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Building Semantic Communication System via Molecules:An End-to-End Training Approach
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作者 Cheng Yukun Chen Wei Ai Bo 《China Communications》 SCIE CSCD 2024年第7期113-124,共12页
The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aim... The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aiming to enhance the efficiency of molecular communication systems by reducing the transmitted information.Specifically,following the joint source channel coding paradigm,the network is designed to encode the task-relevant information into the concentration of the information molecules,which is robust to the degradation of the molecular communication channel.Furthermore,we propose a channel network to enable the E2E learning over the non-differentiable molecular channel.Experimental results demonstrate the superior performance of the semantic molecular communication system over the conventional methods in classification tasks. 展开更多
关键词 deep learning end-to-end learning molecular communication semantic communication
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DTHN: Dual-Transformer Head End-to-End Person Search Network 被引量:1
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作者 Cheng Feng Dezhi Han Chongqing Chen 《Computers, Materials & Continua》 SCIE EI 2023年第10期245-261,共17页
Person search mainly consists of two submissions,namely Person Detection and Person Re-identification(reID).Existing approaches are primarily based on Faster R-CNN and Convolutional Neural Network(CNN)(e.g.,ResNet).Wh... Person search mainly consists of two submissions,namely Person Detection and Person Re-identification(reID).Existing approaches are primarily based on Faster R-CNN and Convolutional Neural Network(CNN)(e.g.,ResNet).While these structures may detect high-quality bounding boxes,they seem to degrade the performance of re-ID.To address this issue,this paper proposes a Dual-Transformer Head Network(DTHN)for end-to-end person search,which contains two independent Transformer heads,a box head for detecting the bounding box and extracting efficient bounding box feature,and a re-ID head for capturing high-quality re-ID features for the re-ID task.Specifically,after the image goes through the ResNet backbone network to extract features,the Region Proposal Network(RPN)proposes possible bounding boxes.The box head then extracts more efficient features within these bounding boxes for detection.Following this,the re-ID head computes the occluded attention of the features in these bounding boxes and distinguishes them from other persons or backgrounds.Extensive experiments on two widely used benchmark datasets,CUHK-SYSU and PRW,achieve state-of-the-art performance levels,94.9 mAP and 95.3 top-1 scores on the CUHK-SYSU dataset,and 51.6 mAP and 87.6 top-1 scores on the PRW dataset,which demonstrates the advantages of this paper’s approach.The efficiency comparison also shows our method is highly efficient in both time and space. 展开更多
关键词 TRANSFORMER occluded attention end-to-end person search person detection person re-ID Dual-Transformer Head
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End-to-End Joint Multi-Object Detection and Tracking for Intelligent Transportation Systems
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作者 Qing Xu Xuewu Lin +6 位作者 Mengchi Cai Yu‑ang Guo Chuang Zhang Kai Li Keqiang Li Jianqiang Wang Dongpu Cao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2023年第5期280-290,共11页
Environment perception is one of the most critical technology of intelligent transportation systems(ITS).Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking(MOT).How... Environment perception is one of the most critical technology of intelligent transportation systems(ITS).Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking(MOT).However,most existing MOT algorithms follow the tracking-by-detection framework,which separates detection and tracking into two independent segments and limit the global efciency.Recently,a few algorithms have combined feature extraction into one network;however,the tracking portion continues to rely on data association,and requires com‑plex post-processing for life cycle management.Those methods do not combine detection and tracking efciently.This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS,named as global correlation network(GCNet).Unlike most object detection methods,GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes,instead of ofsetting predictions.The pipeline of detection and tracking in GCNet is conceptually simple,and does not require compli‑cated tracking strategies such as non-maximum suppression and data association.GCNet was evaluated on a multivehicle tracking dataset,UA-DETRAC,demonstrating promising performance compared to state-of-the-art detectors and trackers. 展开更多
