoretical framework, we propose to examine multimodal texts from the academic genre set belonging to the field of presenting and discussing research results: the academic research article, the academic visual essay and the academic video essay. The data...... for this study has been collected from academic journals that belong to print medium and to multimedia. In order to articulate an analytical model for the description and interpretation of these subgenres, we depart from the understanding of genres as linguistic categories influenced by specific situations...... subgenres will also be facilitated by applying theoretical approaches focused on knowledge communication because the academic discourse in these subgenres is based on specific meaning-making structures. The fact that these structures are linked to the subgenres’ common communicative purpose of representing...

Facial expression recognition in the wild based on multimodal texture features

Science.gov (United States)

Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

2016-11-01

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

Training of Perceptual Motor Skills in Multimodal Virtual Environments

Directory of Open Access Journals (Sweden)

Gopher Daniel

2011-12-01

Full Text Available Multimodal, immersive, virtual reality (VR techniques open new perspectives for perceptualmotor 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.

Multimodal processes scheduling in mesh-like network environment

Directory of Open Access Journals (Sweden)

Bocewicz Grzegorz

2015-06-01

Full Text Available Multimodal processes planning and scheduling play a pivotal role in many different domains including city networks, multimodal transportation systems, computer and telecommunication networks and so on. Multimodal process can be seen as a process partially processed by locally executed cyclic processes. In that context the concept of a Mesh-like Multimodal Transportation Network (MMTN in which several isomorphic subnetworks interact each other via distinguished subsets of common shared intermodal transport interchange facilities (such as a railway station, bus station or bus/tram stop as to provide a variety of demand-responsive passenger transportation services is examined. Consider a mesh-like layout of a passengers transport network equipped with different lines including buses, trams, metro, trains etc. where passenger flows are treated as multimodal processes. The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multimodal transportation processes scheduling encompassing passenger flow itineraries. Then, the main objective is to provide conditions guaranteeing solvability of particular transport lines scheduling, i.e. guaranteeing the right match-up of local cyclic acting bus, tram, metro and train schedules to a given passengers flow itineraries.

Mediating multimodal environmental knowledge across animation techniques

DEFF Research Database (Denmark)

Maier, Carmen Daniela

2011-01-01

://www.sustainlane.com/. The multimodal discourse analysis is meant to reveal how selection and representation of environmental knowledge about social actors, social actions, resources, time and space are influenced by animation techniques. Furthermore, in the context of this multimodal discourse analysis, their influence upon......The growing awareness of and concern about present environmental problems generate a proliferation of new forms of environmental discourses that are mediated in various ways. This chapter explores issues related to the ways in which environmental knowledge is multimodally communicated...

Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

Science.gov (United States)

Liu, Xingbin; Mei, Wenbo; Du, Huiqian

2018-02-13

In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.

PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

Directory of Open Access Journals (Sweden)

Xingxing Zhu

2018-05-01

Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

Multimodal Corpus Analysis as a Method for Ensuring Cultural Usability of Embodied Conversational Agents

DEFF Research Database (Denmark)

Nakano, Yukiko; Rehm, Matthias

2009-01-01

In this paper we propose the method of multimodal corpus analysis to collect enough empirical data for modeling the behavior of embodied conversational agents. This is a prerequisite to ensure the usability of such complex interactive systems. So far, the development of embodied agents suffers fr...

Designing Multimodal Mobile Interaction for a Text Messaging Application for Visually Impaired Users

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Carlos Duarte

2017-12-01

Full Text Available While mobile devices have experienced important accessibility advances in the past years, people with visual impairments still face important barriers, especially in specific contexts when both their hands are not free to hold the mobile device, like when walking outside. By resorting to a multimodal combination of body based gestures and voice, we aim to achieve full hands and vision free interaction with mobile devices. In this article, we describe this vision and present the design of a prototype, inspired by that vision, of a text messaging application. The article also presents a user study where the suitability of the proposed approach was assessed, and a performance comparison between our prototype and existing SMS applications was conducted. Study participants received positively the prototype, which also supported better performance in tasks that involved text editing.

Inverse Transformation: Unleashing Spatially Heterogeneous Dynamics with an Alternative Approach to XPCS Data Analysis.

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Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

2018-02-01

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.

Automatic event-based synchronization of multimodal data streams from wearable and ambient sensors

NARCIS (Netherlands)

Bannach, D.; Amft, O.D.; Lukowicz, P.; Barnaghi, P.; Moessner, K.; Presser, M.; Meissner, S.

2009-01-01

A major challenge in using multi-modal, distributed sensor systems for activity recognition is to maintain a temporal synchronization between individually recorded data streams. A common approach is to use well defined ‘synchronization actions’ performed by the user to generate, easily identifiable

Multidisciplinary approach and multimodal therapy in resected pancreatic cancer: Observational study Evaluación multidisciplinaria y tratamiento multimodal del cáncer de páncreas resecado: Estudio observacional

Directory of Open Access Journals (Sweden)

R. Morales

2011-01-01

Full Text Available Objective: analysis and evaluation of a multidisciplinary approach, postoperative results and survival of a group of patients with resected pancreatic cancer after a multimodal therapy. Design: descriptive, prospective and observational study. Patients: between January 2004 and December 2004, 124 patients with pancreatic cancer were evaluated. In 30 patients pancreatic resection was performed, and they are the object of this study. Results of preoperative evaluation, postoperative morbidity and mortality, and long term survival were studied. Results: diagnostic evaluation was completed in ambulatory basis in 20% of the patients. In 63% of cases, admission was done in the same day of surgery. In 3 patients (9%, tumor resection was not achieved, therefore, concordance between radiological and surgical resectability rate was 91%. Resectability rate was 24.1%. Surgical Mortality was 3.3%, with a global morbidity rate of 56.6%. Survival at one, two, three and, four years was 76.2%, 56.3%, 43%, y 27.3% respectively. Conclusions: technological development and coordination of efforts in multidisciplinary teams offer an accurate evaluation of tumor involvement, and may reduce the number of laparotomies without tumor resection. The application of a systematic and generalized multimodal treatment in pancreatic cancer is progressively showing a tendency of progressive increase in resectability and survival rates in pancreatic cancer.Objetivo: analizar la evaluación del abordaje multidisciplinario de un grupo de pacientes con cáncer de páncreas resecado, los resultados postoperatorios y la supervivencia tras la aplicación de un tratamiento multimodal. Diseño: estudio descriptivo prospectivo observacional. Pacientes: entre enero de 2004 y diciembre 2009 se evaluaron 124 pacientes con cáncer de páncreas. De ellos, se realizó la resección pancreática con intención curativa en 30 casos que constituyen el objeto del estudio. Se analizaron los

Multimodal MEMPRAGE, FLAIR, and R2* Segmentation to Resolve Dura and Vessels from Cortical Gray Matter

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Roberto Viviani

2017-05-01

Full Text Available While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.

Acoustic multimode interference and self-imaging phenomena realized in multimodal phononic crystal waveguides

International Nuclear Information System (INIS)

Zou, Qiushun; Yu, Tianbao; Liu, Jiangtao; Wang, Tongbiao; Liao, Qinghua; Liu, Nianhua

2015-01-01

We report an acoustic multimode interference effect and self-imaging phenomena in an acoustic multimode waveguide system which consists of M parallel phononic crystal waveguides (M-PnCWs). Results show that the self-imaging principle remains applicable for acoustic waveguides just as it does for optical multimode waveguides. To achieve the dispersions and replicas of the input acoustic waves produced along the propagation direction, we performed the finite element method on M-PnCWs, which support M guided modes within the target frequency range. The simulation results show that single images (including direct and mirrored images) and N-fold images (N is an integer) are identified along the propagation direction with asymmetric and symmetric incidence discussed separately. The simulated positions of the replicas agree well with the calculated values that are theoretically decided by self-imaging conditions based on the guided mode propagation analysis. Moreover, the potential applications based on this self-imaging effect for acoustic wavelength de-multiplexing and beam splitting in the acoustic field are also presented. (paper)

Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

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Nakamura Satoshi

2004-01-01

Full Text Available We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

Recent advances in acute pain management: understanding the mechanisms of acute pain, the prescription of opioids, and the role of multimodal pain therapy [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Richa Wardhan

2017-11-01

Full Text Available In this review, we discuss advances in acute pain management, including the recent report of the joint American Pain Society and American Academy of Pain Medicine task force on the classification of acute pain, the role of psychosocial factors, multimodal pain management, new non-opioid therapy, and the effect of the “opioid epidemic”. In this regard, we propose that a fundamental principle in acute pain management is identifying patients who are most at risk and providing an “opioid free anesthesia and postoperative analgesia”. This can be achieved by using a multimodal approach that includes regional anesthesia and minimizing the dose and the duration of opioid prescription. This allows prescribing medications that work through different mechanisms. We shall also look at the recent pharmacologic and treatment advances made in acute pain and regional anesthesia.

Quantitative multi-modal NDT data analysis

International Nuclear Information System (INIS)

Heideklang, René; Shokouhi, Parisa

2014-01-01

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundant information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity

Combined modal split and assignment model for the multimodal transportation network of the economic circle in China

Directory of Open Access Journals (Sweden)

Sh. Li

2009-09-01

Full Text Available Economic circles have been formed and developing in China. An economic circle consists of more than one closely adjoining central cities and their influence zones. It is always the major engine for the development of one country’s economy and even for the world economy. A combined modal split and assignment model with deterministic travel demand is proposed for modelling passengers’ choices of intercity bus and train which are two main competing modes in the multimodal transportation network of the economic circle. The generalized travel cost model of highway and railway are used incorporating travel time, ticket fare and passenger’s discomfort. On the highway network, the interactions of private vehicles and intercity buses are asymmetric. Thus, a variational inequality formulation is proposed to describe the combined model. The streamlined diagonalization algorithm is presented to solve the combined model. The multimodal transportation network based on Yangtze River Delta economic circle is presented to illustrate the proposed method. The results show the efficiency of the proposed model.

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

Science.gov (United States)

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI

Science.gov (United States)

Martinez-Torteya, Antonio; Treviño-Alvarado, Víctor; Tamez-Peña, José

2013-02-01

The accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) confers many clinical research and patient care benefits. Studies have shown that multimodal biomarkers provide better diagnosis accuracy of AD and MCI than unimodal biomarkers, but their construction has been based on traditional statistical approaches. The objective of this work was the creation of accurate AD and MCI diagnostic multimodal biomarkers using advanced bioinformatics tools. The biomarkers were created by exploring multimodal combinations of features using machine learning techniques. Data was obtained from the ADNI database. The baseline information (e.g. MRI analyses, PET analyses and laboratory essays) from AD, MCI and healthy control (HC) subjects with available diagnosis up to June 2012 was mined for case/controls candidates. The data mining yielded 47 HC, 83 MCI and 43 AD subjects for biomarker creation. Each subject was characterized by at least 980 ADNI features. A genetic algorithm feature selection strategy was used to obtain compact and accurate cross-validated nearest centroid biomarkers. The biomarkers achieved training classification accuracies of 0.983, 0.871 and 0.917 for HC vs. AD, HC vs. MCI and MCI vs. AD respectively. The constructed biomarkers were relatively compact: from 5 to 11 features. Those multimodal biomarkers included several widely accepted univariate biomarkers and novel image and biochemical features. Multimodal biomarkers constructed from previously and non-previously AD associated features showed improved diagnostic performance when compared to those based solely on previously AD associated features.

Conditional generation of arbitrary multimode entangled states of light with linear optics

International Nuclear Information System (INIS)

Fiurasek, J.; Massar, S.; Cerf, N. J.

2003-01-01

We propose a universal scheme for the probabilistic generation of an arbitrary multimode entangled state of light with finite expansion in Fock basis. The suggested setup involves passive linear optics, single-photon sources, strong coherent laser beams, and photodetectors with single-photon resolution. The efficiency of this setup may be greatly enhanced if, in addition, a quantum memory is available

Multimode laser beam analyzer instrument using electrically programmable optics.

Science.gov (United States)

Marraccini, Philip J; Riza, Nabeel A

2011-12-01

Presented is a novel design of a multimode laser beam analyzer using a digital micromirror device (DMD) and an electronically controlled variable focus lens (ECVFL) that serve as the digital and analog agile optics, respectively. The proposed analyzer is a broadband laser characterization instrument that uses the agile optics to smartly direct light to the required point photodetectors to enable beam measurements of minimum beam waist size, minimum waist location, divergence, and the beam propagation parameter M(2). Experimental results successfully demonstrate these measurements for a 500 mW multimode test laser beam with a wavelength of 532 nm. The minimum beam waist, divergence, and M(2) experimental results for the test laser are found to be 257.61 μm, 2.103 mrad, 1.600 and 326.67 μm, 2.682 mrad, 2.587 for the vertical and horizontal directions, respectively. These measurements are compared to a traditional scan method and the results of the beam waist are found to be within error tolerance of the demonstrated instrument.

Polarization Characterization of a Multi-Moded Feed Structure

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National Aeronautics and Space Administration — The Polarization Characterization of a Multi-Moded Feed Structure projects characterize the polarization response of a multi-moded feed horn as an innovative...

Multimodal imaging of spike propagation: a technical case report.

Science.gov (United States)

Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

2012-06-01

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

Filter. Remix. Make.: Cultivating Adaptability through Multimodality

Science.gov (United States)

Dusenberry, Lisa; Hutter, Liz; Robinson, Joy

2015-01-01

This article establishes traits of adaptable communicators in the 21st century, explains why adaptability should be a goal of technical communication educators, and shows how multimodal pedagogy supports adaptability. Three examples of scalable, multimodal assignments (infographics, research interviews, and software demonstrations) that evidence…

Wide range optofluidically tunable multimode interference fiber laser

International Nuclear Information System (INIS)

Antonio-Lopez, J E; LiKamWa, P; Sanchez-Mondragon, J J; May-Arrioja, D A

2014-01-01

An optofluidically tunable fiber laser based on multimode interference (MMI) effects with a wide tuning range is proposed and demonstrated. The tunable mechanism is based on an MMI fiber filter fabricated using a special fiber known as no-core fiber, which is a multimode fiber (MMF) without cladding. Therefore, when the MMI filter is covered by liquid the optical properties of the no-core fiber are modified, which allow us to tune the peak wavelength response of the MMI filter. Rather than applying the liquid on the entire no-core fiber, we change the liquid level along the no-core fiber, which provides a highly linear tuning response. In addition, by selecting the adequate refractive index of the liquid we can also choose the tuning range. We demonstrate the versatility of the optofluidically tunable MMI filter by wavelength tuning two different gain media, erbium doped fiber and a semiconductor optical amplifier, achieving tuning ranges of 55 and 90 nm respectively. In both cases, we achieve side-mode suppression ratios (SMSR) better than 50 dBm with output power variations of less than 0.76 dBm over the whole tuning range. (paper)

Compressive multi-mode superresolution display

KAUST Repository

Heide, Felix

2014-01-01

Compressive displays are an emerging technology exploring the co-design of new optical device configurations and compressive computation. Previously, research has shown how to improve the dynamic range of displays and facilitate high-quality light field or glasses-free 3D image synthesis. In this paper, we introduce a new multi-mode compressive display architecture that supports switching between 3D and high dynamic range (HDR) modes as well as a new super-resolution mode. The proposed hardware consists of readily-available components and is driven by a novel splitting algorithm that computes the pixel states from a target high-resolution image. In effect, the display pixels present a compressed representation of the target image that is perceived as a single, high resolution image. © 2014 Optical Society of America.

