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2012 16th International Conference on Information Visualisation, IV 2012

作者： Cesario, Manuel Jervis, Matthew Luz, Saturnino Masoodian, Masood Rogers, Bill Graduate Programme on Health Promotion University of Franca Brazil Department of Computer Science University of Waikato New Zealand School of Computer Science and Statistics Trinity College Dublin Ireland

ISBN: (纸本)9780769547718

Information visualisation methods can potentially be employed to assist the work of epidemiologists and other health care professionals in mapping the spread of communicable diseases in remote areas, where the task of disease surveillance encompasses temporal elements such as changes in climate, land use and population movements. This paper presents an investigation into the use of time-based visualisation techniques coupled with geographical maps and support for distributed mobile collection of patient data. This study has focused on the development of an information visualisation prototype designed for use by epidemiology researchers on mobile platforms (tablets and smart phones). The prototyping activity has involved the participation of prospective users working in the Amazon region. Initial results are presented and discussed. © 2012 IEEE.

关键词： Mapping

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LenAtten: An Effective Length Controlling Unit For Text Summarization

LenAtten: An Effective Length Controlling Unit For Text Summ...

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Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

作者： Yu, Zhongyi Wu, Zhenghao Zheng, Hao Zhe, XuanYuan Fong, Jefferson Su, Weifeng Computer Science and Technology Programme United States Data Science Programme Division of Science and Technology United States Guangdong Key Lab of AI and Multi-Modal Data Processing BNU-HKBU United International College Zhuhai China

ISBN: (纸本)9781954085541

Fixed length summarization aims at generating summaries with a preset number of words or characters. Most recent researches incorporate length information with word embeddings as the input to the recurrent decoding unit, causing a compromise between length controllability and summary quality. In this work, we present an effective length controlling unit Length Attention (LenAtten) to break this trade-off. Experimental results show that LenAtten not only brings improvements in length controllability and ROGUE scores but also has great generalization ability. In the task of generating a summary with the target length, our model is 732 times better than the best-performing length controllable summarizer in length controllability on the CNN/Daily Mail dataset. © 2021 Association for Computational Linguistics

关键词： Controllability

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COVID-19 Vaccination Data Visualization: Issues and Challenges 1

COVID-19 Vaccination Data Visualization: Issues and Challeng...

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1st International Visualization, Informatics and Technology Conference, IVIT 2022

作者： Ismail, Izzatul Syahirah Hajar Aishah Samsudin, Siti Sani Mohd Sofian, Muhammad Adam Jantan, Hamidah Cawangan Terengganu Computer Science Programme Faculty of Computer and Mathematical Sciences Kuala Terengganu21080 Malaysia Universiti Teknologi MARA Cawangan Terengganu Faculty of Computer and Mathematical Sciences Department of Computer Science Kuala Terengganu21080 Malaysia

ISBN: (纸本)9781665486484

Data Visualization plays an important role for patterns and trends analysis in trillion of data rows Big Data analysis, where the data can be represented in some graphical forms. Hence, the data could be more comprehensible in its visual summary in dashboards and storyboards. This study aims to discuss some issues and challenges in visualizing COVID-19 vaccination datasets. There are some possible issues in data visualization, as it is not easy and may be challenging to produce a good dashboard that are interesting and easy for viewers to understand. Therefore, this study focuses on some issues that may arise during performing a data visualization on the COVID-19 dataset. In this study, there are three dashboards have been studied, which are the COVID-19 tracker, its effectiveness, and its acceptance. The first two dataset are derived from Ministry of Health Malaysia bank data, whereas the third dataset is from a survey to support this analysis. The selected attributes are states, the number of people who have received the vaccine as adults, children, and teenagers, and the number of people who already received boosters, and reasons to not get a booster. The visualization issues found within the dashboard are mis-choice of colors, mis-choice of visual object type, lack of interactivity, and plotting too much data. As a result, this proposed alternative solutions for those issues such as color deliberately, pick a suitable visual object, create an interactive dashboard, and reduce the information overload in visualizing the data. © 2022 IEEE.

关键词： COVID-19

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An extended professional development programme for specialist computing teachers in Hong Kong

An extended professional development programme for specialis...