关键词 Intelligent transportation systems Joint detection and tracking Global correlation network end-to-end tracking
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An End-to-End Machine Learning Framework for Predicting Common Geriatric Diseases
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作者 Jian Guo Yu Han +2 位作者 Fan Xu Jiru Deng Zhe Li 《Journal of Beijing Institute of Technology》 EI CAS 2023年第2期209-218,共10页
Interdisciplinary applications between information technology and geriatrics have been accelerated in recent years by the advancement of artificial intelligence,cloud computing,and 5G technology,among others.Meanwhile... Interdisciplinary applications between information technology and geriatrics have been accelerated in recent years by the advancement of artificial intelligence,cloud computing,and 5G technology,among others.Meanwhile,applications developed by using the above technologies make it possible to predict the risk of age-related diseases early,which can give caregivers time to intervene and reduce the risk,potentially improving the health span of the elderly.However,the popularity of these applications is still limited for several reasons.For example,many older people are unable or unwilling to use mobile applications or devices(e.g.smartphones)because they are relatively complex operations or time-consuming for older people.In this work,we design and implement an end-to-end framework and integrate it with the WeChat platform to make it easily accessible to elders.In this work,multifactorial geriatric assessment data can be collected.Then,stacked machine learning models are trained to assess and predict the incidence of common diseases in the elderly.Experimental results show that our framework can not only provide more accurate prediction(precision:0.8713,recall:0.8212)for several common elderly diseases,but also very low timeconsuming(28.6 s)within a workflow compared to some existing similar applications. 展开更多
关键词 predicting geriatric diseases machine learning end-to-end framework
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Attention-based neural network for end-to-end music separation
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作者 Jing Wang Hanyue Liu +3 位作者 Haorong Ying Chuhan Qiu Jingxin Li Muhammad Shahid Anwar 《CAAI Transactions on Intelligence Technology》 SCIE EI 2023年第2期355-363,共9页
The end-to-end separation algorithm with superior performance in the field of speech separation has not been effectively used in music separation.Moreover,since music signals are often dual channel data with a high sa... The end-to-end separation algorithm with superior performance in the field of speech separation has not been effectively used in music separation.Moreover,since music signals are often dual channel data with a high sampling rate,how to model longsequence data and make rational use of the relevant information between channels is also an urgent problem to be solved.In order to solve the above problems,the performance of the end-to-end music separation algorithm is enhanced by improving the network structure.Our main contributions include the following:(1)A more reasonable densely connected U-Net is designed to capture the long-term characteristics of music,such as main melody,tone and so on.(2)On this basis,the multi-head attention and dualpath transformer are introduced in the separation module.Channel attention units are applied recursively on the feature map of each layer of the network,enabling the network to perform long-sequence separation.Experimental results show that after the introduction of the channel attention,the performance of the proposed algorithm has a stable improvement compared with the baseline system.On the MUSDB18 dataset,the average score of the separated audio exceeds that of the current best-performing music separation algorithm based on the time-frequency domain(T-F domain). 展开更多
关键词 channel attention densely connected network end-to-end music separation
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End-to-End Auto-Encoder System for Deep Residual Shrinkage Network for AWGN Channels
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作者 Wenhao Zhao Shengbo Hu 《Journal of Computer and Communications》 2023年第5期161-176,共16页