3D hierarchical spatial representation and memory of multimodal sensory data

Science.gov (United States)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine

Multi-modal Intelligent Seizure Acquisition (MISA) system - A new approach towards seizure detection based on full body motion measures

DEFF Research Database (Denmark)

Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid...... hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three...... test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG...

Multimodal biometric method that combines veins, prints, and shape of a finger

Science.gov (United States)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Kim, Jeong Nyeo

2011-01-01

Multimodal biometrics provides high recognition accuracy and population coverage by using various biometric features. A single finger contains finger veins, fingerprints, and finger geometry features; by using multimodal biometrics, information on these multiple features can be simultaneously obtained in a short time and their fusion can outperform the use of a single feature. This paper proposes a new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features. This research is novel in the following four ways. First, the performances of the finger-vein and fingerprint recognition are improved by using a method based on a local derivative pattern. Second, the accuracy of the finger geometry recognition is greatly increased by combining a Fourier descriptor with principal component analysis. Third, a fuzzy score normalization method is introduced; its performance is better than the conventional Z-score normalization method. Fourth, finger-vein, fingerprint, and finger geometry recognitions are combined by using three support vector machines and a weighted SUM rule. Experimental results showed that the equal error rate of the proposed method was 0.254%, which was lower than those of the other methods.

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

Science.gov (United States)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Gestational Trophoblastic Disease: A Multimodality Imaging Approach with Impact on Diagnosis and Management

International Nuclear Information System (INIS)

Dhanda, S.; Ramani, S.; Dhanda, S.; Ramani, S.; Thakur, M.

2014-01-01

Gestational trophoblastic disease is a condition of uncertain etiology, comprised of hydatiform mole (complete and partial), invasive mole, choriocarcinoma, and placental site trophoblastic tumor. It arises from abnormal proliferation of trophoblastic tissue. Early diagnosis of gestational trophoblastic disease and its potential complications is important for timely and successful management of the condition with preservation of fertility. Initial diagnosis is based on a multimodality approach: encompassing clinical features, serial quantitative β-hCG titers, and pelvic ultrasonography. Pelvic magnetic resonance imaging (MRI) is sometimes used as a problem-solving tool to assess the depth of myometrial invasion and extra uterine disease spread in equivocal and complicated cases. Chest radiography, body computed tomography (CT), and brain MRI have been recommended as investigative tools for overall disease staging. Angiography has a role in management of disease complications and metastases. Efficacy of PET (positron emission tomography) and PET/CT in the evaluation of recurrent or metastatic disease has not been adequately investigated yet. This paper discusses the imaging features of gestational trophoblastic disease on various imaging modalities and the role of different imaging techniques in the diagnosis and management of this entity. 1. Introduction Gestational trophoblastic disease (GTD) refers to an abnormal trophoblastic proliferation composed of a broad spectrum of lesions ranging from benign, albeit pre malignant hydatiform mole (complete and partial), through to the aggressive invasive mole, choriocarcinoma

Joint slot allocation and dynamic pricing of container sea–rail multimodal transportation

Directory of Open Access Journals (Sweden)

Di Liu

2015-06-01

Full Text Available The container sea–rail multimodal transport system faces complex challenges with demand uncertainties for joint slot allocation and dynamic pricing. The challenge is formulated as a two-stage optimal model based on revenue management (RM as actual slots sale of multi-node container sea–rail multimodal transport usually includes contract sale to large shippers and free sale to scattered shippers. First stage in the model utilizes an origin-destination control approach, formulated as a stochastic integer programming equation, to settle long-term slot allocation in the contract market and empty container allocation. Second stage in the model is formulated as a stochastic nonlinear programming equation to solve a multiproduct joint dynamic pricing and inventory control problem for price settling and slot allocation in each period of free market. Considering the random nature of demand, the methods of chance constrained programming and robust optimization are utilized to transform stochastic models into deterministic models. A numerical experiment is presented to verify the availability of models and solving methods. Results of considering uncertain/certain demand are compared, which show that the two-stage optimal strategy integrating slot allocation with dynamic pricing considering random demand is revealed to increase the revenue for multimodal transport operators (MTO while concurrently satisfying shippers' demand. Research resulting from this paper will contribute to the theory and practice of container sea–rail multimodal transport revenue management and provide a scientific decision-making tool for MTO.

Mode converter based on an inverse taper for multimode silicon nanophotonic integrated circuits.

Science.gov (United States)

Dai, Daoxin; Mao, Mao

2015-11-02

An inverse taper on silicon is proposed and designed to realize an efficient mode converter available for the connection between multimode silicon nanophotonic integrated circuits and few-mode fibers. The present mode converter has a silicon-on-insulator inverse taper buried in a 3 × 3μm(2) SiN strip waveguide to deal with not only for the fundamental mode but also for the higher-order modes. The designed inverse taper enables the conversion between the six modes (i.e., TE(11), TE(21), TE(31), TE(41), TM(11), TM(12)) in a 1.4 × 0.22μm(2) multimode SOI waveguide and the six modes (like the LP(01), LP(11a), LP(11b) modes in a few-mode fiber) in a 3 × 3μm(2) SiN strip waveguide. The conversion efficiency for any desired mode is higher than 95.6% while any undesired mode excitation ratio is lower than 0.5%. This is helpful to make multimode silicon nanophotonic integrated circuits (e.g., the on-chip mode (de)multiplexers developed well) available to work together with few-mode fibers in the future.

Focusing and imaging with increased numerical apertures through multimode fibers with micro-fabricated optics.

Science.gov (United States)

Bianchi, S; Rajamanickam, V P; Ferrara, L; Di Fabrizio, E; Liberale, C; Di Leonardo, R

2013-12-01

The use of individual multimode optical fibers in endoscopy applications has the potential to provide highly miniaturized and noninvasive probes for microscopy and optical micromanipulation. A few different strategies have been proposed recently, but they all suffer from intrinsically low resolution related to the low numerical aperture of multimode fibers. Here, we show that two-photon polymerization allows for direct fabrication of micro-optics components on the fiber end, resulting in an increase of the numerical aperture to a value that is close to 1. Coupling light into the fiber through a spatial light modulator, we were able to optically scan a submicrometer spot (300 nm FWHM) over an extended region, facing the opposite fiber end. Fluorescence imaging with improved resolution is also demonstrated.

Utilization of multimode Love wave dispersion curve inversion for geotechnical site investigation

International Nuclear Information System (INIS)

Hamimu, La; Nawawi, Mohd; Safani, Jamhir

2011-01-01

Inversion codes based on a modified genetic algorithm (GA) have been developed to invert multimode Love wave dispersion curves. The multimode Love wave dispersion curves were synthesized from the profile representing shear-wave velocity reversal using a full SH (shear horizontal) waveform. In this study, we used a frequency–slowness transform to extract the dispersion curve from the full SH waveform. Dispersion curves overlain in dispersion images were picked manually. These curves were then inverted using the modified GA. To assess the accuracy of the inversion results, differences between the true and inverted shear-wave velocity profile were quantified in terms of shear-wave velocity and thickness errors, E S and E H . Our numerical modeling showed that the inversion of multimode dispersion curves can significantly provide the better assessment of a shear-wave velocity structure, especially with a velocity reversal profile at typical geotechnical site investigations. This approach has been applied on field data acquired at a site in Niigata prefecture, Japan. In these field data, our inversion results show good agreement between the calculated and experimental dispersion curves and accurately detect low velocity layer targets

A Remaking Pedagogy: Adaptation and Archetypes in the Child's Multimodal Reading and Writing

Science.gov (United States)

Berger, Richard; Zezulkova, Marketa

2018-01-01

This paper proposes combining theories about, and practices of, using archetypes and adaptation in education for the purposes of multimodal literacy learning. Within such contexts, children of primary school age act as readers, performers and researchers, exploring and analysing existing adaptations of archetypal stories and images across time,…

A combined salt-hard templating approach for synthesis of multi-modal porous carbons used for probing the simultaneous effects of porosity and electrode engineering on EDLC performance

KAUST Repository

Bhandari, Nidhi

2015-06-01

A new approach, based on a combination of salt and hard templating for producing multi-modal porous carbons is demonstrated. The hard template, silica nanoparticles, generate mesopores (∼22 nm), and in some cases borderline-macropores (∼64 nm), resulting in high pore volume (∼3.9 cm3/g) while the salt template, zinc chloride, generates borderline-mesopores (∼2 nm), thus imparting high surface area (∼2100 m2/g). The versatility of the proposed synthesis technique is demonstrated using: (i) dual salt templates with hard template resulting in magnetic, nanostructured-clay embedded (∼27% clay content), high surface area (∼1527 m2/g) bimodal carbons (∼2 and 70 nm pores), (ii) multiple hard templates with salt template resulting in tri-modal carbons (∼2, 12 and 28 nm pores), (iii) low temperature (450 °C) synthesis of bimodal carbons afforded by the presence of hygroscopic salt template, (iv) easy coupling with physical activation approaches. A selected set of thus synthesized carbons were used to evaluate, for the first time, the simultaneous effects of carbon porosity and pressure applied during electrode fabrication on EDLC performance. Electrode pressing was found to be more favorable for carbons containing hard-templated mesopores (∼87% capacitance retention at current density of 40 A/g) as compared to those without (∼54% capacitance retention). © 2015 Elsevier Ltd. All rights reserved.

MISTRAL: A game-theoretical model to allocate security measures in a multi-modal chemical transportation network with adaptive adversaries

International Nuclear Information System (INIS)

Talarico, Luca; Reniers, Genserik; Sörensen, Kenneth; Springael, Johan

2015-01-01

In this paper we present a multi-modal security-transportation model to allocate security resources within a chemical supply chain which is characterized by the use of different transport modes, each having their own security features. We consider security-related risks so as to take measures against terrorist acts which could target critical transportation systems. The idea of addressing security-related issues, by supporting decisions for preventing or mitigating intentional acts on transportation infrastructure, has gained attention in academic research only recently. The decision model presented in this paper is based on game theory and it can be employed to organize intelligence capabilities aimed at securing chemical supply chains. It enables detection and warning against impending attacks on transportation infrastructures and the subsequent adoption of security countermeasures. This is of extreme importance for preventing terrorist attacks and for avoiding (possibly huge) human and economic losses. In our work we also provide data sources and numerical simulations by applying the proposed model to a illustrative multi-modal chemical supply chain. - Highlights: • A model to increase the security in a multimodal chemical supply chain is proposed. • The model considers adaptive opponents having multi-attribute utility functions. • The model is based on game theory using an attacker–defender schema. • The model provides recommendations about where to allocate security measures. • Numerical simulations on a sample multimodal chemical supply chain are shown

Impulse radio ultra wide-band over multi-mode fiber for in-home signal distribution

DEFF Research Database (Denmark)

Caballero Jambrina, Antonio; Rodes, Roberto; Jensen, Jesper Bevensee

2009-01-01

We propose and experimentally demonstrate a high speed impulse radio ultra wide-band (IR-UWB) wireless link for in-home network signal distribution. The IR-UWB pulse is distributed over a multimode fiber to the transmitter antenna. Wireless transmitted bit-rates of 1 Gbps at 2 m and 2 Gbps at 1.5 m...

The impact of fMRI on multimodal navigation in surgery of cerebral lesions: four years clinical experience

International Nuclear Information System (INIS)

Wurm, Gabriele; Schnizer, Mathilde; Fellner, Claudia

2008-01-01

Neuronavigation with display of intraoperative structures, instrument locations, orientation and relationships to nearby structures can increase anatomic precision while enhancing the surgeon's confidence and his/her perception of safety. Combination of neuronavigation with functional imaging provides multimodal guidance for surgery of cerebral lesions. We evaluated the impact of functional MRI (fMRI) on surgical decision making and outcome. A neuronavigational device (StealthStation (tm), Medtronic Inc.) was used as platform to merge fMRI data with anatomic images, and to implement intraoperative multimodal guidance. In a 52-month period, where 977 surgical procedures were performed with the aid of neuronavigation, 88 patients underwent image-guided procedures using multimodal guidance. Patient, surgical and outcome data of this series was prospectively collected. Evaluation of 88 procedures on cerebral lesions in complex regions where fMRI data were integrated using the navigation system demonstrated that the additional information was presented in a user-friendly way. Computer assisted fMRI integration was found to be especially helpful in planning the best approach, in assessing alternative approaches, and in defining the extent of the surgical exposure. Furthermore, the surgeons found it more effective to interpret fMRI information when shown in a navigation system as compared to the traditional display on a light board or monitor. Multimodal navigation enhanced by fMRI was judged useful for optimization of surgery of cerebral lesions, especially in and around eloquent regions by experienced neurosurgeons. (orig.)

Body-insensitive Multi-Mode MIMO Terminal Antenna of Double-Ring Structure

DEFF Research Database (Denmark)

Zhao, Kun; Zhang, Shuai; Ishimiya, Katsunori

2015-01-01

of mobile terminals. With the multimode excitation, the MIMO cellular antenna can operate at 830-900 MHz, 1700-2200 MHz, and 2400-2700 MHz, for 2G, 3G, and LTE bands, respectively. The MIMO Wi-Fi antenna can cover two Wi-Fi bands from 2.4 to 2.5 GHz and from 5.2 to 5.8 GHz. The effect of a user's body......In this paper, we propose a novel multimode multi-input multi-output (MIMO) antenna system composed of a dual-element MIMO cellular antenna and dual-element MIMO Wi-Fi antenna for mobile terminal applications. The antenna system has a double-ring structure and can be integrated with the metal frame...... on the MIMO cellular antenna is investigated on CTIA standard phantoms and a real user. Since our antenna mainly operates in the loop mode, it has a much lower efficiency loss than conventional mobile antennas in both talking and data modes. Our theoretical analysis and experiments have shown that our design...

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

Science.gov (United States)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Multimodal therapeutic approach of vaginismus: an innovative approach through trigger point infiltration and pulsed radiofrequency of the pudendal nerve

Directory of Open Access Journals (Sweden)

Joana Chaves Gonçalves Rodrigues de Carvalho

Full Text Available Abstract Vaginismus is a poorly understood disorder, characterized by an involuntary muscular spasm of the pelvic floor muscles and outer third of the vagina during intercourse attempt, which results in aversion to penetration. It is reported to affect 1-7% of women worldwide. With this report the authors aim to describe the case of a young patient with vaginismus in whom techniques usually from the chronic pain domain were used as part of her multimodal therapeutic regimen.

MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck.

Directory of Open Access Journals (Sweden)

Maria Ida Iacono

Full Text Available Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI modalities, the parameters of which were tailored to enhance the signals of specific tissues: i structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii magnetic resonance angiography (MRA data to image the vasculature, and iii diffusion tensor imaging (DTI to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.

The challenge of simple graphics for multimodal studies

DEFF Research Database (Denmark)

Johannessen, Christian Mosbæk

2018-01-01

This article suggests that a Multimodal Social Semiotics (MSS) approach to graphics is severely challenged by structurally very simple texts. Methodologically, MSS favours the level at which elements from discrete modes are integrated grammatically into texts. Because the tradition has this focus......, the analytical description of the expression plane of many modes is underdeveloped. In the case of graphics, we have no descriptive or explanatory readiness for graphic form. The article aims to remedy this problem by combining (i) a small inventory of formal dichotomies for graphic shape features at a general...

Understanding and treating vaginismus: a multimodal approach.

Science.gov (United States)

Pacik, Peter T

2014-12-01

This clinical opinion was written to bring attention to the understanding and treatment of vaginismus, a condition that is often under diagnosed and therefore inadequately treated, yet affects millions of women worldwide. Despite its description more than a century ago, vaginismus is rarely taught in medical school, residency training, and medical meetings. The DSM 5 classification stresses that vaginismus is a penetration disorder in that any form of vaginal penetration such as tampons, finger, vaginal dilators, gynecological examinations, and intercourse is often painful or impossible. Compared with other sexual pain disorders such as vulvodynia and vestibulodynia, the treatment of vaginismus has the potential for a high rate of success. Stratifying the severity of vaginismus allows the clinician to choose among numerous treatment options and to better understand what the patient is experiencing. Vaginismus is both a physical and an emotional disorder. In the more severe cases of vaginismus women (and men) complain that attempted intercourse is like "hitting a wall" suggestive of spasm at the level of the introitus. The emotional fallout resulting from this needs to be addressed in any form of treatment applied. This article is based on lessons learned in the treatment of more than 250 patients and evaluation of more than 400 inquiries, and was written to make vaginismus more widely understood, to aid in the differential diagnosis of sexual pain, suggest a variety of effective treatments, and explain how Botox can be used as part of a multimodal treatment program to treat vaginismus. With greater awareness among clinicians it is hoped that medical schools, residency programs, and medical meetings will begin teaching the understanding and treatment of vaginismus.

Multimodal EEG Recordings, Psychometrics and Behavioural Analysis.

Science.gov (United States)

Boeijinga, Peter H

2015-01-01

High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated. © 2016 S. Karger AG, Basel.

Time-bin entangled photon pairs from spontaneous parametric down-conversion pumped by a cw multi-mode diode laser.

Science.gov (United States)

Kwon, Osung; Park, Kwang-Kyoon; Ra, Young-Sik; Kim, Yong-Su; Kim, Yoon-Ho

2013-10-21

Generation of time-bin entangled photon pairs requires the use of the Franson interferometer which consists of two spatially separated unbalanced Mach-Zehnder interferometers through which the signal and idler photons from spontaneous parametric down-conversion (SPDC) are made to transmit individually. There have been two SPDC pumping regimes where the scheme works: the narrowband regime and the double-pulse regime. In the narrowband regime, the SPDC process is pumped by a narrowband cw laser with the coherence length much longer than the path length difference of the Franson interferometer. In the double-pulse regime, the longitudinal separation between the pulse pair is made equal to the path length difference of the Franson interferometer. In this paper, we propose another regime by which the generation of time-bin entanglement is possible and demonstrate the scheme experimentally. In our scheme, differently from the previous approaches, the SPDC process is pumped by a cw multi-mode (i.e., short coherence length) laser and makes use of the coherence revival property of such a laser. The high-visibility two-photon Franson interference demonstrates clearly that high-quality time-bin entanglement source can be developed using inexpensive cw multi-mode diode lasers for various quantum communication applications.

Multimode optical fibers: steady state mode exciter.

Science.gov (United States)

Ikeda, M; Sugimura, A; Ikegami, T

1976-09-01

The steady state mode power distribution of the multimode graded index fiber was measured. A simple and effective steady state mode exciter was fabricated by an etching technique. Its insertion loss was 0.5 dB for an injection laser. Deviation in transmission characteristics of multimode graded index fibers can be avoided by using the steady state mode exciter.

In vivo mapping of vascular inflammation using multimodal imaging.

Directory of Open Access Journals (Sweden)

Benjamin R Jarrett

2010-10-01

Full Text Available Plaque vulnerability to rupture has emerged as a critical correlate to risk of adverse coronary events but there is as yet no clinical method to assess plaque stability in vivo. In the search to identify biomarkers of vulnerable plaques an association has been found between macrophages and plaque stability--the density and pattern of macrophage localization in lesions is indicative of probability to rupture. In very unstable plaques, macrophages are found in high densities and concentrated in the plaque shoulders. Therefore, the ability to map macrophages in plaques could allow noninvasive assessment of plaque stability. We use a multimodality imaging approach to noninvasively map the distribution of macrophages in vivo. The use of multiple modalities allows us to combine the complementary strengths of each modality to better visualize features of interest. Our combined use of Positron Emission Tomography and Magnetic Resonance Imaging (PET/MRI allows high sensitivity PET screening to identify putative lesions in a whole body view, and high resolution MRI for detailed mapping of biomarker expression in the lesions.Macromolecular and nanoparticle contrast agents targeted to macrophages were developed and tested in three different mouse and rat models of atherosclerosis in which inflamed vascular plaques form spontaneously and/or are induced by injury. For multimodal detection, the probes were designed to contain gadolinium (T1 MRI or iron oxide (T2 MRI, and Cu-64 (PET. PET imaging was utilized to identify regions of macrophage accumulation; these regions were further probed by MRI to visualize macrophage distribution at high resolution. In both PET and MR images the probes enhanced contrast at sites of vascular inflammation, but not in normal vessel walls. MRI was able to identify discrete sites of inflammation that were blurred together at the low resolution of PET. Macrophage content in the lesions was confirmed by histology.The multimodal

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

Energy Technology Data Exchange (ETDEWEB)

Shekhar, R. [Children’s National Health System (United States)

2016-06-15

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

International Nuclear Information System (INIS)

Shekhar, R.

2016-01-01

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504

Multimodal genres in textbooks: are students being schooled for visual literacy?

Directory of Open Access Journals (Sweden)

Cláudia Graziano Paes de Barros

2012-11-01

Full Text Available In this paper, we discuss some issues involved in teaching and learning reading, especially schooling in visual literacy. We seek to observe the work developed with genres that combine verbal and visual languages, found in the reading activities of two high school textbook series for Portuguese language teaching. Our goal was to understand to what extent these activities contribute towards the development of reading skills needed to deal with the specificities of these genres. Therefore, we used the enunciative and discursive assumptions of the socio-historical approach of Bakhtin Circle, as well as the Social Semiotics perspective to understand multimodality. Data analysis revealed that the incidence of multimodal genres studied in the two textbook series is hardly representative. The didactic treatment these genres receive in reading activities does not favor the mobilization of specific reading skills and contributes little to students‟ visual literacy schooling.

Multimodal network design for sustainable household plastic recycling

NARCIS (Netherlands)

Bing Xiaoyun, Xiaoyun; Groot, J.J.; Bloemhof, J.M.; Vorst, van der J.G.A.J.

2013-01-01

Purpose – This research studies a plastic recycling system from a reverse logistics angle and investigates the potential benefits of a multimodality strategy to the network design of plastic recycling. This research aims to quantify the impact of multimodality on the network, to provide decision

Multimodal warnings to enhance risk communication and safety

NARCIS (Netherlands)

Haas, E.C.; Erp, J.B.F. van

2014-01-01

Multimodal warnings incorporate audio and/or skin-based (tactile) cues to supplement or replace visual cues in environments where the user’s visual perception is busy, impaired, or nonexistent. This paper describes characteristics of audio, tactile, and multimodal warning displays and their role in

Focusing and imaging with increased numerical apertures through multimode fibers with micro-fabricated optics

KAUST Repository

Bianchi, Silvio; Rajamanickam, V.; Ferrara, Lorenzo; Di Fabrizio, Enzo M.; Liberale, Carlo; Di Leonardo, Roberto

2013-01-01

The use of individual multimode optical fibers in endoscopy applications has the potential to provide highly miniaturized and noninvasive probes for microscopy and optical micromanipulation. A few different strategies have been proposed recently, but they all suffer from intrinsically low resolution related to the low numerical aperture of multimode fibers. Here, we show that two-photon polymerization allows for direct fabrication of micro-optics components on the fiber end, resulting in an increase of the numerical aperture to a value that is close to 1. Coupling light into the fiber through a spatial light modulator, we were able to optically scan a submicrometer spot (300 nm FWHM) over an extended region, facing the opposite fiber end. Fluorescence imaging with improved resolution is also demonstrated. © 2013 Optical Society of America.

A Multimode Equivalent Network Approach for the Analysis of a 'Realistic' Finite Array of Open Ended Waveguides

NARCIS (Netherlands)

Neto, A.; Bolt, R.; Gerini, G.; Schmitt, D.

2003-01-01

In this contribution we present a theoretical model for the analysis of finite arrays of open-ended waveguides mounted on finite mounting platforms or having radome coverages. This model is based on a Multimode Equivalent Network (MEN) [1] representation of the radiating waveguides complete with

Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

Directory of Open Access Journals (Sweden)

Andre Santos Ribeiro

2015-07-01

Full Text Available Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity.Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI and positron emission tomography (PET. It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also.Results. It was observed both a high inter

Differential-drive mobile robot control using a cloud of particles approach

Directory of Open Access Journals (Sweden)

Walter Fetter Lages

2016-12-01

Full Text Available Common control systems for mobile robots include the use of some deterministic control law coupled with some pose estimation method, such as the extended Kalman filter, by considering the certainty equivalence principle. Recent approaches consider the use of partially observable Markov decision process strategies together with Bayesian estimators. These methods are well suited to handle the uncertainty in pose estimation but demand significant processing power. In order to reduce the required processing power and still allow for multimodal or non-Gaussian uncertain distributions, we propose a scheme based on a particle filter and a corresponding cloud of control signals. The approach avoids the use of the certainty equivalence principle by postponing the decision on the optimal estimate to the control stage. As the mapping between the pose space and the control action space is nonlinear and the best estimation of robot pose is uncertain, postponing the decision to the control space makes it possible to select a better control action in the presence of multimodal and non-Gaussian uncertainty models. Simulation results are presented.

A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

Science.gov (United States)

Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C.; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J.

2017-01-01

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

Science.gov (United States)

Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

2018-01-01

The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Proposal of Innovative Approaches of Relationship Marketing in Business

Directory of Open Access Journals (Sweden)

Viliam Lendel

2015-03-01

Full Text Available The aim of this paper is to propose innovative approaches to relationship marketing that affect the process of building relationships with customers, based on a detailed analysis of the literary sources and the research. This proposal is supported by the information technology e-CRM and social CRM. The paper contains a detailed description of the procedure for successfully implementing innovative approaches to relationship marketing in business. This should serve mainly to marketing managers as a valuable tool in their use of innovative approaches to relationship marketing, especially in the process of obtaining innovative ideas from customers, in order to identify their needs and requirements. Furthermore, the paper contains the main results of our research aimed at identifying the extent of utilization of innovative approaches to relationship marketing in Slovak businesses. A total of 207 respondents were involved in the research (medium and large businesses and following methods were used: comparative method of qualitative evaluation method, the method of structured and structured interview method, observation, document analysis method (method of content analysis and questionnaire method.

Multi-modal locomotion: from animal to application

International Nuclear Information System (INIS)

Lock, R J; Burgess, S C; Vaidyanathan, R

2014-01-01

The majority of robotic vehicles that can be found today are bound to operations within a single media (i.e. land, air or water). This is very rarely the case when considering locomotive capabilities in natural systems. Utility for small robots often reflects the exact same problem domain as small animals, hence providing numerous avenues for biological inspiration. This paper begins to investigate the various modes of locomotion adopted by different genus groups in multiple media as an initial attempt to determine the compromise in ability adopted by the animals when achieving multi-modal locomotion. A review of current biologically inspired multi-modal robots is also presented. The primary aim of this research is to lay the foundation for a generation of vehicles capable of multi-modal locomotion, allowing ambulatory abilities in more than one media, surpassing current capabilities. By identifying and understanding when natural systems use specific locomotion mechanisms, when they opt for disparate mechanisms for each mode of locomotion rather than using a synergized singular mechanism, and how this affects their capability in each medium, similar combinations can be used as inspiration for future multi-modal biologically inspired robotic platforms. (topical review)

[Multimodal therapeutic approach of vaginismus: an innovative approach through trigger point infiltration and pulsed radiofrequency of the pudendal nerve].

Science.gov (United States)

Carvalho, Joana Chaves Gonçalves Rodrigues de; Agualusa, Luís Miguel; Moreira, Luísa Manuela Ribeiro; Costa, Joana Catarina Monteiro da

Vaginismus is a poorly understood disorder, characterized by an involuntary muscular spasm of the pelvic floor muscles and outer third of the vagina during intercourse attempt, which results in aversion to penetration. It is reported to affect 1-7% of women worldwide. With this report the authors aim to describe the case of a young patient with vaginismus in whom techniques usually from the chronic pain domain were used as part of her multimodal therapeutic regimen. Copyright © 2015 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

Multimodal Scaffolding in the Secondary English Classroom Curriculum

Science.gov (United States)

Boche, Benjamin; Henning, Megan

2015-01-01

This article examines the topic of multimodal scaffolding in the secondary English classroom curriculum through the viewpoint of one teacher's experiences. With technology becoming more commonplace and readily available in the English classroom, we must pinpoint specific and tangible ways to help teachers use and teach multimodalities in their…

Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation

Directory of Open Access Journals (Sweden)

Timo Korthals

2018-03-01

Full Text Available Today, agricultural vehicles are available that can automatically perform tasks such as weed detection and spraying, mowing, and sowing while being steered automatically. However, for such systems to be fully autonomous and self-driven, not only their specific agricultural tasks must be automated. An accurate and robust perception system automatically detecting and avoiding all obstacles must also be realized to ensure safety of humans, animals, and other surroundings. In this paper, we present a multi-modal obstacle and environment detection and recognition approach for process evaluation in agricultural fields. The proposed pipeline detects and maps static and dynamic obstacles globally, while providing process-relevant information along the traversed trajectory. Detection algorithms are introduced for a variety of sensor technologies, including range sensors (lidar and radar and cameras (stereo and thermal. Detection information is mapped globally into semantical occupancy grid maps and fused across all sensors with late fusion, resulting in accurate traversability assessment and semantical mapping of process-relevant categories (e.g., crop, ground, and obstacles. Finally, a decoding step uses a Hidden Markov model to extract relevant process-specific parameters along the trajectory of the vehicle, thus informing a potential control system of unexpected structures in the planned path. The method is evaluated on a public dataset for multi-modal obstacle detection in agricultural fields. Results show that a combination of multiple sensor modalities increases detection performance and that different fusion strategies must be applied between algorithms detecting similar and dissimilar classes.

