2022 14th International Conference on Machine Learning and Computing (ICMLC)最新文献_第3页

Accelerated operating room scheduling using Lagrangian relaxation method and VNS meta-heuristic 利用拉格朗日松弛法和VNS元启发式算法加速手术室调度

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529928

Maha Toub, S. Achchab, Omar Souissi

{"title":"Accelerated operating room scheduling using Lagrangian relaxation method and VNS meta-heuristic","authors":"Maha Toub, S. Achchab, Omar Souissi","doi":"10.1145/3529836.3529928","DOIUrl":"https://doi.org/10.1145/3529836.3529928","url":null,"abstract":"Like any business that produces services, the hospital is part of a process of improving the quality of services provided to patients. As part of this, hospitals are faced with the daunting task of planning operating room patients with budget, time and personnel. Most of the scheduling problems are NP-hard, so researchers have favored the development of heuristics and meta-heuristics to the detriment of exact methods. In a context where high performance computers are in continuous improvement, it is once again interesting to explore exact methods. Here we focus on developing exact methods for solving the operating room planning and scheduling problem. Our contribution is to develop first an accelerated Integer Linear Program (ILP) using the Variable Neighborhood Search (VNS) meta-heuristic to optimize patient waiting time according to the priority of their surgeries. Afterwards, we expose a new lower bound obtained by optimizing the patient waiting time relaxed. The experimental results validated the performance of the accelerated ILP in comparison with the original ILP. Furthermore, we have shown that the Lagrangian relaxation of the original ILP produces a lower bound of good quality.","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122505840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AFAR: A Real-Time Vision-based Activity Monitoring and Fall Detection Framework using 1D Convolutional Neural Networks 基于一维卷积神经网络的实时视觉活动监测和跌倒检测框架

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529862

J. Suarez, Nathaniel S. Orillaza, P. Naval

引用次数: 2

Optimize the NOx emission concentration of Circulation Fluidized Bed Boiler based on on-line learning neural network and modified TLBO algorithm 基于在线学习神经网络和改进TLBO算法的循环流化床锅炉NOx排放浓度优化

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529944

S. Liu, Yunpeng Ma, Ran Wang, Wenju Dong, Yuyin Wang

引用次数: 1

Welding Seam Recognition Technology of Welding Robot Based on A Novel Multi-Path Neural Network Algorithm 基于新型多路径神经网络算法的焊接机器人焊缝识别技术

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529906

Chenyang Liu, Xiangqian Chang, Zhiming Cao, Dan Xu, Hongjie Yang, Zhihao Su

引用次数: 0

Classification of Tropical Cyclone Risks in the Philippines using Random Forest 使用随机森林对菲律宾热带气旋风险进行分类

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529916

Donata D. Acula

引用次数: 0

Research on fine-tuning CNN for cancer diagnosis with gene expression data 基于基因表达数据的微调CNN癌症诊断研究

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529844

Z. Liu, Ruoyu Wang, Jin Yang, Wen-bo Zhang

{"title":"Research on fine-tuning CNN for cancer diagnosis with gene expression data","authors":"Z. Liu, Ruoyu Wang, Jin Yang, Wen-bo Zhang","doi":"10.1145/3529836.3529844","DOIUrl":"https://doi.org/10.1145/3529836.3529844","url":null,"abstract":"Convolutional neural networks have been used for cancer type prediction with gene expression data. However, its success is impeded by the lack of large labeled datasets in gene expression data. The class imbalance problem leads to that the model ignores the performance of the minority class. To handle the small sample size problem, fine-tuning CNN is used to transfer the knowledge of pre-trained model for cancer type predicting. The dataset with one cancer is used for training a model. The pre-model is fine-tuned with the training set of a new cancer type, and the fine-tuned model could be used for identifying the new cancer type. And the SMOTE resampling method is used for handling the class imbalance problem. We carried out experiments on The TCGA datasets with 1D-CNN and 2D-CNN models. The fine-tuned 1D-CNN obtains 97.5% accuracy, 98.6% Fscore of cancer type and 78.1% Fscore of normal type on average, and fine-tuned 2D-CNN obtains 97.4% accuracy, 98.5% Fscore of cancer type and 77.4% of normal type on average. Using fine-tuned CNN with SMOTE, the accuracy, Fscore of cancer type and the one of normal type are respectively increased about 1.5%, 0.5% and 21.5% on average.","PeriodicalId":285191,"journal":{"name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121827168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Group Activity Recognition based on Temporal Semantic Sub-Graph Network 基于时态语义子图网络的群体活动识别

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529899

Dongli Wang, Jia Liu, Yan Zhou

引用次数: 1

Self-supervised Domain Adaptation Model Based on Contrastive Learning 基于对比学习的自监督领域自适应模型

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529858

Ya Ma, Biao Chen, Ziwei Li, Gang Bai

引用次数: 0

Brain MR Images Super-Resolution with the Consistent Features 具有一致特征的超分辨率脑MR图像

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529939

Senrong You, Yanyan Shen, Guocheng Wu, Shuqiang Wang

引用次数: 3

Multi-label text classification via hierarchical Transformer-CNN 基于层次变换- cnn的多标签文本分类

2022 14th International Conference on Machine Learning and Computing (ICMLC) Pub Date : 2022-02-18 DOI: 10.1145/3529836.3529912

Junzhe Li, Chenglong Wang, Xiaohan Fang, Kai Yu, Jinye Zhao, Xi Wu, Jibing Gong

引用次数: 1