Hongzhi Wang

Zhixin Qi

Zejiao Dong

In both the database and machine learning communities, data quality has become a serious issue which cannot be ignored. In this context, we refer to data with quality problems as “dirty data.” Clearly, for a given data mining or machine learning task, dirty data in both training and test datasets can affect the accuracy of results. Accordingly, this book analyzes the impacts of dirty data and explores effective methods for dirty data processing. Although existing data cleaning methods improve data quality dramatically, the cleaning costs are still high. If we knew how dirty data affected the accuracy of machine learning models, we could clean data selectively according to the accuracy requirements instead of cleaning all dirty data, which entails substantial costs. However, no book to date has studied the impacts of dirty data on machine learning models in terms of data quality. Filling precisely this gap, the book is intended for a broad audience ranging from researchers inthe database and machine learning communities to industry practitioners. Readers will find valuable takeaway suggestions on: model selection and data cleaning; incomplete data classification with view-based decision trees; density-based clustering for incomplete data; the feature selection method, which reduces the time costs and guarantees the accuracy of machine learning models; and cost-sensitive decision tree induction approaches under different scenarios. Further, the book opens many promising avenues for the further study of dirty data processing, such as data cleaning on demand, constructing a model to predict dirty-data impacts, and integrating data quality issues into other machine learning models. Readers will be introduced to state-of-the-art dirty data processing techniques, and the latest research advances, while also finding new inspirations in this field.

Dirty Data Processing for Machine Learning

Xianhua Song

Zeguang Lu

Zhiwen Yu

Qilong Han

Bin Guo

Xiaokang Zhou

This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections: Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis. Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.

9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023, Harbin, China, September 22–24, 2023, Proceedings, Part I

Data Science

Seyed Mostafa Kia

Mohamad Habes

Hassan Mohy-ud-Din

Saima Rathore

Ahmed Abdulkadir

Cher Bass

Jane Maryam Rondina

Chantal Tax

Thomas Wolfers

Madhura Ingalhalikar

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.

Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology

Gang Wang

Chengyi Hou

Provides the state-of-the-art on wearable technology for smart clothing The book gives a coherent overview of recent development on flexible electronics for smart clothing with emphasis on wearability and durability of the materials and devices. It offers detailed information on the basic functional components of the flexible and wearable electronics including sensing, systems-on-a-chip, interacting, and energy, as well as the integrating and connecting of electronics into textile form. It also provides insights into the compatibility and integration of functional materials, electronics, and the clothing technology. Flexible and Wearable Electronics for Smart Clothing offers comprehensive coverage of the technology in four parts. The first part discusses wearable organic nano-sensors, stimuli-responsive electronic skins, and flexible thermoelectrics and thermoelectric textiles. The next part examines textile triboelectric nanogenerators for energy harvesting, flexible and wearable solar cells and supercapacitors, and flexible and wearable lithium-ion batteries. Thermal and humid management for next-generation textiles, functionalization of fiber materials for washable smart wearable textiles, and flexible microfluidics for wearable electronics are covered in the next section. The last part introduces readers to piezoelectric materials and devices based flexible bio-integrated electronics, printed electronics for smart clothes, and the materials and processes for stretchable and wearable e-textile devices. -Presents the most recent developments in wearable technology such as wearable nanosensors, logic circuit, artificial intelligence, energy harvesting, and wireless communication -Covers the flexible and wearable electronics as essential functional components for smart clothing from sensing, systems-on-a-chip, interacting, energy to the integrating and connecting of electronics -Of high interest to a large and interdisciplinary target group, including materials scientists, textile chemists, and electronic engineers in academia and industry Flexible and Wearable Electronics for Smart Clothing will appeal to materials scientists, textile industry professionals, textile engineers, electronics engineers, and sensor developers.

Flexible and Wearable Electronics for Smart Clothing

Haoliang Qi

Wanxiang Che

Zhaowen Qiu

Leilei Kong

Zhongyuan Han

Junyu Lin

This book constitutes the refereed proceedings of the International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015, held in Harbin, China, in January 2015. The 61 revised full papers presented were carefully reviewed and selected from 200 submissions. The papers cover a wide range of topics related to intelligent computation in Big Data era, such as artificial intelligence, machine learning, algorithms, natural language processing, image processing, MapReduce, social network.

International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015, Harbin, China, January 10-12, 2015, Proceedings

Intelligent Computation in Big Data Era

Guanglu Sun

Pinle Qin

This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.

6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part II

Min Li

Beiji Zou

Wei Xie

This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017. The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 submissions. The papers cover a wide range of topics related to Basic Theory and Techniques for Data Science including Mathematical Issues in Data Science, Computational Theory for Data Science, Big Data Management and Applications, Data Quality and Data Preparation, Evaluation and Measurement in Data Science, Data Visualization, Big Data Mining and Knowledge Management, Infrastructure for Data Science, Machine Learning for Data Science, Data Security and Privacy, Applications of Data Science, Case Study of Data Science, Multimedia Data Management and Analysis, Data-driven Scientific Research, Data-driven Bioinformatics, Data-driven Healthcare, Data-driven Management, Data-driven eGovernment, Data-driven Smart City/Planet, Data Marketing and Economics, Social Media and Recommendation Systems, Data-driven Security, Data-driven Business Model Innovation, Social and/or organizational impacts of Data Science.

Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22–24, 2017, Proceedings, Part I

Zhipeng Cai

Hong Gao

Chaokun Wang

Siyao Cheng

This book constitutes the refereed proceedings of the 9th International Conference on Wireless Algorithms, Systems and Applications, WASA 2014, held in Harbin, China, in June 2014. The 41 revised full papers presented together with 30 invited papers were carefully reviewed and selected from 134 submissions. The papers cover a wide range of topics including cognitive radio networks, wireless sensor networks, cyber-physical systems, distributed and localized algorithm design and analysis, information and coding theory for wireless networks, localization, mobile cloud computing, topology control and coverage, security and privacy, underwater and underground networks, vehicular networks, information processing and data management, programmable service interfaces, energy-efficient algorithms, system and protocol design, operating system and middle-ware support and experimental test-beds and models.

9th International Conference, WASA 2014, Harbin, China, June 23-25, 2014, Proceedings

Wireless Algorithms, Systems, and Applications

Xiaolan Xie

Rui Mao

This two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.

5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings

Luping Zhou

Duygu Sarikaya

Stefanie Speidel

Anand Malpani

Daniel Hashimoto

Tommy Löfstedt

Kerstin Ritter

This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment. MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.

Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings

OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging

Hongzhi Wang

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