MULTIMODAL BIOMETRIC AUTHENTICATION USING PARTICLE SWARM OPTIMIZATION ALGORITHM WITH FINGERPRINT AND IRIS

Directory of Open Access Journals (Sweden)

A. Muthukumar

2012-02-01

Full Text Available In general, the identification and verification are done by passwords, pin number, etc., which is easily cracked by others. In order to overcome this issue biometrics is a unique tool for authenticate an individual person. Nevertheless, unimodal biometric is suffered due to noise, intra class variations, spoof attacks, non-universality and some other attacks. In order to avoid these attacks, the multimodal biometrics i.e. combining of more modalities is adapted. In a biometric authentication system, the acceptance or rejection of an entity is dependent on the similarity score falling above or below the threshold. Hence this paper has focused on the security of the biometric system, because compromised biometric templates cannot be revoked or reissued and also this paper has proposed a multimodal system based on an evolutionary algorithm, Particle Swarm Optimization that adapts for varying security environments. With these two concerns, this paper had developed a design incorporating adaptability, authenticity and security.

Fourier domain asymmetric cryptosystem for privacy protected multimodal biometric security

Science.gov (United States)

Choudhury, Debesh

2016-04-01

We propose a Fourier domain asymmetric cryptosystem for multimodal biometric security. One modality of biometrics (such as face) is used as the plaintext, which is encrypted by another modality of biometrics (such as fingerprint). A private key is synthesized from the encrypted biometric signature by complex spatial Fourier processing. The encrypted biometric signature is further encrypted by other biometric modalities, and the corresponding private keys are synthesized. The resulting biometric signature is privacy protected since the encryption keys are provided by the human, and hence those are private keys. Moreover, the decryption keys are synthesized using those private encryption keys. The encrypted signatures are decrypted using the synthesized private keys and inverse complex spatial Fourier processing. Computer simulations demonstrate the feasibility of the technique proposed.

Multimodal Image Alignment via Linear Mapping between Feature Modalities.

Science.gov (United States)

Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

2017-01-01

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

Multimodal image registration based on binary gradient angle descriptor.

Science.gov (United States)

Jiang, Dongsheng; Shi, Yonghong; Yao, Demin; Fan, Yifeng; Wang, Manning; Song, Zhijian

2017-12-01

Multimodal image registration plays an important role in image-guided interventions/therapy and atlas building, and it is still a challenging task due to the complex intensity variations in different modalities. The paper addresses the problem and proposes a simple, compact, fast and generally applicable modality-independent binary gradient angle descriptor (BGA) based on the rationale of gradient orientation alignment. The BGA can be easily calculated at each voxel by coding the quadrant in which a local gradient vector falls, and it has an extremely low computational complexity, requiring only three convolutions, two multiplication operations and two comparison operations. Meanwhile, the binarized encoding of the gradient orientation makes the BGA more resistant to image degradations compared with conventional gradient orientation methods. The BGA can extract similar feature descriptors for different modalities and enable the use of simple similarity measures, which makes it applicable within a wide range of optimization frameworks. The results for pairwise multimodal and monomodal registrations between various images (T1, T2, PD, T1c, Flair) consistently show that the BGA significantly outperforms localized mutual information. The experimental results also confirm that the BGA can be a reliable alternative to the sum of absolute difference in monomodal image registration. The BGA can also achieve an accuracy of [Formula: see text], similar to that of the SSC, for the deformable registration of inhale and exhale CT scans. Specifically, for the highly challenging deformable registration of preoperative MRI and 3D intraoperative ultrasound images, the BGA achieves a similar registration accuracy of [Formula: see text] compared with state-of-the-art approaches, with a computation time of 18.3 s per case. The BGA improves the registration performance in terms of both accuracy and time efficiency. With further acceleration, the framework has the potential for

Pellet bed reactor for multi-modal space power

International Nuclear Information System (INIS)

Buden, D.; Williams, K.; Mast, P.; Mims, J.

1987-01-01

A review of forthcoming space power needs for both civil and military missions indicates that power requirements will be in the tens of megawatts. The electrical power requirements are envisioned to be twofold: long-duration lower power levels will be needed for station keeping, communications, and/or surveillance; short-duration higher power levels will be required for pulsed power devices. These power characteristics led to the proposal of a multi-modal space power reactor using a pellet bed design. Characteristics desired for such a multimegawatt reactor power source are standby, alert, and pulsed power modes; high-thermal output heat source (approximately 1000 MWt peak power); long lifetime station keeping power (10 to 30 years); high temperature output (1500 K to 1800 K); rapid-burst power transition; high reliability (above 95 percent); and stringent safety standards compliance. The proposed pellet bed reactor is designed to satisfy these characteristics

Detection of relationships among multi-modal brain imaging meta-features via information flow.

Science.gov (United States)

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

Robustness of multimodal processes itineraries

DEFF Research Database (Denmark)

Bocewicz, G.; Banaszak, Z.; Nielsen, Izabela Ewa

2013-01-01

itineraries for assumed (O-D) trip. Since itinerary planning problem, constitutes a common routing and scheduling decision faced by travelers, hence the main question regards of itinerary replanning and particularly a method aimed at prototyping of mode sequences and paths selections. The declarative model......This paper concerns multimodal transport systems (MTS) represented by a supernetworks in which several unimodal networks are connected by transfer links and focuses on the scheduling problems encountered in these systems. Assuming unimodal networks are modeled as cyclic lines, i.e. the routes...... of multimodal processes driven itinerary planning problem is our main contribution. Illustrative examples providing alternative itineraries in some cases of MTS malfunction are presented....

Multimode model for projective photon-counting measurements

International Nuclear Information System (INIS)

Tualle-Brouri, Rosa; Ourjoumtsev, Alexei; Dantan, Aurelien; Grangier, Philippe; Wubs, Martijn; Soerensen, Anders S.

2009-01-01

We present a general model to account for the multimode nature of the quantum electromagnetic field in projective photon-counting measurements. We focus on photon-subtraction experiments, where non-Gaussian states are produced conditionally. These are useful states for continuous-variable quantum-information processing. We present a general method called mode reduction that reduces the multimode model to an effective two-mode problem. We apply this method to a multimode model describing broadband parametric down-conversion, thereby improving the analysis of existing experimental results. The main improvement is that spatial and frequency filters before the photon detector are taken into account explicitly. We find excellent agreement with previously published experimental results, using fewer free parameters than before, and discuss the implications of our analysis for the optimized production of states with negative Wigner functions.

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

Science.gov (United States)

Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

2016-01-01

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

An efficient and fast detection algorithm for multimode FBG sensing

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for fast and accurate peak detection. The algorithm uses threshold determined detection window and Center of gravity algorithm with bias compensation. We analyze the wavelength fit resolution of the DGA for different values of signal to noise ratio...... and different typical peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with higher stability and accuracy compared to conventional algorithms. This makes it very attractive for future implementation in sensing systems especially based on multimode fiber Bragg...

Experiencia de enseñanza multimodal en una clase de idiomas [Experience of multimodal teaching in a language classroom

Directory of Open Access Journals (Sweden)

María Martínez Lirola

2013-12-01

Full Text Available Resumen: Nuestra sociedad es cada vez más tecnológica y multimodal por lo que es necesario que la enseñanza se adapte a los nuevos tiempos. Este artículo analiza el modo en que la asignatura Lengua Inglesa IV de la Licenciatura en Filología Inglesa en la Universidad de Alicante combina el desarrollo de las cinco destrezas (escucha, habla, lectura, escritura e interacción evaluadas por medio de un portafolio con la multimodalidad en las prácticas docentes y en cada una de las actividades que componen el portafolio. Los resultados de una encuesta preparada al final del curso académico 2011-2012 ponen de manifiesto las competencias principales que el alumnado universitario desarrolla gracias a la docencia multimodal y la importancia de las tutorías en este tipo de enseñanza. Abstract: Our society becomes more technological and multimodal and, consequently, teaching has to be adapted to the new time. This article analyses the way in which the subject English Language IV of the degree English Studies at the University of Alicante combines the development of the five skills (listening, speaking, reading, writing and interacting evaluated through a portfolio with multimodality in the teaching practices and in each of the activities that are part of the portfolio. The results of a survey prepared at the end of the academic year 2011-2012 point out the main competences that university students develop thanks to multimodal teaching and the importance of tutorials in this kind of teaching.

BILINGUAL MULTIMODAL SYSTEM FOR TEXT-TO-AUDIOVISUAL SPEECH AND SIGN LANGUAGE SYNTHESIS

Directory of Open Access Journals (Sweden)

A. A. Karpov

2014-09-01

Full Text Available We present a conceptual model, architecture and software of a multimodal system for audio-visual speech and sign language synthesis by the input text. The main components of the developed multimodal synthesis system (signing avatar are: automatic text processor for input text analysis; simulation 3D model of human's head; computer text-to-speech synthesizer; a system for audio-visual speech synthesis; simulation 3D model of human’s hands and upper body; multimodal user interface integrating all the components for generation of audio, visual and signed speech. The proposed system performs automatic translation of input textual information into speech (audio information and gestures (video information, information fusion and its output in the form of multimedia information. A user can input any grammatically correct text in Russian or Czech languages to the system; it is analyzed by the text processor to detect sentences, words and characters. Then this textual information is converted into symbols of the sign language notation. We apply international «Hamburg Notation System» - HamNoSys, which describes the main differential features of each manual sign: hand shape, hand orientation, place and type of movement. On their basis the 3D signing avatar displays the elements of the sign language. The virtual 3D model of human’s head and upper body has been created using VRML virtual reality modeling language, and it is controlled by the software based on OpenGL graphical library. The developed multimodal synthesis system is a universal one since it is oriented for both regular users and disabled people (in particular, for the hard-of-hearing and visually impaired, and it serves for multimedia output (by audio and visual modalities of input textual information.

Multimodality

DEFF Research Database (Denmark)

Buhl, Mie

In this paper, I address an ongoing discussion in Danish E-learning research about how to take advantage of the fact that digital media facilitate other communication forms than text, so-called ‘multimodal’ communication, which should not be confused with the term ‘multimedia’. While multimedia...... and learning situations. The choices they make involve E-learning resources like videos, social platforms and mobile devices, not just as digital artefacts we interact with, but the entire practice of using digital media. In a life-long learning perspective, multimodality is potentially very useful...

Multimodal freight investment criteria.

Science.gov (United States)

2010-07-01

Literature was reviewed on multi-modal investment criteria for freight projects, examining measures and techniques for quantifying project benefits and costs, as well as ways to describe the economic importance of freight transportation. : A limited ...

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA.

Science.gov (United States)

Mitrea, Diana M; Cika, Jaclyn A; Guy, Clifford S; Ban, David; Banerjee, Priya R; Stanley, Christopher B; Nourse, Amanda; Deniz, Ashok A; Kriwacki, Richard W

2016-02-02

The nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identify multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus.

Multimodal profusion in the literacies of the Massive Open Online Course

Directory of Open Access Journals (Sweden)

Jeremy Knox

2014-01-01

Full Text Available This paper takes a view of digital literacy, which moves beyond a focus on technical methods and skills in an attempt to maintain a broader approach that encompasses a critical view of the learning subject. In doing this, we consider socio-materialism and its relation to aspects of literacy theory. We anchor the discussion in a consideration of the ‘E-learning and Digital Cultures’ Coursera MOOC, which provided a tangible setting for theorising some of the practices of digital literacy differently. The profusion of multimodal artefacts produced in response to this course constituted a complex series of socio-material entanglements, in which human beings and technologies each played a constituent part. Two specific digital artefacts are analysed according to these terms. We conclude that socio-material multimodality constitutes a different way of thinking about digital literacy: not as representational practices, but rather as multifaceted and relational enactments of knowledge, specific to particular contexts and moments.

Multimodal follow-up questions to multimodal answers in a QA system

NARCIS (Netherlands)

van Schooten, B.W.; op den Akker, Hendrikus J.A.

2007-01-01

We are developing a dialogue manager (DM) for a multimodal interactive Question Answering (QA) system. Our QA system presents answers using text and pictures, and the user may pose follow-up questions using text or speech, while indicating screen elements with the mouse. We developed a corpus of

Coronary plaque morphology on multi-modality imagining and periprocedural myocardial infarction after percutaneous coronary intervention

Directory of Open Access Journals (Sweden)

Akira Sato

2016-06-01

Full Text Available Percutaneous coronary intervention (PCI may be complicated by periprocedural myocardial infarction (PMI as manifested by elevated cardiac biomarkers such as creatine kinase (CK-MB or troponin T. The occurrence of PMI has been shown to be associated with worse short- and long-term clinical outcome. However, recent studies suggest that PMI defined by biomarker levels alone is a marker of atherosclerosis burden and procedural complexity but in most cases does not have independent prognostic significance. Diagnostic multi-modality imaging such as intravascular ultrasound, optical coherence tomography, coronary angioscopy, near-infrared spectroscopy, multidetector computed tomography, and magnetic resonance imaging can be used to closely investigate the atherosclerotic lesion in order to detect morphological markers of unstable and vulnerable plaques in the patients undergoing PCI. With the improvement of technical aspects of multimodality coronary imaging, clinical practice and research are increasingly shifting toward defining the clinical implication of plaque morphology and patients outcomes. There were numerous published data regarding the relationship between pre-PCI lesion subsets on multi-modality imaging and post-PCI biomarker levels. In this review, we discuss the relationship between coronary plaque morphology estimated by invasive or noninvasive coronary imaging and the occurrence of PMI. Furthermore, this review underlies that the value of the multimodality coronary imaging approach will become the gold standard for invasive or noninvasive prediction of PMI in clinical practice.

Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection.

Science.gov (United States)

Sarikaya, Duygu; Corso, Jason J; Guru, Khurshid A

2017-07-01

Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos. To the best of our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos. Our architecture applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues. Our results with an average precision of 91% and a mean computation time of 0.1 s per test frame detection indicate that our study is superior to conventionally used methods for medical imaging while also emphasizing the benefits of using RPN for precision and efficiency. We also introduce a new data set, ATLAS Dione, for RAS video understanding. Our data set provides video data of ten surgeons from Roswell Park Cancer Institute, Buffalo, NY, USA, performing six different surgical tasks on the daVinci Surgical System (dVSS) with annotations of robotic tools per frame.