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996 International Conference Software Engineering: Education and Practice, SEEP 1996

作者： Stranks, M.B. Woodward, M.C. MMSE Programme Manager Dept. of Computer Science City University of Hong Kong Hong Kong MMSE Programme Manager School of Computing Staffordshire University United Kingdom

ISBN: (纸本)0818673796

This paper describes how two nominally independent programmes, which are offered by independent institutions in different countries, have been combined to form one effective co-ordinated scheme of study that provides school teachers with a part time developmental programme leading to the award of ***. Degree. The first »conversion» programme is designed for graduates with little or no knowledge of computing. Here each student develops their underpinning knowledge and practical skills within computing. The second »advanced» programme is chosen to provide teachers with an opportunity for professional development at an advanced level within the area of computing and to mix with other graduate-level people with industrial experience in computing. The paper first explores the background to the development, identifying needs within Hong Kong which make the development appropriate. The nature and strengths of each of the contributing programmes are then presented. This is followed by a discussion of the rational for providing a coherent route through the two individual programmes. The remainder of the paper concentrates on the ***. Provision, identifying issues in the integration of student groups and the management of dissertations across the sets of students from two different backgrounds. The paper concludes with a summary of the lessons learnt from the development and early operation of the scheme. © 1996 IEEE.

关键词： Students

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Mobile Application for flood disaster in Jakarta

Mobile Application for flood disaster in Jakarta

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2021 International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021

作者： Anta, Vito Lauda Putra Liestyo, Ivander Albert Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Binus Graduate Programme Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728195377

Jakarta as the Indonesian capital city has extreme average rainfall in 2020, based on data from the DKI Jakarta Representative Central Bureau of Statistics and the meteorology, climatology, and geophysics agency. From year to year, the city of Jakarta has not been spared from floods which have seriously disrupted the activities of the people of Jakarta. Flood disasters greatly disrupt people's economic activities and cause various other problems including public health problems, one of which is causing infectious diseases. In such a case, this research work proposes a mobile application for flood disaster monitoring that will help the Jakarta government to maintain the flood as real flood information in Jakarta. The Jakarta city government and the residents of the city of Jakarta can work hand in hand using mobile application technology to combat this flood problem and enable the Jakarta city government to quickly overcome any reported flood problems. The proposed mobile application was modeled with a use case and class diagrams. © 2021 IEEE.

关键词： Disasters

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Effect of think-pair-share in a large CS1 class: 83% sustained engagement

Effect of think-pair-share in a large CS1 class: 83% sustain...

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9th Annual International Computing Education Research Conference, ICER 2013

作者： Kothiyal, Aditi Majumdar, Rwitajit Murthy, Sahana Iyer, Sridhar Inter-disciplinary Programme in Educational Technology IIT Bombay India Department of Computer Science and Engineering IIT Bombay India

ISBN: (纸本)9781450322430

Think-Pair-Share (TPS) is a classroom-based active learning strategy, in which students work on a problem posed by the instructor, first individually, then in pairs, and finally as a classwide discussion. TPS has been recommended for its benefits of allowing students to express their reasoning, reflect on their thinking, and obtain immediate feedback on their understanding. While TPS is intended to promote student engagement, there is a need for research based evidence on the nature of this engagement. In this study, we investigate the quantity and quality of student engagement in a large CSl class during the implementation of TPS activities. We did classroom observations of students over a period of ten weeks and thirteen TPS activities. We determined patterns of student engagement in the three phases using a real-time classroom observation protocol that we developed and validated. We found that 83% of students on average were fully or mostly engaged. Predominant behaviors displayed were writing the solution to the problem (Think), discussing with neighbor or writing (Pair), and following class discussion (Share). We triangulated results with survey data of student perceptions. We find that students report being highly engaged for 62% during Think phase and 70% during Pair phase. Copyright © 2013 ACM.

关键词： Students

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Correction: Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes

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International journal of obesity (2005) 2025年第2期49卷 364-365页

作者： Arthur Leroy Varsha Gupta Mya Thway Tint Delicia Shu Qin Ooi Fabian Yap Ngee Lek Keith M Godfrey Yap Seng Chong Yung Seng Lee Johan G Eriksson Mauricio A Álvarez Navin Michael Dennis Wang Department of Computer Science The University of Manchester Manchester UK. Institute for Human Development and Potential Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. Bioinformatics Institute Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. Department of Paediatrics Yong Loo Lin School of Medicine National University of Singapore Singapore Republic of Singapore. Department of Paediatrics KK Women's and Children's Hospital Singapore Republic of Singapore. Duke-NUS Medical School Singapore Republic of Singapore. MRC Lifecourse Epidemiology Centre and NIHR Southampton Biomedical Research Centre University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK. Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Republic of Singapore. Division of Paediatric Endocrinology Department of Paediatrics Khoo Teck Puat-National University Children's Medical Institute National University Hospital National University Health System Singapore Republic of Singapore. Department of General Practice and Primary Health Care University of Helsinki Helsinki Finland. Folkhälsan Research Center Helsinki Finland. Department of Computer Science University of Sheffield Sheffield UK. Institute for Human Development and Potential Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. dennis_wang@sics.a-star.edu.sg. Bioinformatics Institute Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore. dennis_wang@sics.a-star.edu.sg. Department of Computer Science University of Sheffield Sheffield UK. dennis_wang@sics.a-star.edu.sg. National Heart and Lung Institute Imperial College London London UK. dennis_wang@sics.a-star.edu.sg.