With the rapid development of deep learning methods, the data-driven approach has shown powerful advantages over the model-driven one. In this paper, we propose an end-to-end autoencoder communication system based on ... With the rapid development of deep learning methods, the data-driven approach has shown powerful advantages over the model-driven one. In this paper, we propose an end-to-end autoencoder communication system based on Deep Residual Shrinkage Networks (DRSNs), where neural networks (DNNs) are used to implement the coding, decoding, modulation and demodulation functions of the communication system. Our proposed autoencoder communication system can better reduce the signal noise by adding an “attention mechanism” and “soft thresholding” modules and has better performance at various signal-to-noise ratios (SNR). Also, we have shown through comparative experiments that the system can operate at moderate block lengths and support different throughputs. It has been shown to work efficiently in the AWGN channel. Simulation results show that our model has a higher Bit-Error-Rate (BER) gain and greatly improved decoding performance compared to conventional modulation and classical autoencoder systems at various signal-to-noise ratios. 展开更多
关键词 Deep Residual Shrinkage Network Autoencoder end-to-end Learning Communication Systems
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不同消化道吻合器械在腹腔镜下胃癌根治术中的应用效果及对炎性指标和预后的影响 被引量:1
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作者 涂云飞 朱峰 +2 位作者 孙建 王哲 乔泽强 《实用癌症杂志》 2024年第1期126-128,共3页
目的探讨不同消化道吻合器械在腹腔镜下胃癌根治术中的应用价值及对炎性指标和预后的影响。方法回顾性选取62例行腹腔镜下全胃切除术的胃癌患者,其中研究组患者30例采用完全腹腔镜下应用直线切割闭合器行食管空肠吻合治疗,而对照组患者3... 目的探讨不同消化道吻合器械在腹腔镜下胃癌根治术中的应用价值及对炎性指标和预后的影响。方法回顾性选取62例行腹腔镜下全胃切除术的胃癌患者,其中研究组患者30例采用完全腹腔镜下应用直线切割闭合器行食管空肠吻合治疗,而对照组患者32例则采用腹腔镜辅助下应用圆形吻合器行食管空肠吻合治疗,比较2组患者的临床疗效等差异。结果研究组的手术时间、术中出血量等均低于对照组(P<0.05);术后研究组的并发症总发生率(10.0%)显著低于对照组(31.3%)。术前2组的炎性相关指标比较无差异(P>0.05),而术后2组的炎性相关指标均较术前升高,且对照组升高更为显著(P<0.05)。术后1年,研究组的预后情况优于对照组(P<0.05)。结论直线切割闭合器应用于食管空肠吻合对于行全胃切除术的患者来说更有优势,其不仅可加快患者的康复速度,同时可降低并发症发生率及炎性反应,最终改善预后,值得临床推广应用。 展开更多
关键词 圆形吻合器 直线切割闭合器 食管空肠吻合 全胃切除术 疗效 预后
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全腹腔镜下全胃切除术食管空肠Overlap重建技术要点
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作者 张鹏 尹玉平 +2 位作者 蒋祈 杜雨强 陶凯雄 《腹部外科》 2024年第2期86-88,110,共4页
全腹腔镜下全胃切除术已逐渐成为早期胃癌的标准术式之一,但全腹腔镜下全胃切除术食管空肠消化道重建难度较大。该文就全腹腔镜下全胃切除术食管空肠Overlap重建技术要点进行了总结,以期缩短专科医生学习曲线,进一步改善胃癌病人预后。
关键词 全腹腔镜下全胃切除术 胃癌 食管空肠吻合术
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自牵引后离断技术在全腹腔镜全胃切除术中的应用
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作者 江雯 郑磊 +4 位作者 葛宇 汪晋 丰茂坤 徐茂奇 芮景 《腹腔镜外科杂志》 2024年第9期667-671,共5页
目的:探讨自牵引后离断食管空肠功能性端端吻合应用于全腹腔镜全胃切除术的临床效果。方法:选取2023年3月至2024年2月接受全腹腔镜全胃切除术(自牵引后离断吻合)的18例患者(观察组),并将2021年12月至2023年2月同一手术团队完成的20例腹... 目的:探讨自牵引后离断食管空肠功能性端端吻合应用于全腹腔镜全胃切除术的临床效果。方法:选取2023年3月至2024年2月接受全腹腔镜全胃切除术(自牵引后离断吻合)的18例患者(观察组),并将2021年12月至2023年2月同一手术团队完成的20例腹腔镜全胃切除术(管型吻合)作为对照组,对比分析两组术中、术后情况及手术相关并发症发生率。结果:手术均顺利完成,切缘阴性,无围手术期死亡病例。观察组手术时间[(225.89±26.19)min vs.(244.65±22.05)min,P=0.022]、辅助切口长度[(6.06±1.00)cm vs.(10.20±1.06)cm,P<0.001]短于对照组,差异有统计学意义。两组术中出血量、淋巴结清扫数量、术后首次排气时间、术后住院时间、手术相关并发症发生率差异无统计学意义(P>0.05)。结论:自牵引后离断食管空肠功能性端端吻合应用于全腹腔镜全胃切除术安全可行,容易掌握,值得临床推广。 展开更多
关键词 胃肿瘤 全胃切除术 腹腔镜检查 自牵引后离断 食管-空肠吻合
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E2E-MFERC:AMulti-Face Expression Recognition Model for Group Emotion Assessment
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作者 Lin Wang Juan Zhao +1 位作者 Hu Song Xiaolong Xu 《Computers, Materials & Continua》 SCIE EI 2024年第4期1105-1135,共31页
In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect anal... In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis,thereby continuouslypromotingthe improvementof teaching quality.However,most existingmulti-face expressionrecognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance,and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single faceimages, which are of low quality and lack specificity, also restricting the development of this research. This paperaims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable forsmart classrooms, construct a high-quality multi-face expression dataset to support algorithm research, and applythe model to group emotion assessment to expand its application value. To this end, we propose an end-to-endmulti-face expression recognition algorithm model for smart classrooms (E2E-MFERC). In order to provide highqualityand highly targeted data support for model research, we constructed a multi-face expression dataset inreal classrooms (MFED), containing 2,385 images and a total of 18,712 expression labels, collected from smartclassrooms. In constructing E2E-MFERC, by introducing Re-parameterization visual geometry group (RepVGG)block and symmetric positive definite convolution (SPD-Conv) modules to enhance representational capability;combined with the cross stage partial network fusion module optimized by attention mechanism (C2f_Attention),it strengthens the ability to extract key information;adopts asymptotic