2020 12th International Conference on Knowledge and Systems Engineering (KSE)最新文献_第6页

CityScope Hanoi: interactive simulation for water management in the Bac Hung Hai irrigation system CityScope Hanoi:北鸿海灌溉系统水管理的交互式模拟

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287831

A. Grignard, T. Nguyen-Huu, B. Gaudou, Doanh Nguyen-Ngoc, Arthur Brugière, Tu Dang-Huu, N. Huynh, Trong Khanh Nguyen, K. Larson

{"title":"CityScope Hanoi: interactive simulation for water management in the Bac Hung Hai irrigation system","authors":"A. Grignard, T. Nguyen-Huu, B. Gaudou, Doanh Nguyen-Ngoc, Arthur Brugière, Tu Dang-Huu, N. Huynh, Trong Khanh Nguyen, K. Larson","doi":"10.1109/KSE50997.2020.9287831","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287831","url":null,"abstract":"Irrigation systems contribute worldwide to the provision of a wide range of services on which the survival and well-being of humanity depend. They are of primary importance in Vietnam where about 90% of the water used is for irrigation and aquaculture and where agriculture is the largest employer and a major contributor to the national GDP and to the income of the low-salary households. Nevertheless, irrigation systems have recently been subjected to several issues including increasing demand, pollution, under-investment, depletion of resources or environmental changes. Any mitigation measure against these issues needs to be sustainable with respect to the very diverse uses of the water, the changing conditions upstream and downstream, and the somewhat conflicting objectives carried out by land-use/agricultural planning on one hand and urbanization and society well-being on the other. This need of sustainability requires the design of innovative tools to tackle these issues. This work aims at exploring the usage of Agent-Based Modelling coupled with a tangible and interactive interface in order to enhance interactions between stakeholders and support the evaluation of various alternatives of the management of the Bac Hung Hai irrigation system.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128663493","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: 1

A new method on lncRNA-disease-miRNA tripartite graph to predict lncRNA-disease associations lncrna -疾病- mirna三方图预测lncrna -疾病关联的新方法

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287563

V. Nguyen, Thi Tu Kien Le, D. Tran

引用次数: 3

Isolated Handwritten Balinese Character Recognition from Palm Leaf Manuscripts with Residual Convolutional Neural Networks

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287584

D. M. S. Arsa, Gusti Agung Ayu Putri, Remmy A. M. Zen, S. Bressan

引用次数: 4

An investigation of cancer cell line-based drug response prediction methods on patient data 基于患者数据的肿瘤细胞系药物反应预测方法的研究

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287633

Giang T. T. Nguyen, Le Due Hoang, Q. Nguyen, T. Nguyen, Hien Dang, Duc-Hau Le

{"title":"An investigation of cancer cell line-based drug response prediction methods on patient data","authors":"Giang T. T. Nguyen, Le Due Hoang, Q. Nguyen, T. Nguyen, Hien Dang, Duc-Hau Le","doi":"10.1109/KSE50997.2020.9287633","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287633","url":null,"abstract":"The most significant goal of precision medicine is to identify the right treatment for individual patients based on their molecular profiles. Several big projects have been provided with a large amount of -omics and drug response data for human cell lines such as GDSC and CCLE and for patients such as GEO. Based on these useful datasets, many computational methods are increasingly being applied to predict not only untested drug responses on cell lines but also those on the patients. Such approaches built prediction models for drug response on cell line data then applied the learned models to predict drug response on the patient. In this way, it also helps to tackle the disparity between models trained on cell lines and their clinical applications. However, the datasets are highly heterogeneous in terms of the used array techniques, drug response measurements, and so on, thus leading to inconsistent results across computational methods on different datasets. Therefore, in this study, we assessed seven machine learning models built on the cell line datasets and then applied them to the patient datasets. Experimental results show that models built on pan-cancer cell lines cannot work well on every cancer-specific patient dataset Also, patient datasets with larger sizes were suggested to measure the prediction performance of each method correctly.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115462602","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

A comparison of Vietnamese Statistical Parametric Speech Synthesis Systems 越南语统计参数语音合成系统的比较

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-05-26 DOI: 10.1109/KSE50997.2020.9287553

Phan Huy Kinh, V. Phung, Anh-Tuan Dinh, Quoc Bao Nguyen

引用次数: 0