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Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA recognition

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Computers, Materials & Continua 2019年第3期58卷 665-677页

作者： Wentao Ma Jiaohua Qin Xuyu Xiang Yun Tan Yuanjing Luo neal NXiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410114China Department of Mathematics and Computer Science Northeastern State UniversityOklahoma74464USA.

As the first barrier to protect cyberspace,the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious *** researching the CAPTCHA,we can find its vulnerability and improve the security of ***,many studies have shown that improving the image preprocessing effect of the CAPTCHA,which can achieve a better recognition rate by the state-of-theart machine learning *** are many kinds of noise and distortion in the CAPTCHA images of this *** propose an adaptive median filtering algorithm based on divide and conquer in this ***,the filtering window data quickly sorted by the data correlation,which can greatly improve the filtering ***,the size of the filtering window is adaptively adjusted according to the noise *** demonstrated in the experimental results,the proposed scheme can achieve superior performance compared with the conventional median *** algorithm can not only effectively detect the noise and remove it,but also has a good effect in preservation ***,this algorithm can be one of the most strong tools for various CAPTCHA image recognition and related applications.

关键词： Image preprocessing machine learning CAPTCHA recognition adaptive median filtering algorithm.

Privacy Protection for Medical Images Based on DenseNet and Coverless Steganography

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Computers, Materials & Continua 2020年第9期64卷 1797-1817页

作者： Yun Tan Jiaohua Qin Hao Tang Xuyu Xiang Ling Tan neal NXiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410114China The Second Xiangya Hospital of Central South University Changsha410011China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA

With the development of the internet of medical things(IoMT),the privacy protection problem has become more and more *** this paper,we propose a privacy protection scheme for medical images based on DenseNet and coverless *** a given group of medical images of one patient,DenseNet is used to regroup the images based on feature similarity *** the mapping indexes can be constructed based on LBP feature and hash *** mapping the privacy information with the hash sequences,the corresponding mapped indexes of secret information will be packed together with the medical images group and released to the authorized *** user can extract the privacy information successfully with a similar method of feature analysis and index *** simulation results show good performance of *** the hiding success rate also shows good feasibility and practicability for *** the medical images are kept original without embedding and modification,the performance of crack resistance is outstanding and can keep better quality for diagnosis compared with traditional schemes with data embedding.

关键词： Privacy protection medical image coverless steganography DenseNet LBP

Low-carbon city communication:Integrated strategies for urban and rural municipalities in Thailand

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Chinese Journal of Population,resources and Environment 2020年第1期18卷 16-25页

作者： Sukanya Sereenonchai Noppol Arunrat Thomas neal Stewart Faculty of Environment and resource Studies Mahidol UniversitySalayaNakhon Pathom73170Thailand

As an important sustainable development goal,the creation of low-carbon cities(LCCs)has become crucial to creating livable cities and environmental ***,we aimed to understand the factors that support the transition of traditional cities to LCCs,by analyzing and synthesizing how to promote practical LCC across 15 pilot municipalities in four regions of Thailand,covering four strategies:City of Trees,City of Waste Minimization,City of Energy Efficiency,and City of Sustainable *** research,in-depth interviews,and observations were employed for data collection,while the 5W(who,says what,in which channel,to whom,and with what effect)and SMCr(sender,message,channel,and receiver)models were used to create a communication analysis *** revealed that the effective activities of municipalities should increase tree planting and implement more serious regulations for the conservation of existing *** compost and establishing waste recycling banks are recommended for rural municipalities,while optimization of garbage and wastewater management systems and facilities should be highlighted in urban ***,recycling,low-carbon agriculture,second-hand shops/markets,green markets,and homegrown vegetables should be encouraged for sustainable *** with local municipalities,credible leaders and representatives were the key ***,message design should compare the pros and cons of behaviors,connect with local health and tourism,and promote dialogue in easy-to-understand and thought-provoking *** that drive LCC should have an excellent understanding of LCC practice and its benefits,be public-minded,and have a desire to live in a good environment.