feature pyramid network (AFPN) featurefusion tailored to classroomscenes and optimizes the head prediction output size;achieves high-performance endto-end multi-face expression detection. Finally, we apply the model to smart classroom group emotion assessmentand provide design references for classroom effect analysis evaluation metrics. Experiments based on MFED showthat the mAP and F1-score of E2E-MFERC on classroom evaluation data reach 83.6% and 0.77, respectively,improving the mAP of same-scale You Only Look Once version 5 (YOLOv5) and You Only Look Once version8 (YOLOv8) by 6.8% and 2.5%, respectively, and the F1-score by 0.06 and 0.04, respectively. E2E-MFERC modelhas obvious advantages in both detection speed and accuracy, which can meet the practical needs of real-timemulti-face expression analysis in classrooms, and serve the application of teaching effect assessment very well. 展开更多
关键词 Multi-face expression recognition smart classroom end-to-end detection group emotion assessment
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A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images
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作者 Yuejie Li Shijun Li 《Computers, Materials & Continua》 SCIE EI 2024年第3期3041-3070,共30页
6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is... 6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques. 展开更多
关键词 6G technology blockchain end-to-end recognition Chinese characters natural scene computer vision algorithms convolutional neural network
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Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats
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作者 Yunting Xiang Xiangxin Xing +6 位作者 Xuyun Hua Yuwen Zhang Xin Xue Jiajia Wu Mouxiong Zheng He Wang Jianguang Xu 《Neural Regeneration Research》 SCIE CAS 2025年第5期1495-1504,共10页
Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev... Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery. 展开更多
关键词 brain functional networks end-to-end nerve transfer end-to-side nerve transfer independent component analysis nerve repair peripheral plexus injury resting-state functional connectivity
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Intracorporeal esophagojejunostomy after totally laparoscopic total gastrectomy: A single-center 7-year experience 被引量:16
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作者 Ke Chen Yu Pan +6 位作者 Jia-Qin Cai Xiao-Wu Xu Di Wu Jia-Fei Yan Rong-Gao Chen Yang He Yi-Ping Mou 《World Journal of Gastroenterology》 SCIE CAS 2016年第12期3432-3440,共9页
AIM: To assess the efficacy and safety of intracorporeal esophagojejunostomy in patients undergoing laparoscopic total gastrectomy(LTG) for gastric cancer.METHODS: A retrospective review of 81 consecutive patients who... AIM: To assess the efficacy and safety of intracorporeal esophagojejunostomy in patients undergoing laparoscopic total gastrectomy(LTG) for gastric cancer.METHODS: A retrospective review of 81 consecutive patients who underwent LTG with the same surgical team between November 2007 and July 2014 was performed. Four types of intracorporeal esophagojejunostomy using staplers or hand-sewn suturing were performed after LTG. Data on clinicopatholgoical characteristics, occurrence of complications, postoperative recovery, anastomotic time, and operation time among the surgical groups were obtained through medical records.RESULTS: The average operation time was 288.7 min, the average anastomotic time was 54.3 min, and the average estimated blood loss was 82.7 m L. There were no cases of conversion to open surgery. The first flatus was observed around 3.7 d, while the liquid diet was started, on average, from 4.9 d. The average postoperative hospital stay was 10.1 d. Postoperative complications occurred in 14 patients, nearly 17.3%.However, there were no cases of postoperative death.CONCLUSION: LTG performed with intracorporeal esophagojejunostomy using laparoscopic staplers or hand-sewn suturing is feasible and safe. The surgical results were acceptable from the perspective of minimal invasiveness. 展开更多
关键词 Gastric cancer Total GASTRECTOMY esophagojejunostomy LAPAROSCOPY Hand-sewn
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Esophagojejunostomy after laparoscopic total gastrectomy by Or VilTM or hemi-double stapling technique 被引量:13
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作者 Hao Wang Qun Hao +4 位作者 Meng Wang Min Feng Feng Wang Xin Kang Wen-Xian Guan 《World Journal of Gastroenterology》 SCIE CAS 2015年第29期8943-8951,共9页