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A Sensor Network-Based Data Stream Clustering Algorithm for Pervasive Computing

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电子学报(英文版) 2009年第2期18卷 255-258页

作者： YE Ning WANG Ruchuan Institute of Computer Science Nanjing University of Posts and Telecommunications Nanjing 210003 China Department of Information Science Nanjing College ]or Population Programme Management Nanjing 210042 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China

Pervasive computing is characterized by the integration with communication and digital media technology embedded to the people's living space. People can transparently access the digital service anywhere. Wireless sensor networks are a novel technology and have broad application prospects. With the maturity of the wireless sensor networks technology, pervasive computing is becoming a reality. It is become a new technology challenge to process the data streams of sensor networks for pervasive environment efficiently and to find useful knowledge in these data streams. A k-means data stream clustering algorithm based on sensor networks is presented. The main idea of this algorithm is to select the initial centroids according to the aggregation gain of the node, then to cluster the data stream using the average square error. The experimental results are showed that this algorithm is effective and efficient.

关键词：无线传感器网络聚类算法普适计算数据流数字媒体技术平均平方误差空间一体化网络技术

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Traffic Congestion Prevention Using Ant Colony Optimization 8

Traffic Congestion Prevention Using Ant Colony Optimization

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8th International Engineering Conference on Renewable Energy and Sustainability, ieCRES 2023

作者： Abusamra, Aiman Ashour, Abeer Ghazal, Mai Aldahdooh, Jehad Abuarja, Raghad Islamic University of Gaza Computer Engineering Dept. Gaza Palestine University of Helsinki Doctoral Programme in Computer Science Helsinki Finland Islamic University of Gaza Computer Engineering Gaza Palestine

ISBN: (纸本)9798350300758

Managing traffic congestion is crucial for improving mobility, reducing fuel consumption, and mitigating environmental impacts in urban areas. To address this challenge, we present a novel framework named TCP-ACO for detecting traffic congestion that classifies congestion into three distinct types: expected, unexpected, and real-time. The framework utilizes data from various sources, including databases, Ant colony optimization (ACO) systems, and computer vision techniques, to precisely detect and handle traffic congestion. Expected congestion is identified by analyzing historical traffic data and scheduled events, while unexpected congestion is detected by leveraging real-time data from ACO systems. Real-time congestion is detected by employing computer vision techniques, such as analyzing video footage from cameras or drones. The proposed framework has the potential, by recognizing and managing various types of congestion, to improve traffic flow, shorten travel times, and decrease environmental impacts. Additionally, it also offers a precise and effective solution for traffic congestion detection, which is a crucial aspect of smart city traffic management systems. Our analysis shows that the ACO algorithm adapted in TCP-ACO is more effective in finding the shortest path between two cities (result obtained: 4.014) compared to the result obtained from the shortest path technique compounded with computer vision (which yields a score of 6.224 when the path is free). This indicates the effectiveness of the proposed framework in addressing the challenges of traffic congestion, offering a promising solution for smart city traffic management systems to improve mobility and reduce environmental impacts in urban areas. © 2023 IEEE.

关键词： Traffic congestion

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A Classification: Using Back Propagation Neural Network Algorithm to Identify Cataract Disease 4

A Classification: Using Back Propagation Neural Network Algo...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Simamora, W.S. Lubis, R.S. Zamzami, E.M. Master Programme in Informatics Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

Artificial Neural Networks are often used in the fields of pattern recognition, speech, and image recognition, where high levels of computation are needed. One method that can be used is the Back-propagation Neural Network. The method can be used to identify several diseases, one of which is a cataract. A cataract is one of the most significant diseases that can cause blindness. Cataracts consist of three levels, namely mature cataracts, immature cataracts, and hyper-mature cataracts. The testing method uses two parameter values, namely epoch with value 1000,5000,10000 and learning rate with value 0.01, 0.05, 0.1. From the test, it was found that the best parameters of the above trial results were epoch with a value of 10000 and learning rate with a value of 0.1 on 80 experimental data. In experiments conducted to identify normal, mature, immature, and hyper mature obtained an accuracy of 100%, 95%, 85%, and 90%. The percentage value of the accuracy of the test results using the BPN method is 92.5%. © Published under licence by IOP Publishing Ltd.

关键词： Image recognition

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