Chinese medical named entity recognition utilizing entity association and gate context awareness. by Yang Yan, Yufeng Kang, Wenbo Huang, Xudong Cai

“…Finally, we leverage conditional random fields in combination with the cross-entropy loss function to enhance entity recognition accuracy and ensure label sequence consistency. …”
Get full text

Rolling Bearing Fault Diagnosis Using Improved Deep Residual Shrinkage Networks by Zhijin Zhang, He Li, Lei Chen, Ping Han

“…To improve feature learning ability and accurately diagnose the faults of rolling bearings under a strong background noise environment, we present a new shrinkage function named leaky thresholding to replace the soft thresholding in the deep residual shrinkage networks (DRSNs). …”
Get full text

Tibetan entity relation extraction based on multi-level attention fusion mechanism by Like WANG, Yuan SUN, Sisi LIU

“…Compared with Chinese and English, the training corpus of Tibetan entity relation is smaller, so it is difficult to obtain higher accuracy based on traditional supervised learning methods.And there exists the problem of wrong labels in distant supervision for relation extraction.To solve these problems, the distant supervision method was used to construct the data set of Tibetan entity relation extraction through aligning the knowledge base with texts, which could alleviate the problem of lacking of large-scale corpus in Tibetan.And a Tibetan entity relation extraction model based on multi-level attention fusion mechanism was proposed.The self-attention was added to extract internal features of words in word level.The selective attention mechanism could assign weights of each instance, so as to make full use of informative sentences and reduce weights of noisy instances.Meanwhile, a joint score function was introduced to correct wrong labels, and neural network was combined with support vector machine to extract relations.Experimental results show that the proposed model can effectively improve the accuracy of Tibetan entity relation extraction, and is better than the baseline.…”
Get full text

Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss by Yongsoo Park, Gregory C. Beroza

“…Here, we test the Dice loss, which is a preferred loss function for highly imbalanced image segmentation problems. …”
Get full text

Gaps between market performance, government planning and social objectives: projections and comparisons of carbon price intervals by Xing Zhou, Jianze Xu, Ming Zhang, Anyi Niu, Chuxia Lin

“…Abstract The core function of the carbon market is price discovery, but the current carbon prices neither reflect government planning to reduce emissions nor provide the necessary incentives for the innovation of low-carbon technologies in society. …”
Get full text

An Improved Method of Particle Swarm Optimization for Path Planning of Mobile Robot by Xun Li, Dandan Wu, Jingjing He, Muhammad Bashir, Ma Liping

“…This paper proposes an improved PSO integration scheme based on improved details, which integrates uniform distribution, exponential attenuation inertia weight, cubic spline interpolation function, and learning factor of enhanced control. …”
Get full text

Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
Get full text

Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
Get full text

Qualités des dossiers universitaires : analyse d’un programme de formation en enseignement by Léon Harvey, Marie-Hélène Hébert, Catherine Simard

“…However, some slight iniquities remain in the UGPA as a function of students’ gender and age, once past academic success has been accounted for.…”
Get full text

Reconstruction of internal structures of Nilaparvata lugens using micro-computer tomography technology (Micro CT) by SHU Runguo, ZHOU Hang, CAO Zixiong, HE Kang, LI Fei

“…It provides a new technique for insect development investigation and gene function analysis in entomology.…”
Get full text

Understanding the No-sword with no teacher: A practical attempt to read The Illustrated Catalogue of the Shinkage-Ryū Martial Arts with the help of Yagyū heihō kadensho by Michael Mattner

“…Despite being written at different times, can the depictions, descriptions and the text together function as a mean to learn the techniques? Is it possible to extract the embodied knowledge embedded in the text by combining the scroll with the commentary and the book? …”
Get full text

Technique for target recognition based on intuitionistic fuzzy c-means clustering and kernel matching pursuit by Yang LEI, Wei-wei KONG, Ying-jie LEI

“…Kernel matching pursuit requires every step of searching process be global optimal searching in the redundant dictionary of function.Namely,the dictionary learning time of KMP was too long.To the above drawbacks,a novel technique for KMP based on IFCM was proposed to substitute local searching for global searching by the property superiority of dynamic clustering performance,which was also the superiority in Intuitionistic fuzzy c-means algorithm.Then two testing including classification and effectiveness were carried out towards four real sample data.Subsequently,high resolution range profile (HRRP)was selected from the classical properties of target recognition in e middle ballistic trajectory,which were extracted for getting sub-range profile.Finally,three algorithms including FCM,KMP,IFCM-KMP were carried out respectively towards different kinds of sub-range profile samples in emulation platform,the conclusion of which fully demonstrates that the IFCM-KMP algorithm is superior over FCM and KMP when it comes to target recognition in the middle ballistic trajectory.…”
Get full text

Fusion of multi-scale and context for small target detection algorithm of unmanned aerial vehicle rescue by LIU Yuan, ZHAO Jing, JIANG Guoping, XU Fengyu, LU Ningyun

“…Secondly, to improve the robustness of the model, spatial attention module was designed to enhance the learning of important features. Finally, balance L1 loss was used to optimize the loss function of the baseline algorithm and enhance the stability of the model during the process of detection. …”
Get full text

Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures by Nishchal K. Verma

“…The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. …”
Get full text

Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…The recursive random forest removal function provided a significant feature range. Random Forest Classifier investigated the diabetes estimate. …”
Get full text

Binary atom search optimisation approaches for feature selection by Jingwei Too, Abdul Rahim Abdullah

“…In the proposed scheme, eight transfer functions from S-shaped and V-shaped families are used to convert the continuous ASO into the binary version. …”
Get full text

Spatial Mapping of Glioblastoma Infiltration: Diffusion Tensor Imaging-Based Radiomics and Connectomics in Recurrence Prediction by Kevin Jang, Michael Back

“…The implications for personalised neuro-oncology are profound, marking a shift towards risk-adaptive, tract-aware treatment strategies that may improve local control and preserve neurocognitive function.…”
Get full text

Att bli och att vara framgångsrik musiker – socialisation och sortering genom livet by Anna Nørholm Lundin

“… This article concerns learning, socialization and social sorting among successful musicians. …”
Get full text

Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
Get full text

Creative expression, community, and calculated risks : protective and risk factors associated with BMX by Dave Camilleri, Shanee Katz

“…This study explores the role of Bicycle Motocross (BMX) beyond its conventional recreational function, focusing on its impact on individual and social wellbeing. …”
Get full text