Traditional handwriting recognition algorithms rely heavily on small lexicons and clean word images. Unfortunately, emergency medical documents do not satisfy either of these conditions. this is a significant road-blo...
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ISBN:
(纸本)0769524206
Traditional handwriting recognition algorithms rely heavily on small lexicons and clean word images. Unfortunately, emergency medical documents do not satisfy either of these conditions. this is a significant road-block that is hampering efforts to rapidly convert valuable offline healthcare handwriting data into digital content that can be efficiently mined for information. this paper describes a strategy whereby given an image representing a noisy handwritten word from a medical document, and a large lexicon consisting of English, medical and pharmacological words, symbols, abbreviations and acronyms, significantly reduces the size of the lexicon while keeping the unknown desired entry within the lexicon. the approach combines geometric interpretations Of the word image along with contextual inference of concepts to reduce lexicons for word recognition. the data extracted can then be efficiently and securely disseminated for epidemiological and outbreak detection/analysis. Experimental results on NY State PCR forms are reported.
Wearable-sensor-based Human Activity recognition (HAR) has long been a hot topic in ubiquitous computing, which is benefit by the success of deep learning algorithms. the critical difficulties in multimodal sensing en...
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ISBN:
(数字)9781665490627
ISBN:
(纸本)9781665490627
Wearable-sensor-based Human Activity recognition (HAR) has long been a hot topic in ubiquitous computing, which is benefit by the success of deep learning algorithms. the critical difficulties in multimodal sensing environments are how to represent the spatial-temporal dependencies while concurrently extracting features with high characterization. In this work, we propose a self-attention based deep dilated convolution network. Our method uses two channels, named temporal channel and spatial channel, respectively, to extract the readings-over-time and time-over-readings features from sensor signals. the self-attention mechanism helps directly capture the long time dependence of sensor signals. To extract local features while expanding the receptive field and avoiding information loss caused by pooling and upsampling, we use deep dilated convolution, which expanding the receptive field and avoiding information loss caused by pooling and upsampling. Extensive experiments on a self-built dataset and two available benchmark datasets (PAMAP2, OPPORTUNITY) reveal that the effectiveness of our proposed model is more competitive than the state-of-the-art methods in HAR tasks.
Computational thinking(CT) has been considered as a problem solving approach that involving fundamental thinking processes which include decomposition,patternrecognition,abstraction,and *** see that CT would be of us...
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ISBN:
(纸本)9781450361040
Computational thinking(CT) has been considered as a problem solving approach that involving fundamental thinking processes which include decomposition,patternrecognition,abstraction,and *** see that CT would be of useful to solve complex problems of user interface design(UID),this study aims to see the extent the CT framework would have an effect on the achievement of designs thinking *** study was carried out based on the evaluation of user interface design projects accomplished by undergraduate students involving 3 cohorts composed of 21 groups in *** results indicate that disregarding CT process in design thinking leads to inefficiency interface design.
this paper examines the human expressive states dependent on facial pictures utilizing a few viable component extraction methods. It reproduces the K-Nearest Neighbor (k-NN) classifier to approve the adequacy of succe...
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this paper formulates a pattern search method for nonlinear programming. A distributed parallel algorithm is given based on the pattern search method by distributing the direction to every processor. Promising experim...
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the Modern decade of future Internet stepping into all the technologies includes sensors, artificial intelligence, patternrecognition and machine learning. As sensor technology increases its liabilities by extending ...
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ISBN:
(纸本)9781509066216
the Modern decade of future Internet stepping into all the technologies includes sensors, artificial intelligence, patternrecognition and machine learning. As sensor technology increases its liabilities by extending to novel recognition methods for identifying an individual. Smell print is a state-of-art technique to perform authentication, verification and validation of a person to apply in fields of human tracking, criminal investigation and canine training etc. this paper describes the compounds combination of human odor, the factors that influence the human odor and sources of smell print in a human body. It gives a prototype for Cogno-detective system for the human odor in order to imitate the human olfaction and procedure to implement the artificial olfaction mechanism.
the system which is based on the Internet of things technology, the data is mostly transmitted to the cloud for processing, which reduces the real-time performance of the system, increases the burden of the cloud comp...
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ISBN:
(纸本)9781538681787
the system which is based on the Internet of things technology, the data is mostly transmitted to the cloud for processing, which reduces the real-time performance of the system, increases the burden of the cloud computing center. Withthe increases of number of intelligent devices, and the rapid growth of data also gives the network bandwidth stress. In view of the above problems, this paper proposes a method of applying edge computing [1 similar to 2] to the Internet of things. the main idea is to use the characteristics of the edge nodes closer to the data source in the monitoring of the farm house environment system which is based on the Internet of things technology. the processing is done on the edge nodes. After experimentation, the data can be processed in real time, reducing the burden on the cloud computing center.
this book constitutes the refereed proceedings of the 8thinternational Workshop on Artificial Intelligence and patternrecognition, IWAIPR 2023, held in Varadero, Cuba, in October 2023.;the 68 papers presented in the...
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ISBN:
(数字)9783031495526
ISBN:
(纸本)9783031495519
this book constitutes the refereed proceedings of the 8thinternational Workshop on Artificial Intelligence and patternrecognition, IWAIPR 2023, held in Varadero, Cuba, in October 2023.;the 68 papers presented in the proceedings set were carefully reviewed and selected from 38 submissions.;the IWAIPR conference aims to provide a leading international forum to promote and disseminate ongoing research into mathematical methods of computing techniques for Artifical Intelligence and patternrecognition.
the proceedings contain 101 papers. the topics discussed include: an efficient and modified median root prior based framework for PET/SPECT reconstruction algorithm;frequent block access pattern-based replication algo...
ISBN:
(纸本)9781467379489
the proceedings contain 101 papers. the topics discussed include: an efficient and modified median root prior based framework for PET/SPECT reconstruction algorithm;frequent block access pattern-based replication algorithm for cloud storage systems;gray scale image watermarking using fuzzy entropy and Lagrangian twin SVR in DCT domain;task behaviour inputs to a heterogeneous multiprocessor scheduler;online anomaly detection via class-imbalance learning;extracting academic social networks among conference participants;automatic classification of frogs calls based on fusion of features and SVM;an efficient DCT based image watermarking scheme for protecting distribution rights;an image processing based method to identify and grade conjunctivitis infected eye according to its types and intensity;dimension reduction using spectral methods in fanny for fuzzy clustering of graphs;and hand written digit recognition system for South Indian languages using artificial neural networks.
Today, wireless access networks are moving from traditional architectures to centralized cellular architectures based on general-purpose computing platforms. the centralized cellular network architecture provides comp...
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ISBN:
(纸本)9781538681787
Today, wireless access networks are moving from traditional architectures to centralized cellular architectures based on general-purpose computing platforms. the centralized cellular network architecture provides computing resource requirements for mobile user services through centralized deployment of computing resource pools. the allocation of centralized computing resources directly determines the efficiency of system computing resources and the energy efficiency of the system. In this paper, the relationship between computing resources and communication bandwidth of centralized base station pool based on the general computing platform is analyzed. Based on this, a computing resource allocation model is established, an allocation algorithm based on service load balancing is proposed for this model. the simulation results show that the algorithm can effectively reduce the number of allocations of computing units, improve the utilization of computing resources, and achieve the goal of green energy conservation.
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