Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis最新文献

A Review of Text Classification Based on Deep Learning 基于深度学习的文本分类研究综述

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397082

Yifan Zhou

{"title":"A Review of Text Classification Based on Deep Learning","authors":"Yifan Zhou","doi":"10.1145/3397056.3397082","DOIUrl":"https://doi.org/10.1145/3397056.3397082","url":null,"abstract":"Text classification is the process of discriminating predetermined text into a certain class or some certain classes. Text categorization has important applications in redundant filtering, organization management, information retrieval, index building, ambiguity resolution, and text filtering. This paper we will mainly introduce the research background of text classification and tracks the research dynamics of text classification at home and abroad. Text classification is an essential component in many NLP problems. Neural network model had achieved extraordinary effect in text classification. So we will discuss how the general methods with deep learning to deal with text classification problems, including Convolution Neural Network(CNN), Recurrent convolution neural network(RCNN), Long Short-Term memory(LSTM), and fastCNN. CNN can construct the representation of text using a convolutional neural network. RNN does well in capturing contextual information. LSTM is explicitly designed for time-series data for learning long-term dependencies. Besides, we will introduce the distributed representation, such as Continuous Bags of Words(CBOW) and Skip-Gram. And analyze the advantages of word2vec model over on-hot encoding.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126931852","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: 18

Fishing Techniques Classification Based on Beidou Trajectories and Machine Learning 基于北斗轨迹和机器学习的钓鱼技术分类

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397072

Yao Li, Nanyu Chen, Luo Chen

{"title":"Fishing Techniques Classification Based on Beidou Trajectories and Machine Learning","authors":"Yao Li, Nanyu Chen, Luo Chen","doi":"10.1145/3397056.3397072","DOIUrl":"https://doi.org/10.1145/3397056.3397072","url":null,"abstract":"Beidou navigation information is widely used in Chinese fisheries. It helps fishermen to locate themselves and hedge. Compared with the data ashore, analysis of satellite data on the ocean is still not enough. Inspired by vehicle trajectory analysis, we want to do some analysis on boat trajectories. Fishing techniques are various, so their trajectories. In this paper, we choose 3 fishing techniques (Trawling, seining and gillnetting). We implement classification with two different algorithms. One of them is ResNet which belongs to image classification with deep learning. The other one is LightGBM which is a kind of decision tree algorithm. The result shows that although deep learning has made great success in daily life images classification, it adds too much redundant pixels and ignore the speed and direction parameters in this task. This leads to a lower precision and more calculations. In contrast, LightGBM can use information effectively and has a higher score with a higher speed. This work shows traditional machine learning algorithm can achieve better result than deep learning algorithm in some circumstance. It will also contribute to establish a smart ocean system.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114707088","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 Deceptive Interference Cancellation for GNSS Receiver with Small Forwarding Delay 小转发延迟GNSS接收机的欺骗性干扰消除

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397067

Honglei Lin, Zukun Lu, Xiaomei Tang

引用次数: 0

Space-Time Adaptive Processor with Zero Delay for GNSS Antenna Arrays 零延迟GNSS天线阵空时自适应处理器

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397064

Zukun Lu, Yuchen Xie, Honglei Lin, Jingyuan Li, Feiqiang Chen

引用次数: 1

Overview of Anti-Jamming Technology Based on GNSS Single-Antenna Receiver 基于GNSS单天线接收机的抗干扰技术综述

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397077

Xianghao Li, Feiqiang Chen, Zukun Lu, Zhe Liu, G. Ou

引用次数: 2

A GIS and Remote Sensing Approach for Desertification Sensitivity Assessment in Basilicata Region (Italy) 意大利巴西利卡塔地区沙漠化敏感性评价的GIS与遥感方法

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397079

Marzia Gabriele, M. Previtali

{"title":"A GIS and Remote Sensing Approach for Desertification Sensitivity Assessment in Basilicata Region (Italy)","authors":"Marzia Gabriele, M. Previtali","doi":"10.1145/3397056.3397079","DOIUrl":"https://doi.org/10.1145/3397056.3397079","url":null,"abstract":"The evaluation of the environmental sensitivity to desertification of the rapidly changing Mediterranean landscape under the effects of climate change is evidently necessary for planning a sustainable method of management policies. This paper aim is to evaluate the current sensitivity to desertification of Basilicata region in southern Italy, where this phenomenon has been increasing over the past years, without control. Losses are strongly impacting on the potential regional progress, both economic and social, leading also to a huge ecological damage. The analysis was carried out based on the MEDALUS (MEditerrean Desertification and Land Use) model, developed within a dedicated European project. This method identifies the areas of the region that are more likely to be sensible to desertification thought the Environmentally Sensitive Areas (ESAs) index. Starting with this methodology, the model parameters were implemented and then processed with a GIS-based approach, in order to evaluate soil, climate, management and vegetation quality factors, that represent the necessary input for assessing ESAs. The results were useful to indicate that the region is effectively lacking of management policies in those highly sensitive areas, due to a proved scarcity of previous studies on the topic. This study may open new opportunities for a further more conscious planning to prevent landscape, land and soil degradation.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125076246","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: 2