Randomized Controlled Trial: Multimodal Anxiety and Social Skill Intervention for Adolescents with Autism Spectrum Disorder

Science.gov (United States)

White, Susan W.; Ollendick, Thomas; Albano, Anne Marie; Oswald, Donald; Johnson, Cynthia; Southam-Gerow, Michael A.; Kim, Inyoung; Scahill, Lawrence

2013-01-01

Anxiety is common among adolescents with autism spectrum disorders (ASD) and may amplify the core social disability, thus necessitating combined treatment approaches. This pilot, randomized controlled trial evaluated the feasibility and preliminary outcomes of the Multimodal Anxiety and Social Skills Intervention (MASSI) program in a sample of 30…

Multimodal surveillance sensors, algorithms, and systems

CERN Document Server

Zhu, Zhigang

2007-01-01

From front-end sensors to systems and environmental issues, this practical resource guides you through the many facets of multimodal surveillance. The book examines thermal, vibration, video, and audio sensors in a broad context of civilian and military applications. This cutting-edge volume provides an in-depth treatment of data fusion algorithms that takes you to the core of multimodal surveillance, biometrics, and sentient computing. The book discusses such people and activity topics as tracking people and vehicles and identifying individuals by their speech.Systems designers benefit from d

Multimode waveguide speckle patterns for compressive sensing.

Science.gov (United States)

Valley, George C; Sefler, George A; Justin Shaw, T

2016-06-01

Compressive sensing (CS) of sparse gigahertz-band RF signals using microwave photonics may achieve better performances with smaller size, weight, and power than electronic CS or conventional Nyquist rate sampling. The critical element in a CS system is the device that produces the CS measurement matrix (MM). We show that passive speckle patterns in multimode waveguides potentially provide excellent MMs for CS. We measure and calculate the MM for a multimode fiber and perform simulations using this MM in a CS system. We show that the speckle MM exhibits the sharp phase transition and coherence properties needed for CS and that these properties are similar to those of a sub-Gaussian MM with the same mean and standard deviation. We calculate the MM for a multimode planar waveguide and find dimensions of the planar guide that give a speckle MM with a performance similar to that of the multimode fiber. The CS simulations show that all measured and calculated speckle MMs exhibit a robust performance with equal amplitude signals that are sparse in time, in frequency, and in wavelets (Haar wavelet transform). The planar waveguide results indicate a path to a microwave photonic integrated circuit for measuring sparse gigahertz-band RF signals using CS.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

Science.gov (United States)

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.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

International Nuclear Information System (INIS)

Ismail, M A; Said, M N

2014-01-01

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

Science.gov (United States)

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.

Statistical approach of weakly nonlinear ablative Rayleigh-Taylor instability

International Nuclear Information System (INIS)

Garnier, J.; Masse, L.

2005-01-01

A weakly nonlinear model is proposed for the Rayleigh-Taylor instability in presence of ablation and thermal transport. The nonlinear effects for a single-mode disturbance are computed, included the nonlinear correction to the exponential growth of the fundamental modulation. Mode coupling in the spectrum of a multimode disturbance is thoroughly analyzed by a statistical approach. The exponential growth of the linear regime is shown to be reduced by the nonlinear mode coupling. The saturation amplitude is around 0.1λ for long wavelengths, but higher for short instable wavelengths in the ablative regime

Unconventional geometric logic gate in a strong-driving-assisted multi-mode cavity

International Nuclear Information System (INIS)

Chang-Ning, Pan; Di-Wu, Yang; Xue-Hui, Zhao; Mao-Fa, Fang

2010-01-01

We propose a scheme to implement an unconventional geometric logic gate separately in a two-mode cavity and a multi-mode cavity assisted by a strong classical driving field. The effect of the cavity decay is included in the investigation. The numerical calculation is carried out, and the result shows that our scheme is more tolerant to cavity decay than the previous one because the time consumed for finishing the logic gate is doubly reduced. (general)

Development of a Framework for Multimodal Research: Creation of a Bibliographic Database

National Research Council Canada - National Science Library

Coovert, Michael D; Gray, Ashley A; Elliott, Linda R; Redden, Elizabeth S

2007-01-01

.... The results of the overall effort, the multimodal framework and article tracking sheet, bibliographic database, and searchable multimodal database make substantial and valuable contributions to the accumulation and interpretation of multimodal research. References collected in this effort are listed in the appendix.

Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches.

Science.gov (United States)

Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2015-01-01

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.

Multimodal aspects of CSR communication related to gender empowerment and environmental protection

DEFF Research Database (Denmark)

Maier, Carmen Daniela

Purpose – This paper explores how the multimodal persuasive strategies of CSR communication related to Coca-Cola’s “5 by 20” succeed to highlight the company’s continuous commitment to gender empowerment and environmental protection. Launched in 2010, “5 by 20” is a program designed to empower 5...... as the usual textual focus is extended to a multimodal one. Shedding light on how the multimodal interplay contributes to communicate corporate commitment to gender empowerment and environmental protection, this model can also be employed in order to explore multimodally other areas of CSR communication....... a multimodal analysis model through which it is possible to map and explain the multimodal persuasive strategies employed by the company in their CSR communication. The paper is focused on the analysis of the video series that can be accessed at: http://www.coca-colacompany.com/stories/5by20. Based on a social...

Mode-multiplexed transmission over conventional graded-index multimode fibers

NARCIS (Netherlands)

Ryf, R.; Fontaine, N.K.; Chen, H.; Guan, B.; Huang, B.; Esmaeelpour, M.; Gnauck, A.H.; Randel, S.; Yoo, S.J.B.; Koonen, A.M.J.; Shubochkin, R.; Sun, Yi; Lingle, R.

2015-01-01

We present experimental results for combined mode-multiplexed and wavelength multiplexed transmission over conventional graded-index multimode fibers. We use mode-selective photonic lanterns as mode couplers to precisely excite a subset of the modes of the multimode fiber and additionally to

A Multimodal Database for Affect Recognition and Implicit Tagging

NARCIS (Netherlands)

Soleymani, Mohammad; Lichtenauer, Jeroen; Pun, Thierry; Pantic, Maja

MAHNOB-HCI is a multimodal database recorded in response to affective stimuli with the goal of emotion recognition and implicit tagging research. A multimodal setup was arranged for synchronized recording of face videos, audio signals, eye gaze data, and peripheral/central nervous system

Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Directory of Open Access Journals (Sweden)

Shigang Zhang

2015-10-01

Full Text Available Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics.

Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Science.gov (United States)

Zhang, Shigang; Song, Lijun; Zhang, Wei; Hu, Zheng; Yang, Yongmin

2015-01-01

Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics. PMID:26457709

All-optical universal logic gates on nonlinear multimode interference coupler using tunable input intensity

Science.gov (United States)

Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

2015-04-01

The theory of Nonlinear Modal Propagation Analysis Method (NMPA) have shown significant features of nonlinear multimode interference (MMI) coupler with compact dimension and when launched near the threshold of nonlinearity. Moreover, NMPA have the potential to allow studying the nonlinear MMI based the modal interference to explorer the phenomenon that what happen due to the natural of multimode region. Proposal of all-optical switch based NMPA has approved its capability to achieving the all-optical gates. All-optical gates have attracted increasing attention due to their practical utility in all-optical signal processing networks and systems. Nonlinear multimode interference devices could apply as universal all-optical gates due to significant features that NMPA introduce them. In this Paper, we present a novel Ultra-compact MMI coupler based on NMPA method in low intensity compared to last reports either as a novel design method and potential application for optical NAND, NOR as universal gates on single structure for Boolean logic signal processing devices and optimize their application via studding the contrast ratio between ON and OFF as a function of output width. We have applied NMPA for several applications so that the miniaturization in low nonlinear intensities is their main purpose.

Quantifying Quality Aspects of Multimodal Interactive Systems

CERN Document Server

Kühnel, Christine

2012-01-01

This book systematically addresses the quantification of quality aspects of multimodal interactive systems. The conceptual structure is based on a schematic view on human-computer interaction where the user interacts with the system and perceives it via input and output interfaces. Thus, aspects of multimodal interaction are analyzed first, followed by a discussion of the evaluation of output and input and concluding with a view on the evaluation of a complete system.

A novel APD-based detector module for multi-modality PET/SPECT/CT scanners

International Nuclear Information System (INIS)

Saoudi, A.; Lecomte, R.

1999-01-01

The lack of anatomical information in SPECT and PET images is one of the major factors limiting the ability to localize and accurately quantify radionuclide uptake in small regions of interest. This problem could be resolved by using multi-modality scanners having the capability to acquire anatomical and functional images simultaneously. The feasibility of a novel detector suitable for measuring high-energy annihilation radiation in PET, medium-energy γ-rays in SPECT and low-energy X-rays in transmission CT is demonstrated and its performance is evaluated for potential use in multi-modality PET/SPECT/CT imaging. The proposed detector consists of a thin CsI(Tl) scintillator sitting on top of a deep GSO/LSO pair read out by an avalanche photodiode. The GSO/LOS pair provides depth-of-interaction information for 511 keV detection in PET, while the thin CsI(Tl) that is essentially transparent to annihilation radiation is used for detecting lower energy X- and γ-rays. The detector performance is compared to that of an LSO/YSO phoswich. Although the implementation of the proposed GSO/LSO/CsI(Tl) detector raises special problems that increase complexity, it generally outperforms the LSO/YSO phoswich for simultaneous PET, SPECT and CT imaging

Player/Avatar Body Relations in Multimodal Augmented Reality Games

NARCIS (Netherlands)

Rosa, N.E.

2016-01-01

Augmented reality research is finally moving towards multimodal experiences: more and more applications do not only include visuals, but also audio and even haptics. The purpose of multimodality in these applications can be to increase realism or to increase the amount or quality of communicated

Multifuel multimodal network design; Projeto de redes multicombustiveis multimodal

Energy Technology Data Exchange (ETDEWEB)

Lage, Carolina; Dias, Gustavo; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE). Programa de Engenharia de Producao

2008-07-01

The objective of the Multi commodity Multimodal Network Project is the development of modeling tools and methodologies for the optimal sizing of production networks and multimodal distribution of multiple fuel and its incomes, considering investments and transportation costs. Given the inherently non-linear combinatory nature of the problem, the resolution of real instances by the complete model, in an exact way, becomes computationally intractable. Thus, the strategy for resolution should contain a combination of exacts and heuristics methods, that must be applied to subdivisions of the original problem. This paper deals with one of these subdivisions, tackling the problem of modeling a network of pipelines in order to drain the production of ethanol away from the producing plants. The objective consists in defining the best network topology, minimizing investment and operational costs, and attending the total demand. In order to do that, the network was considered a tree, where the nodes are the center of producing regions and the edges are the pipelines, trough where the ethanol produced by plants must be drained away. The main objective also includes the decision over the optimal diameter of each pipeline and the optimal size of the bombs, in order to minimize the pumping costs. (author)

A multimodal physical therapy approach utilizing the Maitland concept in the management of a patient with cervical and lumbar radiculitis and Ehlers-Danlos syndrome-hypermobility type: A case report.

Science.gov (United States)

Pennetti, Adelina

2018-07-01

The purpose of this case report is to present a multimodal approach for patient management using the Maitland concept framework for cervical and lumbar radiculitis with an underlying diagnosis of Ehlers-Danlos Syndrome-Hypermobility Type (EDS-HT). This case presents care guided by evidence, patient values, and rationale for the selected course of physical therapy treatment provided by therapist experience. A 35-year-old female with a 2-year history of worsening lumbar and cervical pain was referred to physical therapy to address these musculoskeletal issues concurrent with diagnostic testing for EDS. A multimodal approach including manual therapy, therapeutic exercise, postural and body mechanics education, and a home exercise program was used. The patient specific functional scale (PSFS) was used to gauge patient's perceived improvements which were demonstrated by increased scores at reevaluation and at discharge. Following the Maitland concept framework, the physical therapist was able to make sound clinical decisions by tracking the logical flow of constant patient assessment. A 10-month course of treatment designed to maximize recovery of function was successful with a chronic history of pain and the EDS-HT diagnosis. The role of education and empowering the patient is shown to be of utmost importance. Optimizing therapeutic outcomes long-term for this patient population requires maintaining a home exercise program, adaptation and modifications of work and lifestyle activities.

Multimode optical fiber

Science.gov (United States)

Bigot-Astruc, Marianne; Molin, Denis; Sillard, Pierre

2014-11-04

A depressed graded-index multimode optical fiber includes a central core, an inner depressed cladding, a depressed trench, an outer depressed cladding, and an outer cladding. The central core has an alpha-index profile. The depressed claddings limit the impact of leaky modes on optical-fiber performance characteristics (e.g., bandwidth, core size, and/or numerical aperture).

Language and Identity in Multimodal Text: Case Study of Thailand’s Bank Pamphlet

Directory of Open Access Journals (Sweden)

Korapat Pruekchaikul

2017-12-01

Full Text Available With the main objective of presenting a linguistic model for the analysis of identity construction in multimodal texts, particularly in advertising, this article attempts to integrate three theoretical frameworks, namely the types of discourse of the Socio-Discursive Interactionism, Greimas’ actantial roles and the symbolic processes of the Grammar of Visual Design proposed by Kress e van Leeuwen. The first two theories are used to analyze verbal language form whereas the third is exclusively for images in advertising. The data sample is a Thai bank pamphlet of Siam Commercial Bank, collected in Bangkok, Thailand, in June, 2015. According to the data analysis, the theoretical frameworks employed here proves that identity, the psychological product, exists in the human mind and can be indexed by language in interaction. Also, the analysis found that identity could be projected as multimodally as language manifestation, of which forms are not only verbal but also pictorial.

Multimodal versus Unimodal Instruction in a Complex Learning Context.

Science.gov (United States)

Gellevij, Mark; van der Meij, Hans; de Jong, Ton; Pieters, Jules

2002-01-01

Compared multimodal instruction with text and pictures with unimodal text-only instruction as 44 college students used a visual or textual manual to learn a complex software application. Results initially support dual coding theory and indicate that multimodal instruction led to better performance than unimodal instruction. (SLD)

Facilitating Multiple Intelligences Through Multimodal Learning Analytics

Directory of Open Access Journals (Sweden)

Ayesha PERVEEN

2018-01-01

Full Text Available This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner’s 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as multiple intelligences by online education systems and then suggests a framework of the advanced form of learning analytics i.e., multimodal learning analytics for tracing and facilitating multiple intelligences while they are engaged in online ubiquitous learning. As multimodal learning analytics is still an evolving area, it poses many challenges for technologists, educationists as well as organizational managers. Learning analytics make machines meet humans, therefore, the educationists with an expertise in learning theories can help technologists devise latest technological methods for multimodal learning analytics and organizational managers can implement them for the improvement of online education. Therefore, a careful instructional design based on a deep understanding of students’ learning abilities, is required to develop teaching plans and technological possibilities for monitoring students’ learning paths. This is how learning analytics can help design an adaptive instructional design based on a quick analysis of the data gathered. Based on that analysis, the academicians can critically reflect upon the quick or delayed implementation of the existing instructional design based on students’ cognitive abilities or even about the single or double loop learning design. The researcher concludes that the online education is multimodal in nature, has the capacity to endorse multiliteracies and, therefore, multiple intelligences can be tracked and facilitated through multimodal learning analytics in an online mode. However, online teachers’ training both in technological implementations and

The Stability of Multi-modal Traffic Network

International Nuclear Information System (INIS)

Han Linghui; Sun Huijun; Zhu Chengjuan; Jia Bin; Wu Jianjun

2013-01-01

There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion. (general)

Photoacoustic-Based Multimodal Nanoprobes: from Constructing to Biological Applications.