关键词： Low-carbon city Low-carbon communication Integrated strategies Urban and rural municipalities Thailand

Associative learning mechanism for drug‐target interaction prediction

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1558-1577页

作者： Zhiqin Zhu Zheng Yao Guanqiu Qi neal Mazur Pan Yang Baisen Cong College of Automation Chongqing University of Posts and TelecommunicationsChongqingChina Computer Information Systems Department State University of New York at Buffalo StateBuffaloNew YorkUSA Department of Cardiovascular Surgery Chongqing General HospitalUniversity of Chinese Academy of SciencesChongqingChina Emergency Department The Second Affiliated Hospital of Chongqing Medical UniversityChongqingChina Data Scientist Diagnostics Digital DH(Shanghai)Diagnostics Co.Ltd.Danaher CompanyShanghaiChina

As a necessary process of modern drug development,finding a drug compound that can selectively bind to a specific protein is highly challenging and *** drug‐target interaction strength in terms of drug‐target affinity(DTA)is an emerging and effective research approach for drug ***,it is challenging to model drug‐target interactions in a deep learning manner,and few studies provide interpretable analysis of *** paper proposes a DTA prediction method(mutual transformer‐drug target affinity[MT‐DTA])with interactive learning and an autoencoder *** proposed MT‐DTA builds a variational autoencoders system with a cascade structure of the attention model and convolutional neural *** not only enhances the ability to capture the characteristic information of a single molecular sequence but also establishes the characteristic expression relationship for each substructure in a single molecular *** this basis,a molecular information interaction module is constructed,which adds information interaction paths between molecular sequence pairs and complements the expression of correlations between molecular *** performance of the proposed model was verified on two public benchmark datasets,KIBA and Davis,and the results confirm that the proposed model structure is effective in predicting ***,attention transformer models with different configurations can improve the feature expression of drug/protein *** model performs better in correctly predicting interaction strengths compared with state‐of‐the‐art *** addition,the diversity of drug/protein molecules can be better expressed than existing methods such as SeqGAN and Co‐VAE to generate more effective new *** DTA value prediction module fuses the drug‐target pair interaction information to output the predicted value of ***,this paper theoretically proves that the proposed method maximises evidence lower bound

关键词： deep learning medical applications

Criss-Cross Attentional Siamese Networks for Object Tracking

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Computers, Materials & Continua 2022年第11期73卷 2931-2946页

作者： Zhangdong Wang Jiaohua Qin Xuyu Xiang Yun Tan neal N.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Visual object tracking is a hot topic in recent *** the meanwhile,Siamese networks have attracted extensive attention in this field because of its balanced precision and ***,most of the Siamese network methods can only distinguish foreground from the non-semantic *** fine-tuning and retraining of fully-convolutional Siamese networks for object tracking(SiamFC)can achieve higher precision under interferences,but the tracking accuracy is still not ideal,especially in the environment with more target interferences,dim light,and *** this paper,we propose crisscross attentional Siamese networks for object tracking(SiamCC).To solve the imbalance between foreground and non-semantic background,we use the feature enhancement module of criss-cross attention to greatly improve the accuracy of video object tracking in dim light and shadow *** results show that the maximum running speed of SiamCC in the object tracking benchmark dataset is 90 frames/*** terms of detection accuracy,the accuracy of shadow sequences is greatly improved,especially the accuracy score of sequence HUMAN8 is improved from 0.09 to 0.89 compared with the original SiamFC,and the success rate score is improved from 0.07 to 0.55.

关键词： Criss-cross attention object-tracking siamese-network

Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

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Computers, Materials & Continua 2023年第4期75卷 1447-1465页

作者： Debnath Bhattacharyya EaliStephen neal Joshua N.Thirupathi rao Yung-cheol Byun Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGuntur522302Andhra PradeshIndia Department of Computer Science&Engineering Vignan’s Institute of Information Technology(A)Visakhapatnam530049Andhra PradeshIndia Department of Computer Engineering Jeju National University102 Jejudaehak-roJeju-siJeju-do690-756Korea

Lung cancer is the leading cause of mortality in the world affectingboth men and women *** a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are *** of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one *** the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most *** employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.