AIM: To investigate the feasibility, advantages and disadvantages of two types of anvil insertion techniques for esophagojejunostomy after laparoscopic total gastrectomy.METHODS: This was an open-label prospective coh... AIM: To investigate the feasibility, advantages and disadvantages of two types of anvil insertion techniques for esophagojejunostomy after laparoscopic total gastrectomy.METHODS: This was an open-label prospective cohort study. Laparoscopy-assisted radical total gastrectomy with D2 lymph node dissection was performed in 84 patients with primary non-metastatic gastric cancer confirmed by pre-operative histological examination. Overweight patients were excluded, as well as patients with peritoneal dissemination and invasion of adjacent organs. After total gastrectomy, all patients were randomized into two groups. Patients in Group Ⅰ underwent esophagojejunostomy using a transorally-inserted anvil(Or VilTM), while patients in Group Ⅱ underwent esophagojejunostomy using the hemi-double stapling technique(HDST). Both types of esophagojejunostomy were performed under laparoscopy. Patients' baseline characteristics, preoperative characteristics, perioperative characteristics, short-term postoperative outcomes and operation cost were comparedbetween the two groups. The primary endpoint was evaluation of the surgical outcome(operating time, time of digestive tract reconstruction and time of anvil insertion) and the medical cost of each operation(operation cost and total cost of hospitalization). The secondary endpoints were time to solid diet, post-surgical hospitalization time, time to defecation, time to ambulation and intra-operative blood loss. In addition, complications were assessed and compared. RESULTS: Laparoscopic total gastrectomy and esophagojejunostomy were successfully performed in all 84 patients, without conversion to laparotomy. There were no significant differences in the operative time and time for total gastrectomy between the two groups(287.8 ± 38.4 min vs 271.8 ± 46.1 min, P = 0.09, and 147.7 ± 31.6 min vs 159.8 ± 33.8 min, P = 0.09, respectively). The time for digestive tract reconstruction and for anvil insertion were significantly decreased in Group Ⅱ compared with Group I(47.8 ± 12.1 min vs 55.4 ± 15.7 min, P = 0.01, and 12.6 ± 4.7 min vs 18.7 ± 7.5 min, P = 0.001, respectively). Intraoperative blood loss(96.4 ± 32.7 m L vs 88.2 ± 36.9 m L, P = 0.28), time to defecation(3.5 ± 0.9 d vs 3.2 ± 1.1 d, P = 0.12), time to ambulation(3.9 ± 0.7 d vs 3.6 ± 1.1 d, P = 0.12), time to solid diet(7.6 ± 1.4 d vs 8.0 ± 2.7 d, P = 0.31) and total hospitalization(10.6 ± 2.6 d vs 10.8 ± 3.5 d, P = 0.80) were similar between the two groups. In addition, the total costs of hospitalization were similar between the two groups(73848.7 ± 11781.0 RMB vs 70870.3 ± 14003.5 RMB, P = 0.296), but operation cost was significantly higher in Group I compared with Group Ⅱ(32401.9 ± 1981.6 RMB vs 26961.9 ± 2293.8 RMB, P < 0.001).CONCLUSION: Anvil insertion was faster and easier using the HDST technique compared with Or VilTM, and was more cost-effective. There was no significant difference in safety. 展开更多
关键词 LAPAROSCOPY GASTRECTOMY GASTRIC cancer esophagojejunostomy COHORT analysis
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Data Augmentation Technology Driven By Image Style Transfer in Self-Driving Car Based on End-to-End Learning 被引量:5
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作者 Dongjie Liu Jin Zhao +4 位作者 Axin Xi Chao Wang Xinnian Huang Kuncheng Lai Chang Liu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第2期593-617,共25页
With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while ... With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while current end-to-end model learning is generally limited to training of massive data,innovation of deep network architecture,and learning in-situ model in a simulation environment.Therefore,we introduce a new image style transfer method into data augmentation,and improve the diversity of limited data by changing the texture,contrast ratio and color of the image,and then it is extended to the scenarios that the model has been unobserved before.Inspired by rapid style transfer and artistic style neural algorithms,we propose an arbitrary style generation network architecture,including style transfer network,style learning network,style loss network and multivariate Gaussian distribution function.The style embedding vector is randomly sampled from the multivariate Gaussian distribution and linearly interpolated with the embedded vector predicted by the input image on the style learning network,which provides a set of normalization constants for the style transfer network,and finally realizes the diversity of the image style.In order to verify the effectiveness of the method,image classification and simulation experiments were performed separately.Finally,we built a small-sized smart car experiment platform,and apply the data augmentation technology based on image style transfer drive to the experiment of automatic driving for the first time.The experimental results show that:(1)The proposed scheme can improve the prediction accuracy of the end-to-end model and reduce the model’s error accumulation;(2)the method based on image style transfer provides a new scheme for data augmentation technology,and also provides a solution for the high cost that many deep models rely heavily on a large number of label data. 展开更多