Science.gov (United States)

Gao, Duyang; Yuan, Zhen

2017-01-01

Multimodal nanoprobes have attracted intensive attentions since they can integrate various imaging modalities to obtain complementary merits of single modality. Meanwhile, recent interest in laser-induced photoacoustic imaging is rapidly growing due to its unique advantages in visualizing tissue structure and function with high spatial resolution and satisfactory imaging depth. In this review, we summarize multimodal nanoprobes involving photoacoustic imaging. In particular, we focus on the method to construct multimodal nanoprobes. We have divided the synthetic methods into two types. First, we call it "one for all" concept, which involves intrinsic properties of the element in a single particle. Second, "all in one" concept, which means integrating different functional blocks in one particle. Then, we simply introduce the applications of the multifunctional nanoprobes for in vivo imaging and imaging-guided tumor therapy. At last, we discuss the advantages and disadvantages of the present methods to construct the multimodal nanoprobes and share our viewpoints in this area.

Multimodality treatment of locally advanced squamous cell carcinoma of the oesophagus: A comprehensive review and network meta-analysis.

Science.gov (United States)

Montagnani, Francesco; Fornaro, Lorenzo; Frumento, Paolo; Vivaldi, Caterina; Falcone, Alfredo; Fioretto, Luisa

2017-06-01

Surgery is the mainstay of treatment for oesophageal squamous-cell carcinoma (OSCC) but with poor results. Attempts to improve patient outcome have been made by introducing chemotherapy (CT), radiotherapy (RT), or both (CRT). However, randomized comparisons for all these strategies are not always available. We conducted an extensive literature search for studies comparing surgery with multimodality treatment (i.e. [neo-]adjuvant CT or RT or CRT or definitive CRT). Network meta-analysis was performed in a Bayesian framewor and node-split models were built to assess inconsistency. Twenty-five trials including a total of 3866 OSCC patients were included. Neoadjuvant CRT was associated with the most robust survival advantage across different multimodality treatment options (HR 0.73; 95% credible interval [CrI] 0.63-0.86). Definitive CRT was also significantly more effective than surgery but with greater uncertainties (HR 0.62; 95%CrI 0.41-0.96). Neoadjuvant CT (HR 0.90; 95%CrI 0.76-1.07) and adjuvant CRT (HR 1.00; 95%CrI 0.70-1.40) are associated with a non-significant benefit. To date, neoadjuvant CRT seems to represent the best approach to maximize the benefit of a multimodality approach. Copyright © 2017 Elsevier B.V. All rights reserved.

PET-MRI and multimodal cancer imaging

International Nuclear Information System (INIS)

Wang Taisong; Zhao Jinhua; Song Jianhua

2011-01-01

Multimodality imaging, specifically PET-CT, brought a new perspective into the fields of clinical imaging. Clinical cases have shown that PET-CT has great value in clinical diagnosis and experimental research. But PET-CT still bears some limitations. A major drawback is that CT provides only limited soft tissue contrast and exposes the patient to a significant radiation dose. MRI overcome these limitations, it has excellent soft tissue contrast, high temporal and spatial resolution and no radiation damage. Additionally, since MRI provides also functional information, PET-MRI will show a new direction of multimodality imaging in the future. (authors)

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

Directory of Open Access Journals (Sweden)

Peter Kampmann

2014-04-01

Full Text Available With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach.

Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation

International Nuclear Information System (INIS)

Wang, Yan; Zhou, Jiliu; Zhang, Pei; An, Le; Ma, Guangkai; Kang, Jiayin; Shi, Feng; Shen, Dinggang; Wu, Xi; Lalush, David S; Lin, Weili

2016-01-01

Positron emission tomography (PET) has been widely used in clinical diagnosis for diseases and disorders. To obtain high-quality PET images requires a standard-dose radionuclide (tracer) injection into the human body, which inevitably increases risk of radiation exposure. One possible solution to this problem is to predict the standard-dose PET image from its low-dose counterpart and its corresponding multimodal magnetic resonance (MR) images. Inspired by the success of patch-based sparse representation (SR) in super-resolution image reconstruction, we propose a mapping-based SR (m-SR) framework for standard-dose PET image prediction. Compared with the conventional patch-based SR, our method uses a mapping strategy to ensure that the sparse coefficients, estimated from the multimodal MR images and low-dose PET image, can be applied directly to the prediction of standard-dose PET image. As the mapping between multimodal MR images (or low-dose PET image) and standard-dose PET images can be particularly complex, one step of mapping is often insufficient. To this end, an incremental refinement framework is therefore proposed. Specifically, the predicted standard-dose PET image is further mapped to the target standard-dose PET image, and then the SR is performed again to predict a new standard-dose PET image. This procedure can be repeated for prediction refinement of the iterations. Also, a patch selection based dictionary construction method is further used to speed up the prediction process. The proposed method is validated on a human brain dataset. The experimental results show that our method can outperform benchmark methods in both qualitative and quantitative measures. (paper)

Realtime Interaction Analysis of Social Interplay in a Multimodal Musical-Sonic Interaction Context

DEFF Research Database (Denmark)

Hansen, Anne-Marie

2010-01-01

This paper presents an approach to the analysis of social interplay among users in a multimodal interaction and musical performance situation. The approach consists of a combined method of realtime sensor data analysis for the description and interpretation of player gestures and video micro......-analysis methods used to describe the interaction situation and the context in which the social interplay takes place. This combined method is used in an iterative process, where the design of interactive games with musical-sonic feedback is improved according to newly discovered understandings and interpretations...

Multimode Coupling Theory for Kelvin–Helmholtz Instability in Incompressible Fluid

International Nuclear Information System (INIS)

Li-Feng, Wang; Ying-Jun, Li; Wen-Hua, Ye; Zheng-Feng, Fan

2009-01-01

A weakly nonlinear model is proposed for multimode Kelvin–Helmholtz instability. The second-order mode coupling formula for Kelvin–Helmholtz instability in two-dimensional incompressible fluid is presented by expanding the perturbation velocity potential to second order. It is found that there is an important resonance in the course of the sum frequency mode coupling but the difference frequency mode coupling does not have. This resonance makes the sum frequency mode coupling process relatively complex. The sum frequency mode coupling is strongly dependent on time especially when the density of the two fluids is adjacent and the difference frequency mode coupling is not

Agrupador de imágenes multimodal no supervisado

OpenAIRE

Pérez Hernando, Jesús

2013-01-01

Trabajo Fin de Máster donde se implementa un método multimodal para la clasificación de imágenes sin etiquetar y sin intervención humana. Treball Fi de Màster on s'implementa un mètode multimodal per a la classificació d'imatges sense etiquetar i sense intervenció humana. Master thesis for the Computer Science Engineering program.

Multimodal treatment in children and adolescents with attention-deficit/hyperactivity disorder: a 6-month follow-up.

Science.gov (United States)

Duric, Nezla S; Assmus, Jørg; Gundersen, Doris; Duric Golos, Alisa; Elgen, Irene B

2017-07-01

Different treatment approaches aimed at reducing attention-deficit/hyperactivity disorder (ADHD) core symptoms are available. However, factors such as intolerance, side-effects, lack of efficacy, high new technology costs, and placebo effect have spurred on an increasing interest in alternative or complementary treatment. The aim of this study is to explore efficacy of multimodal treatment consisting of standard stimulant medication (methylphenidate) and neurofeedback (NF) in combination, and to compare it with the single treatment in 6-month follow-up in ADHD children and adolescents. This randomized controlled trial with 6-month follow-up comprised three treatment arms: multimodal treatment (NF + MED), MED alone, and NF alone. A total of 130 ADHD children/adolescents participated, and 62% completed the study. ADHD core symptoms were recorded pre-/post-treatment, using parents' and teachers' forms taken from Barkley's Defiant Children: A Clinician's Manual for Assessment and Parent Training, and a self-report questionnaire. Significant ADHD core symptom improvements were reported 6 months after treatment completion by parents, teachers, and participants in all three groups, with marked improvement in inattention in all groups. However, no significant improvements in hyperactivity or academic performance were reported by teachers or self-reported by children/adolescents, respectively, in the three groups. Changes obtained with multimodal treatment at 6-month follow-up were comparable to those with single medication treatment, as reported by all participants. Multimodal treatment using combined stimulant medication and NF showed 6-month efficacy in ADHD treatment. More research is needed to explore whether multimodal treatment is suitable for ADHD children and adolescents who showed a poor response to single medication treatment, and for those who want to reduce the use of stimulant medication.

Multimodal news framing effects

NARCIS (Netherlands)

Powell, T.E.

2017-01-01

Visuals in news media play a vital role in framing citizens’ political preferences. Yet, compared to the written word, visual images are undervalued in political communication research. Using framing theory, this thesis redresses the balance by studying the combined, or multimodal, effects of visual

Learning Multimodal Deep Representations for Crowd Anomaly Event Detection

Directory of Open Access Journals (Sweden)

Shaonian Huang

2018-01-01

Full Text Available Anomaly event detection in crowd scenes is extremely important; however, the majority of existing studies merely use hand-crafted features to detect anomalies. In this study, a novel unsupervised deep learning framework is proposed to detect anomaly events in crowded scenes. Specifically, low-level visual features, energy features, and motion map features are simultaneously extracted based on spatiotemporal energy measurements. Three convolutional restricted Boltzmann machines are trained to model the mid-level feature representation of normal patterns. Then a multimodal fusion scheme is utilized to learn the deep representation of crowd patterns. Based on the learned deep representation, a one-class support vector machine model is used to detect anomaly events. The proposed method is evaluated using two available public datasets and compared with state-of-the-art methods. The experimental results show its competitive performance for anomaly event detection in video surveillance.

Brightness enhancement of a multi-mode ribbon fiber using transmitting Bragg gratings

Science.gov (United States)

Anderson, B. M.; Venus, G.; Ott, D.; Divliansky, I.; Dawson, J. W.; Drachenberg, D. R.; Messerly, M. J.; Pax, P. H.; Tassano, J. B.; Glebov, L. B.

2015-03-01

Increasing the dimensions of a waveguide provides the simplest means of reducing detrimental nonlinear effects, but such systems are inherently multi-mode, reducing the brightness of the system. Furthermore, using rectangular dimensions allows for improved heat extraction, as well as uniform temperature profile within the core. We propose a method of using the angular acceptance of a transmitting Bragg grating (TBG) to filter the fundamental mode of a fiber laser resonator, and as a means to increase the brightness of multi-mode fiber laser. Numerical modeling is used to calculate the diffraction losses needed to suppress the higher order modes in a laser system with saturable gain. The model is tested by constructing an external cavity resonator using an ytterbium doped ribbon fiber with core dimensions of 107.8μm by 8.3μm as the active medium. We show that the TBG increases the beam quality of the system from M2 = 11.3 to M2 = 1.45, while reducing the slope efficiency from 76% to 53%, overall increasing the brightness by 5.1 times.

Operative and economic evaluation of a 'Laser Printer Multimodality' System

International Nuclear Information System (INIS)

Battaglia, G.; Moscatelli, G.; Maroldi, R.; Chiesa, A.

1991-01-01

The increasing application of digital techniques to diagnostic imaging is causing significant changes in several related activities, such as a reproduction of digital images on film. In the Department of Diagnostic Imaging of the University of Brescia, about 70% of the whole of images are produced by digital techniques; at present, most of these images are reproduced on film with a Multimodality System interfacing CT, MR, DSA, and DR units with a single laser printer. Our analysis evaluates the operative and economics aspects of image reproduction, by comparing the 'single cassette' multiformat Camera and the Laser Printer Multimodality SAystem. Our results point out the advantages obtained by reproducing images with a Laser Printer Multimodality System: outstanding quality, reproduction of multiple originals, and marked reduction in the time needed for both image archiving and film handling. The Laser Printer Multimodality System allows over 5 hours/day to be saved -that is to say the working day of an operator, who can be thus shifted to other functions. The important economic aspect of the reproduction of digital images on film proves the Laser Printer Multimodality System to have some advantage over Cameras

Sustainable Multi-Modal Sensing by a Single Sensor Utilizing the Passivity of an Elastic Actuator

Directory of Open Access Journals (Sweden)

Takashi Takuma

2014-05-01

Full Text Available When a robot equipped with compliant joints driven by elastic actuators contacts an object and its joints are deformed, multi-modal information, including the magnitude and direction of the applied force and the deformation of the joint, is used to enhance the performance of the robot such as dexterous manipulation. In conventional approaches, some types of sensors used to obtain the multi-modal information are attached to the point of contact where the force is applied and at the joint. However, this approach is not sustainable for daily use in robots, i.e., not durable or robust, because the sensors can undergo damage due to the application of excessive force and wear due to repeated contacts. Further, multiple types of sensors are required to measure such physical values, which add to the complexity of the device system of the robot. In our approach, a single type of sensor is used and it is located at a point distant from the contact point and the joint, and the information is obtained indirectly by the measurement of certain physical parameters that are influenced by the applied force and the joint deformation. In this study, we employ the McKibben pneumatic actuator whose inner pressure changes passively when a force is applied to the actuator. We derive the relationships between information and the pressures of a two-degrees-of-freedom (2-DoF joint mechanism driven by four pneumatic actuators. Experimental results show that the multi-modal information can be obtained by using the set of pressures measured before and after the force is applied. Further, we apply our principle to obtain the stiffness values of certain contacting objects that can subsequently be categorized by using the aforementioned relationships.

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

Science.gov (United States)

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

Science.gov (United States)

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Implementation of multimode release criteria and dose standard alternatives

International Nuclear Information System (INIS)

Klett, R.

1993-01-01

The current standard that regulates the disposal of high-level radioactive wastes (HLW) and transuranic (TRU) wastes evaluates the cumulative risk of all repositories with a single derived set of generic release limits. This paper reviews the technical basis, attributes, and deficiencies of the present approach and two alternative modifications and extensions. The alternatives are the multimode release limits applied at the point of release and a dose standard alternative suggested at the first Electric Power Research Institute (EPRI) waste disposal workshop. Methods of developing and applying the alternatives are presented and some suggestions are given for incorporating them in the standards

Multimodality management of primary diaphragmatic synovial sarcoma: First report

Directory of Open Access Journals (Sweden)

Preyas J Vaidya

2016-01-01

Full Text Available Synovial cell sarcoma is an extremely rare tumor of mesenchymal origin. It commonly affects the soft tissues of the extremities but could possibly origin from the head and neck, heart, lung, pleura, mediastinum, esophagus, abdominal wall and the mesentery, and retroperitoneum. Primary synovial sarcoma of pleura, mediastinum, and lung have been reported. Primary synovial sarcoma of the diaphragm has not been reported to the best of our knowledge. We report a case of primary synovial cell sarcoma of the diaphragm presenting as a recurrent pleural effusion and pain in the left hypochondrium managed with multimodality approach.

