The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the in...
详细信息
With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of ever...
详细信息
With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.
Semantic transfer is an important problem of the language understanding (LU), which is about how the recognition pattern of a semantic concept benefits other associated concepts. In this paper, we propose a new semant...
详细信息
Recently long short-term memory language model(LSTMLM)has received tremendous interests from both language and speech communities,due to its superiorty on modelling long-term ***,integrating auxiliary information,such...
详细信息
ISBN:
(纸本)9783319690049
Recently long short-term memory language model(LSTMLM)has received tremendous interests from both language and speech communities,due to its superiorty on modelling long-term ***,integrating auxiliary information,such as context feature,into the LSTM LM has shown improved performance in perplexity(PPL).However,improper feed of auxiliary information won't give consistent gain on word error rate(WER)in a large vocabulary continuous speech recognition(LVCSR)*** solve this problem,a multi-view LSTM LM architecture combining a tagging model is proposed in this *** an on-line unidirectional LSTM-RNN is built as a tagging model,which can generate word-synchronized auxiliary *** the auxiliary feature from the tagging model is combined with the word sequence to train a multi-view unidirectional LSTM *** training modes for the tagging model and language model are explored and *** new architecture is evaluated on PTB,Fisher English and SMS Chinese data sets,and the results show that not only LM PPL promotion is observed,but also the improvements can be well transferred to WER reduction in ASR-rescore task.
An ontology is a taxonomic hierarchy of lexical terms and their syntactic and semantic relations for representing a framework of structured knowledge. Ontology used to be problem-specific and manually built due to its...
详细信息
Accurate estimation of spike train from calcium (Ca~(2+)) fluorescence signals is challenging owing to significant fluctuations of fluorescence level. This paper proposes a non-model-based approach for spike train inf...
详细信息
ISBN:
(纸本)9781509041183
Accurate estimation of spike train from calcium (Ca~(2+)) fluorescence signals is challenging owing to significant fluctuations of fluorescence level. This paper proposes a non-model-based approach for spike train inference using group delay (GD) analysis. It primarily exploits the property that change in Ca~(2+) fluorescence corresponding to a spike has a notable onset location followed by a decaying transient. The proposed algorithm, GDspike, is compared with state-of-the-art systems on five datasets. F-measure is best for GDspike (41%) followed by STM (40%), MLspike (39%), and Vogelstein (35%). While existing methods are inspired by the physiology of neuronal responses, the proposed approach is inspired by GD-based high-resolution processing of the Ca~(2+) fluorescence signal. GDspike is a fast and unsupervised algorithm. It is found to be unaffected when tested with five different GCaMP indicators and scanning rate varying from 15Hz to 60Hz.
Smart systems that can accurately diagnose patients with mental disorders and identify effective treatments based on brain functional imaging data are of great applicability and are gaining much attention. Most previo...
详细信息
The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through pe...
The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.
Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack of information provided by current t...
详细信息
暂无评论