关键词 Deep learning SELF-DRIVING end-to-end learning style transfer data augmentation.
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Partially Overlapped Channels- and Flow-Based End-to-End Channel Assignment for Multi-Radio Multi-Channel Wireless Mesh Networks 被引量:3
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作者 WANG Jihong SHI Wenxiao 《China Communications》 SCIE CSCD 2016年第4期1-13,共13页
Capacity reduction is a major problem faced by wireless mesh networks. An efficient way to alleviate this problem is proper channel assignment. Current end-toend channel assignment schemes usually focus on the case wh... Capacity reduction is a major problem faced by wireless mesh networks. An efficient way to alleviate this problem is proper channel assignment. Current end-toend channel assignment schemes usually focus on the case where channels in distinct frequency bands are assigned to mesh access and backbone, but actually backbone network and access network can use the same IEEE 802.11 technology. Besides, these channel assignment schemes only utilize orthogonal channels to perform channel assignment, and the resulting network interference dramatically degrades network performance. Moreover, Internet-oriented traffic is considered only, and peerto-peer traffic is omitted, or vice versa. The traffic type does not match the practical network. In this paper, we explore how to exploit partially overlapped channels to perform endto-end channel assignment in order to achieve effective end-to-end flow transmissions. The proposed flow-based end-to-end channel assignment schemes can conquer the limitations aforementioned. Simulations reveal that loadaware channel assignment can be applied to networks with stable traffic load, and it can achieve near-optimal performance; Traffic-irrelevant channel assignment is suitable for networks with frequent change of traffic load,and it can achieve good balance between performance and overhead. Also, partially overlapped channels' capability of improving network performance is situation-dependent, they should be used carefully. 展开更多
关键词 channel assignment: end-to-end partially overlapped channels load-aware traffic-irrelevant
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Redistribution of nerve strain enables end-to-end repair under tension without inhibiting nerve regeneration 被引量:2
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作者 Holly M.Howarth Turki Alaziz +2 位作者 Brogan Nicolds Shawn O'Connor Sameer B.Shah 《Neural Regeneration Research》 SCIE CAS CSCD 2019年第7期1280-1288,共9页
End-to-end repair under no or low tension leads to improved outcomes for transected nerves with short gaps,compared to repairs with a graft.However,grafts are typically used to enable a tension-free repair for moderat... End-to-end repair under no or low tension leads to improved outcomes for transected nerves with short gaps,compared to repairs with a graft.However,grafts are typically used to enable a tension-free repair for moderate to large gaps,as excessive tension can cause repairs to fail and catastrophically impede recovery.In this study,we tested the hypothesis that unloading the repair interface by redistributing tension away from the site of repair is a safe and feasible strategy for end-to-end repair of larger nerve gaps.Further,we tested the hypothesis that such an approach does not adversely affect structural and functional regeneration.In this study,we used a rat sciatic nerve injury model to compare the integrity of repair and several regenerative outcomes following end-to-end repairs of nerve gaps of increasing size.In addition,we proposed the use of a novel implantable device to safely repair end-to-end repair of larger nerve gaps by redistributing tension away from the repair interface.Our data suggest that redistriubution of tension away from the site of repair enables safe end-to-end repair of larger gap sizes.In addition,structural and functional measures of regeneration were equal or enhanced in nerves repaired under tension – with or without a tension redistribution device – compared to tension-free repairs.Provided that repair integrity is maintained,end-to-end repairs under tension should be considered as a reasonable surgical strategy.All animal experiments were performed under the approval of the Institutional Animal Care and Use Committee of University of California,San Diego(Protocol S11274). 展开更多