Robust Estimation Model for 3D Coordinate Transformations based on Differential Total Least Squares Algorithm 基于微分总最小二乘算法的三维坐标变换鲁棒估计模型

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397062

Fan Wei, Pan Guo-rong, Qi Liyang

{"title":"Robust Estimation Model for 3D Coordinate Transformations based on Differential Total Least Squares Algorithm","authors":"Fan Wei, Pan Guo-rong, Qi Liyang","doi":"10.1145/3397056.3397062","DOIUrl":"https://doi.org/10.1145/3397056.3397062","url":null,"abstract":"Existing Gauss-Newton methods for solving the problem of 3D similarity transformation are all based on the method of numerical partial derivatives, which can linearize the 3D similarity transformation model by using Taylor expansion for approximated variables to the first order derivative. And by using the linearized 3D transformation model, all of the unknown variables can be obtained by an iterative process. In existing models, the model considering random errors of design matrix is called errors-in-variables (EIV) model. In contrast to the Gauss-Newton methods, a Gauss-quasi-Newton method for solving the problem of 3D similarity transformation is proposed in this paper. In the Gauss-quasi-Newton method, 3D similarity transformation model is linearized by a differential method, and based on the differential linearization model, an iterative robust estimation can be carried out by considering both random errors and gross errors in 3D coordinates of common points. The new method proposed in this paper can be applied to 3D similarity transformation of arbitrary rotational angles. Finally, the new method is validated by three cases, and results showed that the new method is effective and feasible.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133902222","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

An Empirical Study of Agile Testing in A Distributed Software Development Project 敏捷测试在分布式软件开发项目中的实证研究

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397085

A. Qahtani

{"title":"An Empirical Study of Agile Testing in A Distributed Software Development Project","authors":"A. Qahtani","doi":"10.1145/3397056.3397085","DOIUrl":"https://doi.org/10.1145/3397056.3397085","url":null,"abstract":"The software engineering industry has witnessed an increasing number of innovative methods and practices in the last decade at different levels, ranging from development processes to software projects and from testing to verification software products. Extensive studies have been conducted empirically to investigate and discuss the impact of using agile principles in the testing process on distributed teams across geographical boundaries. This empirical study has a similar focus, using a real case study in a distributed domain and applying agile testing to a selected team, compares their outcome with another three teams to determine the impact of involving a client in a testing process to overcome distributed development challenges. The findings indicate a highly positive impact on team productivity when using agile tests as compared with other groups using central distributed team testing. All teams met a 90% testing requirement. However, the group applying agile testing verified more than 99% of all requests entered into the testing process, a notable difference supporting the productivity of any development project.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123432908","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: 2

Data-Driven Representation Model of Urban Movement Space 城市运动空间的数据驱动表示模型

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397061

Harbil Arregui, O. Otaegui, O. Arbelaitz

引用次数: 0

Artificial Bee Colony for Solving Multi-Objectives Three-Dimensional Knapsack Problem 求解多目标三维背包问题的人工蜂群

Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis Pub Date : 2020-04-15 DOI: 10.1145/3397056.3397087

Suriya Phongmoo, K. Leksakul, Pongsawat Premphet

{"title":"Artificial Bee Colony for Solving Multi-Objectives Three-Dimensional Knapsack Problem","authors":"Suriya Phongmoo, K. Leksakul, Pongsawat Premphet","doi":"10.1145/3397056.3397087","DOIUrl":"https://doi.org/10.1145/3397056.3397087","url":null,"abstract":"The objectives of this research aim to apply the mathematical model, to propose an Artificial Bee Colony for Solving Three-Dimensional Knapsack Problem and to determine the optimal parameters of an Artificial Bee Colony Algorithm. This work application of heuristic approach is used for optimizing containers loading problem and we has a contract with logistic and transport company in the northern of Thailand to joint on this research. For the containers loading problem are the Three-Dimensional Knapsack Problem and it will be solving the real problem within the supporting of logistic and transport company in the northern of Thailand. However we deal with Nim See Seng Transport 1988 Co., Ltd cause of they are the big transportation company in the north of Thailand. The result of this research will be comparing between performance of the result in OR-Library which is a database that collects the best optimal solution data about Three-Dimensional Knapsack Problem and Artificial Bee Colony Algorithm, on the other hand Artificial Bee Colony Algorithm will be provides the good solutions within the satisfaction computer runtime, maximize profit, minimize empty space and respond to customers satisfaction also.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134484547","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