Hybrid PD and effective multi-mode positive position feedback control for slewing and vibration suppression of a smart flexible manipulator

International Nuclear Information System (INIS)

Lou, Jun-qiang; Wei, Yan-ding; Yang, Yi-ling; Xie, Feng-ran

2015-01-01

A hybrid control strategy for slewing and vibration suppression of a smart flexible manipulator is presented in this paper. It consists of a proportional derivative controller to realize motion control, and an effective multi-mode positive position feedback (EMPPF) controller to suppress the multi-mode vibration. Rather than treat each mode equally as the standard multi-mode PPF, the essence of the EMPPF is that control forces of different modes are applied according to the mode parameters of the respective modes, so the vibration modes with less vibration energy receive fewer control forces. Stability conditions for the close loop system are established through stability analysis. Optimal parameters of the EMPPF controller are obtained using the method of root locus analysis. The performance of the proposed strategy is demonstrated by simulation and experiments. Experimental results show that the first two vibration modes of the manipulator are effectively suppressed. The setting time of the setup descends approximately 55%, reaching 3.12 s from 5.67 s. (paper)

Hybrid PD and effective multi-mode positive position feedback control for slewing and vibration suppression of a smart flexible manipulator

Science.gov (United States)

Lou, Jun-qiang; Wei, Yan-ding; Yang, Yi-ling; Xie, Feng-ran

2015-03-01

A hybrid control strategy for slewing and vibration suppression of a smart flexible manipulator is presented in this paper. It consists of a proportional derivative controller to realize motion control, and an effective multi-mode positive position feedback (EMPPF) controller to suppress the multi-mode vibration. Rather than treat each mode equally as the standard multi-mode PPF, the essence of the EMPPF is that control forces of different modes are applied according to the mode parameters of the respective modes, so the vibration modes with less vibration energy receive fewer control forces. Stability conditions for the close loop system are established through stability analysis. Optimal parameters of the EMPPF controller are obtained using the method of root locus analysis. The performance of the proposed strategy is demonstrated by simulation and experiments. Experimental results show that the first two vibration modes of the manipulator are effectively suppressed. The setting time of the setup descends approximately 55%, reaching 3.12 s from 5.67 s.

Multimodal nonlinear microscopy: A powerful label-free method for supporting standard diagnostics on biological tissues

Directory of Open Access Journals (Sweden)

Riccardo Cicchi

2014-09-01

Full Text Available The large use of nonlinear laser scanning microscopy in the past decade paved the way for potential clinical application of this imaging technique. Modern nonlinear microscopy techniques offer promising label-free solutions to improve diagnostic performances on tissues. In particular, the combination of multiple nonlinear imaging techniques in the same microscope allows integrating morphological with functional information in a morpho-functional scheme. Such approach provides a high-resolution label-free alternative to both histological and immunohistochemical examination of tissues and is becoming increasingly popular among the clinical community. Nevertheless, several technical improvements, including automatic scanning and image analysis, are required before the technique represents a standard diagnostic method. In this review paper, we highlight the capabilities of multimodal nonlinear microscopy for tissue imaging, by providing various examples on colon, arterial and skin tissues. The comparison between images acquired using multimodal nonlinear microscopy and histology shows a good agreement between the two methods. The results demonstrate that multimodal nonlinear microscopy is a powerful label-free alternative to standard histopathological methods and has the potential to find a stable place in the clinical setting in the near future.

'MetaTaal': enhancing complex syntax in children with specific language impairment--a metalinguistic and multimodal approach.

Science.gov (United States)

Zwitserlood, Rob; Wijnen, Frank; van Weerdenburg, Marjolijn; Verhoeven, Ludo

2015-01-01

Currently, most research on the effective treatment of morphosyntax in children with specific language impairment (SLI) pertains to younger children. In the last two decades, several studies have provided evidence that intervention for older school-age children with SLI can be effective. These metalinguistic intervention approaches teach grammatical rules explicitly and use shapes and colours as two-dimensional visual support. Reading or writing activities form a substantial part of these interventions. However, some children with SLI are poor readers and might benefit more from an approach that is less dependent on literacy skills. To examine the effectiveness of a combined metalinguistic and multimodal approach in older school-age children with SLI. The intervention was adapted to suit poor readers and targeted the improvement of relative clause production, because relative clauses still pose difficulties for older children with SLI. Participants were 12 monolingual Dutch children with SLI (mean age 11;2). All children visited a special school for children with speech and language disorders in the Netherlands. A quasi-experimental multiple-baseline design was chosen to evaluate the effectiveness of the intervention. A set of tasks was constructed to test relative clause production and comprehension. Two balanced versions were alternated in order to suppress a possible learning effect from multiple presentations of the tasks. After 3 monthly baseline measurements, the children received individual treatment with a protocolled intervention programme twice a week during 5 weeks. The tests were repeated directly post-therapy and at a retention measurement 3 months later. During the intervention programme, the speech therapist delivering the treatment remained blind to the test results. No significant changes were found during the baseline measurements. However, measurement directly post-therapy showed that 5 h of intervention produced significant improvement on the

Strategy development management of Multimodal Transport Network

Directory of Open Access Journals (Sweden)

Nesterova Natalia S.

2016-01-01

Full Text Available The article gives a brief overview of works on the development of transport infrastructure for multimodal transportation and integration of Russian transport system into the international transport corridors. The technology for control of the strategy, that changes shape and capacity of Multi-modal Transport Network (MTN, is considered as part of the methodology for designing and development of MTN. This technology allows to carry out strategic and operational management of the strategy implementation based on the use of the balanced scorecard.

Multimodal Behavior Therapy: Case Study of a High School Student.

Science.gov (United States)

Seligman, Linda

1981-01-01

A case study of a high school student concerned with weight problems illustrates multimodal behavior therapy and its use in a high school setting. Multimodal therapy allows the school counselor to maximize referral sources while emphasizing growth and actualization. (JAC)

Acting rehearsal in collaborative multimodal mixed reality environments

OpenAIRE

Steptoe, William; Normand, Jean-Marie; Oyekoya, Oyewole; Pece, Fabrizio; Giannopoulos, Elias; Tecchia, Franco; Steed, Anthony; Weyrich, Tim; Kautz, Jan; Slater, Mel

2012-01-01

This paper presents the use of our multimodal mixed reality telecommunication system to support remote acting rehearsal. The rehearsals involved two actors, located in London and Barcelona, and a director in another location in London. This triadic audiovisual telecommunication was performed in a spatial and multimodal collaborative mixed reality environment based on the 'destination-visitor' paradigm, which we define and put into use. We detail our heterogeneous system architecture, which sp...

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

Energy Technology Data Exchange (ETDEWEB)

Kapur, T. [Brigham & Women’s Hospital (United States)

2016-06-15

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

International Nuclear Information System (INIS)

Kapur, T.

2016-01-01

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504

Developing a new method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources

Directory of Open Access Journals (Sweden)

Aidin Delgoshaei

2016-09-01

Full Text Available The issue of resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating is frequently seen after initial scheduling of a project in practice and causes significant amount of efforts to modify the initial schedules. In this research, a new method is developed for modifying over-allocated schedules in a multi-mode resource constrained project scheduling problems (MRCPSPs with positive cash flows (MRCPSP-PCF. The aim is to maximize profit of the MRCPSPs or logically minimizing costs. The proposed method can be used as a macro in Microsoft Office Project® Software to modify resource over-allocated days after scheduling a project. This research considers progress payment method and preemptive resources. The proposed approach maximizes profit by scheduling activities through the resource calendar respecting to the available level of preemptive resources and activity numbers. To examine the performance of the proposed method a number of experiments derived from the literature are solved. The results are then compared with the circumstances where resource constraints are relaxed. The outcomes show that in all studied cases, the proposed algorithm can provide modified schedules with no over-allocated days. Afterward the method is applied to modify a manufacturing project in practice.

MIDA - Optimizing control room performance through multi-modal design

International Nuclear Information System (INIS)

Ronan, A. M.

2006-01-01

Multi-modal interfaces can support the integration of humans with information processing systems and computational devices to maximize the unique qualities that comprise a complex system. In a dynamic environment, such as a nuclear power plant control room, multi-modal interfaces, if designed correctly, can provide complementary interaction between the human operator and the system which can improve overall performance while reducing human error. Developing such interfaces can be difficult for a designer without explicit knowledge of Human Factors Engineering principles. The Multi-modal Interface Design Advisor (MIDA) was developed as a support tool for system designers and developers. It provides design recommendations based upon a combination of Human Factors principles, a knowledge base of historical research, and current interface technologies. MIDA's primary objective is to optimize available multi-modal technologies within a human computer interface in order to balance operator workload with efficient operator performance. The purpose of this paper is to demonstrate MIDA and illustrate its value as a design evaluation tool within the nuclear power industry. (authors)

Multimodal Magnetic-Plasmonic Nanoparticles for Biomedical Applications

Directory of Open Access Journals (Sweden)

Shelley Stafford

2018-01-01

Full Text Available Magnetic plasmonic nanomaterials are of great interest in the field of biomedicine due to their vast number of potential applications, for example, in molecular imaging, photothermal therapy, magnetic hyperthermia and as drug delivery vehicles. The multimodal nature of these nanoparticles means that they are potentially ideal theranostic agents—i.e., they can be used both as therapeutic and diagnostic tools. This review details progress in the field of magnetic-plasmonic nanomaterials over the past ten years, focusing on significant developments that have been made and outlining the future work that still needs to be done in this fast emerging area. The review describes the main synthetic approaches to each type of magnetic plasmonic nanomaterial and the potential biomedical applications of these hybrid nanomaterials.

Pattern recognition of neurotransmitters using multimode sensing.

Science.gov (United States)

Stefan-van Staden, Raluca-Ioana; Moldoveanu, Iuliana; van Staden, Jacobus Frederick

2014-05-30

Pattern recognition is essential in chemical analysis of biological fluids. Reliable and sensitive methods for neurotransmitters analysis are needed. Therefore, we developed for pattern recognition of neurotransmitters: dopamine, epinephrine, norepinephrine a method based on multimode sensing. Multimode sensing was performed using microsensors based on diamond paste modified with 5,10,15,20-tetraphenyl-21H,23H-porphyrine, hemin and protoporphyrin IX in stochastic and differential pulse voltammetry modes. Optimized working conditions: phosphate buffer solution of pH 3.01 and KCl 0.1mol/L (as electrolyte support), were determined using cyclic voltammetry and used in all measurements. The lowest limits of quantification were: 10(-10)mol/L for dopamine and epinephrine, and 10(-11)mol/L for norepinephrine. The multimode microsensors were selective over ascorbic and uric acids and the method facilitated reliable assay of neurotransmitters in urine samples, and therefore, the pattern recognition showed high reliability (RSDneurotransmitters on biological fluids at a lower determination level than chromatographic methods. The sampling of the biological fluids referees only to the buffering (1:1, v/v) with a phosphate buffer pH 3.01, while for chromatographic methods the sampling is laborious. Accordingly with the statistic evaluation of the results at 99.00% confidence level, both modes can be used for pattern recognition and quantification of neurotransmitters with high reliability. The best multimode microsensor was the one based on diamond paste modified with protoporphyrin IX. Copyright © 2014 Elsevier B.V. All rights reserved.

Validation of a multimodal travel simulator with travel information provision

NARCIS (Netherlands)

Chorus, C.G.; Molin, E.J.E.; Arentze, T.A.; Hoogendoorn, S.P.; Timmermans, H.J.P.; Wee, van G.P.

2007-01-01

This paper presents a computer based travel simulator for collecting data concerning the use of next-generation ATIS and their effects on traveler decision making in a multimodal travel environment. The tool distinguishes itself by presenting a completely abstract multimodal transport network, where

OSM-ORIENTED METHOD OF MULTIMODAL ROUTE PLANNING

Directory of Open Access Journals (Sweden)

X. Li

2015-07-01

Full Text Available With the increasing pervasiveness of basic facilitate of transportation and information, the need of multimodal route planning is becoming more essential in the fields of communication and transportation, urban planning, logistics management, etc. This article mainly described an OSM-oriented method of multimodal route planning. Firstly, it introduced how to extract the information we need from OSM data and build proper network model and storage model; then it analysed the accustomed cost standard adopted by most travellers; finally, we used shortest path algorithm to calculate the best route with multiple traffic means.

Self-imaging effect of TM modes in photonic crystal multimode waveguides only exhibiting band gaps for TE modes

International Nuclear Information System (INIS)

Yu Tianbao; Jiang Xiaoqing; Yang Jianyi; Zhou Haifeng; Liao Qinghua; Wang Minghua

2007-01-01

This Letter presents the properties of transverse-magnetic (TM) modes in multimode photonic crystal waveguides (PCWs), which only exhibit photonic band gaps for transverse-electric (TE) modes. A good equivalent model is applied to analysis the designed structures on the basis of multimode interference effect and self-imaging principle. The performance shows that the TM modes can also be propagated with high efficiency, and resemble index-guided modes owing to the combination of total internal reflection (TIR) and distribution Bragg reflection. It provides a novel way to realize the components for both TM and TE polarizations by combining PBG and TIR effect in PCWs. As one of potential applications, polarization-insensitive power splitter based on the proposed structures can be designed

Multi-mode interference revealed by two photon absorption in silicon rich SiO2 waveguides

International Nuclear Information System (INIS)

Manna, S.; Ramiro-Manzano, F.; Mancinelli, M.; Turri, F.; Pavesi, L.; Ghulinyan, M.; Pucker, G.

2015-01-01

Photoluminescence (PL) from Si nanocrystals (NCs) excited by two-photon absorption (TPA) has been observed in Si nanocrystal-based waveguides fabricated by plasma enhanced chemical vapor deposition. The TPA excited photoluminescence emission resembles the one-photon excited photoluminescence arising from inter-band transitions in the quantum confined Si nanocrystals. By measuring the non-linear transmission of waveguides, a large TPA coefficient of β up to 10 −8  cm/W has been measured at 1550 nm. These values of β depend on the Si NCs size and are two orders of magnitude larger than the bulk silicon value. Here, we propose to use the TPA excited visible PL emission as a tool to map the spatial intensity profile of the 1550 nm propagating optical modes in multimode waveguides. In this way, multimode interference has been revealed experimentally and confirmed through a finite element simulation

Increased discriminability of authenticity from multimodal laughter is driven by auditory information.

Science.gov (United States)

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.

Design and fabrication of multimode interference couplers based on digital micro-mirror system

Science.gov (United States)

Wu, Sumei; He, Xingdao; Shen, Chenbo

2008-03-01

Multimode interference (MMI) couplers, based on the self-imaging effect (SIE), are accepted popularly in integrated optics. According to the importance of MMI devices, in this paper, we present a novel method to design and fabricate MMI couplers. A technology of maskless lithography to make MMI couplers based on a smart digital micro-mirror device (DMD) system is proposed. A 1×4 MMI device is designed as an example, which shows the present method is efficient and cost-effective.