关键词 tension biomechanics STRAIN end-to-end REPAIR PERIPHERAL NERVE NERVE regeneration
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Internet end-to-end delay dynamics 被引量:2
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作者 Zhu Changhua Pei Changxing Li Jiandong Chen Nan Yi Yunhui 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第3期685-691,共7页
End-to-end delay is one of the most important characteristics of Internet end-to-end packet dynamics, which can be applied to quality of services (OoS) management, service level agreement (SLA) management, congest... End-to-end delay is one of the most important characteristics of Internet end-to-end packet dynamics, which can be applied to quality of services (OoS) management, service level agreement (SLA) management, congestion control algorithm development, etc. Nonstationarity and nonlinearity are found by the analysis of various delay series measured from different links. The fact that different types of links have different degree of Self-Similarity is also obtained. By constructing appropriate network architecture and neural functions, functional networks can be used to model the Internet end-to-end nonlinear delay time series. Furthermore, by using adaptive parameter studying algorithm, the nonstationarity can also be well modeled. The numerical results show that the provided functional network architecture and adaptive algorithm can precisely characterize the Internet end-to-end delay dynamics. 展开更多
关键词 INTERNET end-to-end delay functional network nonlinear system.
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Generating Questions Based on Semi-Automated and End-to-End Neural Network 被引量:1
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作者 Tianci Xia Yuan Sun +2 位作者 Xiaobing Zhao Wei Song Yumiao Guo 《Computers, Materials & Continua》 SCIE EI 2019年第8期617-628,共12页
With the emergence of large-scale knowledge base,how to use triple information to generate natural questions is a key technology in question answering systems.The traditional way of generating questions require a lot ... With the emergence of large-scale knowledge base,how to use triple information to generate natural questions is a key technology in question answering systems.The traditional way of generating questions require a lot of manual intervention and produce lots of noise.To solve these problems,we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions.The semi-automated model can generate question templates and real questions combining the knowledge base and center graph.The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network.Meanwhile,the attention mechanism is utilized in the decoding layer,which makes the triples and generated questions more relevant.Finally,the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach. 展开更多
关键词 Generating questions semi-automated model end-to-end neural network question answering
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An autonomic joint radio resource management algorithm in end-to-end reconfigurable system 被引量:1
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作者 林粤伟 《High Technology Letters》 EI CAS 2008年第3期238-244,共7页
This paper presents the multi-step Q-learning(MQL)algorithm as an autonomic approach to thejoint radio resource management(JRRM)among heterogeneous radio access technologies(RATs)in theB3G environment.Through the'... This paper presents the multi-step Q-learning(MQL)algorithm as an autonomic approach to thejoint radio resource management(JRRM)among heterogeneous radio access technologies(RATs)in theB3G environment.Through the'trial-and-error'on-line learning process,the JRRM controller can con-verge to the optimized admission control policy.The JRRM controller learns to give the best allocation foreach session in terms of both the access RAT and the service bandwidth.Simulation results show that theproposed algorithm realizes the autonomy of JRRM and achieves well trade-off between the spectrum utilityand the blocking probability comparing to the load-balancing algorithm and the utility-maximizing algo-rithm.Besides,the proposed algorithm has better online performances and convergence speed than theone-step Q-learning(QL)algorithm.Therefore,the user statisfaction degree could be improved also. 展开更多
关键词 joint radio resource management reinforcement learning AUTONOMIC end-to-end reconfigurability heterogeneous networks
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