关键词： Magnetic resonance imaging(MrI) lung cancer Luna-16 logistic distribution segmentation deep learning juxta plural pulmonary nodules

Coverless Image Steganography Based on Image Segmentation

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Computers, Materials & Continua 2020年第8期64卷 1281-1295页

作者： Yuanjing Luo Jiaohua Qin Xuyu Xiang Yun Tan Zhibin He neal NXiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410114China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA

To resist the risk of the stego-image being maliciously altered during transmission,we propose a coverless image steganography method based on image *** existing coverless steganography methods are based on whole feature mapping,which has poor robustness when facing geometric attacks,because the contents in the image are easy to *** solve this problem,we use resNet to extract semantic features,and segment the object areas from the image through Mask rCNN for information *** selected object areas have ethical structural integrity and are not located in the visual center of the image,reducing the information loss of malicious ***,these object areas will be binarized to generate hash sequences for information *** transmission,only a set of stego-images unrelated to the secret information are transmitted,so it can fundamentally resist *** the same time,since both Mask rCNN and resNet have excellent robustness,pre-training the model through supervised learning can achieve good *** robust hash algorithm can also resist attacks during *** image segmentation will reduce the capacity,multiple object areas can be extracted from an image to ensure the capacity to a certain *** results show that compared with other coverless image steganography methods,our method is more robust when facing geometric attacks.

关键词： Coverless steganography semantic feature image segmentation Mask rCNN resNet

Cardiovascular Care for Older Adults Aortic valve disease in the older adult

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Journal of Geriatric Cardiology 2016年第12期13卷 941-944页

作者： neal Bhatia Sukhdeep S Basra Adam H Skolnick Nanette K Wenger Emory University School of Medicine Atlanta GA USA The Heart Hospital Baylor Piano Dallas TX USA Leon H Charney Division of Cardiology New York University Langone Medical Center NY USA

As the population continues to age, aortic stenosis re- mains as the most prevalent valvular disease in Western countries. The number of elderly patients with aortic ste- nosis continues to pose both a diagnostic and therapeutic challenge. Despite new advances such as transcatheter aortic valvular replacement （TAVr）, there is still much pa- tient-provider decision making that needs to take place giv- en the comorbidities and complex goals of care in an elderly patient population.

关键词： Aortic stenosis The elderly Valve disease

AF-Net:A Medical Image Segmentation Network Based on Attention Mechanism and Feature Fusion

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Computers, Materials & Continua 2021年第11期69卷 1877-1891页

作者： Guimin Hou Jiaohua Qin Xuyu Xiang Yun Tan neal N.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Medical image segmentation is an important application field of computer vision in medical image *** to the close location and high similarity of different organs in medical images,the current segmentation algorithms have problems with mis-segmentation and poor edge *** address these challenges,we propose a medical image segmentation network(AF-Net)based on attention mechanism and feature fusion,which can effectively capture global information while focusing the network on the object *** this approach,we add dual attention blocks(DA-block)to the backbone network,which comprises parallel channels and spatial attention branches,to adaptively calibrate and weigh ***,the multi-scale feature fusion block(MFF-block)is proposed to obtain feature maps of different receptive domains and get multi-scale information with less computational ***,to restore the locations and shapes of organs,we adopt the global feature fusion blocks(GFF-block)to fuse high-level and low-level information,which can obtain accurate pixel *** evaluate our method on multiple datasets(the aorta and lungs dataset),and the experimental results achieve 94.0%in mIoU and 96.3%in DICE,showing that our approach performs better than U-Net and other state-of-art methods.

关键词： Deep learning medical image segmentation feature fusion attention mechanism