A new proposal for greenhouse gas emissions responsibility allocation: best available technologies approach.

Science.gov (United States)

Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo

2014-01-01

In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.

Interactivity in Educational Apps for Young Children: A Multimodal Analysis

Science.gov (United States)

Blitz-Raith, Alexandra H.; Liu, Jianxin

2017-01-01

Interactivity is an important indicator of an educational app's reception. Since most educational apps are multimodal, it justifies a methodological initiative to understand meaningful involvement of multimodality in enacting and even amplifying interactivity in an educational app. Yet research so far has largely concentrated on algorithm…

Multimodal Desktop Interaction: The Face –Object-Gesture–Voice Example

DEFF Research Database (Denmark)

Vidakis, Nikolas; Vlasopoulos, Anastasios; Kounalakis, Tsampikos

2013-01-01

This paper presents a natural user interface system based on multimodal human computer interaction, which operates as an intermediate module between the user and the operating system. The aim of this work is to demonstrate a multimodal system which gives users the ability to interact with desktop...

Applications of Elpasolites as a Multimode Radiation Sensor

Science.gov (United States)

Guckes, Amber

This study consists of both computational and experimental investigations. The computational results enabled detector design selections and confirmed experimental results. The experimental results determined that the CLYC scintillation detector can be applied as a functional and field-deployable multimode radiation sensor. The computational study utilized MCNP6 code to investigate the response of CLYC to various incident radiations and to determine the feasibility of its application as a handheld multimode sensor and as a single-scintillator collimated directional detection system. These simulations include: • Characterization of the response of the CLYC scintillator to gamma-rays and neutrons; • Study of the isotopic enrichment of 7Li versus 6Li in the CLYC for optimal detection of both thermal neutrons and fast neutrons; • Analysis of collimator designs to determine the optimal collimator for the single CLYC sensor directional detection system to assay gamma rays and neutrons; Simulations of a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system with the optimized collimator to determine the feasibility of detecting nuclear materials that could be encountered during field operations. These nuclear materials include depleted uranium, natural uranium, low-enriched uranium, highly-enriched uranium, reactor-grade plutonium, and weapons-grade plutonium. The experimental study includes the design, construction, and testing of both a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system. Both were designed in the Inventor CAD software and based on results of the computational study to optimize its performance. The handheld CLYC multimode sensor is modular, scalable, low?power, and optimized for high count rates. Commercial?off?the?shelf components were used where possible in order to optimize size, increase robustness, and minimize cost. The handheld CLYC multimode

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

Science.gov (United States)

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

Research on Congestion Pricing in Multimode Traffic considering Delay and Emission

Directory of Open Access Journals (Sweden)

Hongna Dai

2015-01-01

Full Text Available Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.

Heuristic method for searching global maximum of multimodal unknown function

Energy Technology Data Exchange (ETDEWEB)

Kamei, K; Araki, Y; Inoue, K

1983-06-01

The method is composed of three kinds of searches. They are called g (grasping)-mode search, f (finding)-mode search and c (confirming)-mode search. In the g-mode search and the c-mode search, a heuristic method is used which was extracted from search behaviors of human subjects. In f-mode search, the simplex method is used which is well known as a search method for unimodal unknown function. Each mode search and its transitions are shown in the form of flowchart. The numerical results for one-dimensional through six-dimensional multimodal functions prove the proposed search method to be an effective one. 11 references.

Osteoesclerosant axial. Proposal for a new diagnostic approach

International Nuclear Information System (INIS)

Toro, Carlos Enrique; Quintana Duque, Mario Andres; Restrepo, Jose Felix; Quintana, Gerardo; Rondon, Federico; Sanchez, Alvaro; Cons Molina, Fidencio; Gamarra, Antonio Iglesias

2007-01-01

Osteosclerosant diseases with axial involvement are a rare group of disorders characterized by a high bone mineral density secondary to impairment in the endochondral and membranous bone formation process. In this article we analyzed the current classification of these diseases and propose a new and simple approach. In addition, we describe the main radiologic, laboratory and clinical keys to arrive to the differential diagnosis

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

Science.gov (United States)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.

Science.gov (United States)

Triantafyllopoulos, Dimitrios; Korvesis, Panagiotis; Mporas, Iosif; Megalooikonomou, Vasileios

2016-03-01

New generation of healthcare is represented by wearable health monitoring systems, which provide real-time monitoring of patient's physiological parameters. It is expected that continuous ambulatory monitoring of vital signals will improve treatment of patients and enable proactive personal health management. In this paper, we present the implementation of a multimodal real-time system for epilepsy management. The proposed methodology is based on a data streaming architecture and efficient management of a big flow of physiological parameters. The performance of this architecture is examined for varying spatial resolution of the recorded data.

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

Science.gov (United States)

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…

Multimodal Strategies of Theorization

DEFF Research Database (Denmark)

Cartel, Melodie; Colombero, Sylvain; Boxenbaum, Eva

This paper examines the role of multimodal strategies in processes of theorization. Empirically, we investigate the theorization process of a highly disruptive innovation in the history of architecture: reinforced concrete. Relying on archival data from a dominant French architectural journal from...... with well-known rhetorical strategies and develop a process model of theorization....

Multimodal treatment for unresectable pancreatic cancer

International Nuclear Information System (INIS)

Katayama, Kanji; Iida, Atsushi; Fujita, Takashi; Kobayashi, Taizo; Shinmoto, Syuichi; Hirose, Kazuo; Yamaguchi, Akio; Yoshida, Masanori

1998-01-01

In order to improve in prognosis and quality of life (QOL), the multimodal treatment for unresectable pancreatic cancers were performed. Bypass surgery was carried out for unresectable pancreatic cancer with intraoperative irradiation (IOR). After surgery, patients were treated with the combination of CDDP (25 mg) and MMC (4 mg) administration, intravenously continuous injection of 5-FU (250 mg for 24 hours), external radiation by the high voltage X-ray (1.5 Gy per irradiation, 4 times a week, and during hyperthermia 3 Gy per irradiation) and hyperthermia using the Thermotron RF-8 warmer. Six out of 13 patients received hyperthermia at over 40degC, were obtained PR, and their survival periods were 22, 21, 19, 18, 11 and 8 months and they could return to work. For all patients with pain, the symptom was abolished or reduced. The survival periods in cases of the multimodal treatment were longer than those of only bypass-surgery or of the resective cases with the curability C. The multimodal treatment combined with radiation, hyperthermia and surgery is more useful for the removal of pain and the improvement of QOL, and also expected the improvement of the prognosis than pancreatectomy. And hyperthermia has an important role on the effect of this treatment. (K.H.)

Multimodal treatment for unresectable pancreatic cancer

Energy Technology Data Exchange (ETDEWEB)

Katayama, Kanji; Iida, Atsushi; Fujita, Takashi; Kobayashi, Taizo; Shinmoto, Syuichi; Hirose, Kazuo; Yamaguchi, Akio; Yoshida, Masanori [Fukui Medical School, Matsuoka (Japan)

1998-07-01

In order to improve in prognosis and quality of life (QOL), the multimodal treatment for unresectable pancreatic cancers were performed. Bypass surgery was carried out for unresectable pancreatic cancer with intraoperative irradiation (IOR). After surgery, patients were treated with the combination of CDDP (25 mg) and MMC (4 mg) administration, intravenously continuous injection of 5-FU (250 mg for 24 hours), external radiation by the high voltage X-ray (1.5 Gy per irradiation, 4 times a week, and during hyperthermia 3 Gy per irradiation) and hyperthermia using the Thermotron RF-8 warmer. Six out of 13 patients received hyperthermia at over 40degC, were obtained PR, and their survival periods were 22, 21, 19, 18, 11 and 8 months and they could return to work. For all patients with pain, the symptom was abolished or reduced. The survival periods in cases of the multimodal treatment were longer than those of only bypass-surgery or of the resective cases with the curability C. The multimodal treatment combined with radiation, hyperthermia and surgery is more useful for the removal of pain and the improvement of QOL, and also expected the improvement of the prognosis than pancreatectomy. And hyperthermia has an important role on the effect of this treatment. (K.H.)

Multimodal Semantics Extraction from User-Generated Videos

Directory of Open Access Journals (Sweden)

Francesco Cricri

2012-01-01

Full Text Available User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium, genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

Multimodal Hierarchical Dirichlet Process-Based Active Perception by a Robot

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Tadahiro Taniguchi

2018-05-01

Full Text Available 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

Outcomes of a multimodal cognitive and physical rehabilitation program for persons with mild dementia and their caregivers: a goal-oriented approach

Directory of Open Access Journals (Sweden)

Chew J

2015-10-01

Full Text Available Justin Chew, Mei-Sian Chong, Yoke-Leng Fong, Laura Tay Department of Geriatric Medicine, Institute of Geriatrics and Active Ageing, Tan Tock Seng Hospital, Singapore, Singapore Background: Nonpharmacological interventions such as exercise and cognitive rehabilitation programs have shown promise in reducing the impact of dementia on the individual and the caregiver. In this study, we examine the effect of a multimodal cognitive and physical rehabilitation program for persons with mild dementia and their caregivers using conventional measures of cognition, behavior, quality of life (QoL, and caregiver burden together with goal attainment scaling (GAS, an individualized outcome measure.Methods: Goals were set at baseline, and GAS score was calculated at the end of the program. Participants were also assessed with the Chinese Mini-Mental State Examination, functional and behavioral scales (Barthel Index, Instrumental Activities of Daily Living, Neuropsychiatric Inventory Questionnaire, QoL, and caregiver burden using EuroQol-five dimension questionnaire and Zarit Burden Interview (ZBI. Differences in median scores postintervention were obtained. Further analysis of caregiver burden was undertaken utilizing the multidimensional classification of burden on the ZBI.Results: Thirty-four (61.8% patients were assessed to have met their goals (GAS score ≥50. Mean (standard deviation GAS score was 48.6 (6.5. Cognition goals were set in only 20.6%, followed by goals to improve engagement and socialization; reduce caregiver stress; and improve physical function, behavior, and mood. Median scores in the cognitive, functional, and QoL measures did not differ significantly pre- and postintervention. The intervention had a positive impact on role strain, a unique dimension of caregiver burden.Conclusion: This study provides evidence that a multimodal approach combining physical exercise and cognitive rehabilitation improves goal attainment and caregiver burden

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

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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 (pusers.

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

Science.gov (United States)

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.

A multimodal image sensor system for identifying water stress in grapevines

Science.gov (United States)

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.

Cultural Shifts, Multimodal Representations, and Assessment Practices: A Case Study

Science.gov (United States)

Curwood, Jen Scott

2012-01-01

Multimodal texts involve the presence, absence, and co-occurrence of alphabetic text with visual, audio, tactile, gestural, and spatial representations. This article explores how teachers' evaluation of students' multimodal work can be understood in terms of cognition and culture. When teachers apply a paradigm of assessment rooted in print-based…

Retwitting, Reposting, Repinning; Reshaping Identities Online: Towards a Social Semiotic Multimodal Analysis of Digital Remediation

Directory of Open Access Journals (Sweden)

Elisabetta Adami

2014-12-01

Full Text Available The paper focuses on crossposting, as a form of digital remediation consisting in the production and distribution of multimodal texts in multiple online spaces through embedding and sharing. The study sketches the analytical steps to approach the phenomenon, applying them on a UK food blogger’s activity spanning her blog, her Facebook, Twitter, YouTube, Pinterest, and Instagram accounts. In the instance examined, recontextualized texts are re-genred; genre assignment is given by the combination of the multimodal configuration in each space and the blogger’s use of these affordances to her aims. Through minimum new text creation, by recontextualizing her texts in different spaces, the blogger can shape differently her relation with the audience. The analytical framework is intended as a flexible tool that, adjusted as appropriate, can be used for a broader in-depth analysis of crossposting.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

Science.gov (United States)

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.

Proposed quantitative approach to safety for nuclear power plants in Canada

International Nuclear Information System (INIS)

1995-07-01

A set of quantitative risk and frequency limits plus required processes is proposed to help ensure that a nuclear power plant in Canada meets the qualitative safety objectives defined in ACNS-2 and in IAEA 75-INSAG-3. As emphasized in this report, risks and hence doses are to be reduced below the limits using ALARA (As Low as Reasonably Achievable, economic and social factors being taken into account) or VIA (value-impact analysis) processes unless, in general, calculated risks and hence doses are below recommended de minimis levels. An updated version of ACNS-4, which will be issued as ACNS-21, will incorporate a statement of these limits and objectives as well as assessment criteria and procedures that will facilitate their application. The quantitative approach proposed here is consistent with a growing consensus on the need for, and the elements of, a quantitative approach to risk management of all major activities in an advanced industrial society. The ACNS recommends that the Atomic Energy Control Board adopt the proposed approach as a rational and coherent basis for nuclear power plant safety policy and requirements in Canada. (author). 68 refs., 4 tabs., 1 fig

Proposed quantitative approach to safety for nuclear power plants in Canada

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-07-01

A set of quantitative risk and frequency limits plus required processes is proposed to help ensure that a nuclear power plant in Canada meets the qualitative safety objectives defined in ACNS-2 and in IAEA 75-INSAG-3. As emphasized in this report, risks and hence doses are to be reduced below the limits using ALARA (As Low as Reasonably Achievable, economic and social factors being taken into account) or VIA (value-impact analysis) processes unless, in general, calculated risks and hence doses are below recommended de minimis levels. An updated version of ACNS-4, which will be issued as ACNS-21, will incorporate a statement of these limits and objectives as well as assessment criteria and procedures that will facilitate their application. The quantitative approach proposed here is consistent with a growing consensus on the need for, and the elements of, a quantitative approach to risk management of all major activities in an advanced industrial society. The ACNS recommends that the Atomic Energy Control Board adopt the proposed approach as a rational and coherent basis for nuclear power plant safety policy and requirements in Canada. (author). 68 refs., 4 tabs., 1 fig.

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

Science.gov (United States)

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…

Decision Support for Planning of Multimodal Transportation with Multiple Objectives

DEFF Research Database (Denmark)

Petersen, Hanne Løhmann

phase, and considers passenger inconvenience at transfers at the same time. The paper presents a mathematical model of the problem, and the implementation of a large neighbourhood search solution procedure. The problem is solved for a real-life based problem instance, containing eight bus lines......-known issues. They both originate in the world of multimodality, and deal with problems that arise as a consequence of the combined use of several modes. The thesis introduces the Double Travelling Salesman Problem with Multiple Stacks (DTSPMS), which is a problem that combines routing and last...... compare to solutions of the regular Travelling Salesman Problem. Next, two papers are presented, introducing respectively heuristic and exact solution procedures for the problem. The heuristic approach tests a variety of metaheuristic solution approaches, of which a large neighbourhood search obtains...

Multimodal and synthetic aperture approach to full-field 3D shape and displacement measurements