Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67\% accuracy and 96.02\% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.Comment: 9 pages, 4 figures, Accepted by Scientific Report

Understanding the cost of green buildings : Evidence from Singapore

Master'sMASTER OF SCIENCE (ESTATE MANAGEMENT

Analysis of Urban Impervious Surface in Coastal Cities: A Case Study in Lianyungang, China

Impervious surface is an important indicator of the level of urbanization. It is of great significance to study the impervious surface to promote the sustainable development of the city. In the process of urban development, the increase of impervious surface cities is bound to be accompanied by a reduction of one or more types of land use in the city. This paper, taking Lianyungang as an example, introduces the methods of extracting urban impervious surface based on VIS model, NDVI (normalized vegetation index), MNDWI (modified normalized water body index), and unsupervised classification, analyzes the changes of impervious surface in Lianyungang from 1987 to 2014, and on this basis, analyzes the trend and driving forces of land use types in Lianyungang city in depth. The results show that the impervious surface of Lianyungang increased by a total of 29.70% between 1987 and 2014. While the impervious surface continues to increase, the area of cultivated land and coastal areas (including salt works and tidal flats) has been greatly reduced, and the types of land use have undergone significant changes

Cavity-enhanced single photon emission from a single impurity-bound exciton

Impurity-bound excitons in ZnSe quantum wells are bright single photon emitters--a crucial element in photonics-based quantum technology. But to achieve the efficiencies required for practical applications, these emitters must be integrated into optical cavities that enhance their radiative properties and far-field emission pattern. In this work, we demonstrate cavity-enhanced emission from a single impurity-bound exciton in a ZnSe quantum well. We utilize a bullseye cavity structure optimized to feature a small mode volume and a nearly Gaussian far-field transverse mode that can efficiently couple to an optical fiber. The fabricated device displays emission that is more than an order of magnitude brighter than bulk impurity-bound exciton emitters in the ZnSe quantum well, as-well-as clear anti-bunching, which verifies the single photon emission from the source. Time-resolved photoluminescence spectroscopy reveals a Purcell-enhanced radiative decay process with a Purcell factor of 1.43. This work paves the way towards high efficiency spin-photon interfaces using an impurity-doped II-VI semiconductor coupled to nanophotonics

Fault Injection based Failure Analysis of three CentOS-like Operating Systems

The reliability of operating system (OS) has always been a major concern in the academia and industry. This paper studies how to perform OS failure analysis by fault injection based on the fault mode library. Firstly, we use the fault mode generation method based on Linux abstract hierarchy structure analysis to systematically define the Linux-like fault modes, construct a Linux fault mode library and develop a fault injection tool based on the fault mode library (FIFML). Then, fault injection experiments are carried out on three commercial Linux distributions, CentOS, Anolis OS and openEuler, to identify their reliability problems and give improvement suggestions. We also use the virtual file systems of these three OSs as experimental objects, to perform fault injection at levels of Light and Normal, measure the performance of 13 common file operations before and after fault injection.Comment: 9 pages, 8 figure

Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation

Unsupervised Domain Adaptation (UDA) aims to adapt the model trained on the labeled source domain to an unlabeled target domain. In this paper, we present Prototypical Contrast Adaptation (ProCA), a simple and efficient contrastive learning method for unsupervised domain adaptive semantic segmentation. Previous domain adaptation methods merely consider the alignment of the intra-class representational distributions across various domains, while the inter-class structural relationship is insufficiently explored, resulting in the aligned representations on the target domain might not be as easily discriminated as done on the source domain anymore. Instead, ProCA incorporates inter-class information into class-wise prototypes, and adopts the class-centered distribution alignment for adaptation. By considering the same class prototypes as positives and other class prototypes as negatives to achieve class-centered distribution alignment, ProCA achieves state-of-the-art performance on classical domain adaptation tasks, {\em i.e., GTA5 $\to$ Cityscapes \text{and} SYNTHIA $\to$ Cityscapes}. Code is available at \href{https://github.com/jiangzhengkai/ProCA}{ProCA

Review on the research of hydrogen storage system fast refueling in fuel cell vehicle: Review

International audienceA comprehensive review of the hydrogen storage systems and investigations performed in search for development of fast refueling technology for fuel cell vehicles are presented. Nowadays, hydrogen is considered as a good and promising energy carrier and can be stored in gaseous, liquid or solid state. Among the three ways, high pressure (such as 35 MPa or 70 MPa) appears to be the most suitable method for transportation due to its technical simplicity, high reliability, high energy efficiency and affordability. However, the refueling of high pressure hydrogen can cause a rapid increase of inner temperature of the storage cylinder, which may result not only in a decrease of the state of charge (SOC) but also in damages to the tank walls and finally to safety problems. In this paper, the theoretical analysis, experiments and simulations on the factors related to the fast refueling, such as initial pressure, initial temperature, filling rate and ambient temperature, are reviewed and analyzed. Understanding the potential relationships between these parameters and the temperature rise may shed a light in developing novel controlling strategies and innovative routes for hydrogen tank fast filling

A case report of multicentric reticulohistiocytosis with atypical cutaneous presentation

Multicentric reticulohistiocytosis (MRH) is a rare systemic disorder characterized by histiocytic hyperplasia that mainly involves the skin, mucous membranes, and joints. The typical clinical features include papules, nodules, and arthritis. MRH lesions are relatively extensive but small and scattered. Joint inflammation is characterized by diffuse symmetric polyarthritis as the first symptom, which can be severe and disabling due to destructive joint changes. MRH is easily misdiagnosed in clinical practice. Here, we report the case of an elderly male patient who presented with polyarticular pain in the hip and interphalangeal joints as the first manifestation, followed by the development of large, isolated, bulging skin nodules, which are atypical MRH lesions. This is rare in all MRH case reports, and we made the correct diagnosis by combining skin histopathology, immunohistochemistry, and other clinical examinations. We performed surgical treatment on the local skin lesions of this patient. This case suggests that clinicians should actively correlate the condition and accurately diagnose MRH when encountering atypical skin changes or other diseases as the first symptom and explore the mechanisms of MRH and other clinical manifestations