Computational Intelligence in Analytics and Information Systems: Volume 1: Data Science and Ai​, ​selected Papers from Ciais-2021

The new book presents a valuable selection of state-of-the-art technological advancements using the concepts of AI and machine learning, highlighting the use of predictive analytics of data to find timely solutions to real-time problems. It helps to identify applicable approaches in order to enhance, automate, and develop effective solutions to challenges in data science and artificial intelligence. The various novel approaches include applications in healthcare, natural language processing, and smart cities. As such, the book is divided into sections that address:

• Computational Intelligence in Image Processing
• Computational Intelligence in Healthcare
• Techniques for Natural Language Processing
• Computational Intelligence in Smart Cities

The very diverse range of topics include AI and machine learning applications for

• In security: For using digital image processing for image fusion (face recognition, feature extraction, object detection as well tracking, moving object identification), for person re-identification for security purposes.
• In healthcare and medicine: For diagnosis and prediction of breast cancer, other cancers, diabetes, heart disease; for predicting susceptibility to COVID-19; for prediction of mood and anxiety disorders.
• In agriculture: For prediction of crop profit; for prediction of cropping patterns and recommendation for crop cultivation.
• In traffic science/smart cities: For understanding road scene images, for detection of traffic signs, for devising a fog-based intelligent traffic phase timing regulation system
• In language/speech/text: For automatic text summarization, for document indexing for unstructured data, for speech/accent recognition, for sound separation, for American Sign Language interpretation for nonsigners, for emotional recognition and analysis through speech, body postures with facial expressions, and other body movements (to improve the performance of virtual personal assistants / emotion recognition using speech, body postures with facial expressions and other body movements.

This volume offers valuable information for researchers working in interdisciplinary or multidisciplinary areas of healthcare, image analysis, natural language processing, and smart cities. This includes academicians, people in industry, and students with engineering background with research interest in these areas.

These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems (CIAIS- 2021), held in April 2021 at Manav Rachna University, India. Together with Volume 2: Advances in Digital Transformation, this 2-volume set offers an abundacne of valuable information on emerging technologies in computational intelligence in information systems focusing on data science and artificial intelliegence.

這本新書介紹了一系列利用人工智慧和機器學習概念的最新技術進展，強調使用預測分析來找到即時問題的及時解決方案。它有助於識別適用的方法，以增強、自動化和開發數據科學和人工智慧領域的有效解決方案。這些新穎的方法包括在醫療保健、自然語言處理和智慧城市等領域的應用。因此，這本書分為以下幾個部分：

- 影像處理中的計算智能
- 醫療保健中的計算智能
- 自然語言處理技術
- 智慧城市中的計算智能

這些非常多樣化的主題包括以下人工智慧和機器學習應用：

- 在安全領域：使用數字影像處理進行影像融合（人臉識別、特徵提取、物體檢測和追蹤、移動物體識別），用於安全目的的人員重新識別。
- 在醫療保健和醫學領域：用於乳腺癌、其他癌症、糖尿病、心臟病的診斷和預測；用於預測對COVID-19的易感性；用於預測情緒和焦慮疾患。
- 在農業領域：用於預測作物利潤；用於預測作物種植模式並提供作物種植建議。
- 在交通科學/智慧城市領域：用於理解道路場景影像，檢測交通標誌，設計基於霧的智能交通相位定時調節系統。
- 在語言/語音/文本領域：用於自動文本摘要，用於非結構化數據的文檔索引，用於語音/口音識別，用於聲音分離，用於非手語使用者的美國手語解釋，用於通過語音、身體姿勢和面部表情以及其他身體動作進行情緒識別和分析（以提高虛擬個人助理/情緒識別的性能）。

這本書為在醫療保健、影像分析、自然語言處理和智慧城市等跨學科或多學科領域工作的研究人員提供了有價值的信息。這包括學者、工業界人士和具有工程背景且對這些領域有研究興趣的學生。

這些經過同行評審的章節是從2021年4月在印度的Manav Rachna大學舉行的國際計算智能分析和信息系統會議（CIAIS-2021）中選出的。與《第二卷：數字轉型的進展》一起，這套兩卷本提供了關於數據科學和人工智慧的計算智能在信息系統中新興技術的豐富信息。

Hardeo Kumar Thakur, PhD, is working as an Associate Professor in the Department of Computer Science and Technology of Manav Rachna University, Faridabad, India. With over 10 years of teaching and research experience, he focuses on data mining, dynamic graph mining, machine learning and big data analytics.

Manpreet Kaur, PhD, is an Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She has more than 14 years of teaching and research experience. Her current research is on machine learning, deep learning, and natural language processing.

Parneeta Dhaliwal, PhD, has over 16 years of experience in teaching and research. Presently, she is an Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She is also Head of the Research Cluster of Computing (RCC) to facilitate students in their research projects.

Rajeev Kumar Arya, PhD, is an Assistant Professor with the Department of Electronics and Communication Engineering at National Institute of Technology, Patna, India. His current research interests are in wireless communication, soft computing techniques, cognitive radio, signal processing, communication systems, and circuit design.

Joan Lu, PhD, is a Professor in the Department of Computer Science and the Research Group Leader of Information and System Engineering in the Centre of High Intelligent Computing at the University of Huddersfield, UK, having previously been team leader in the IT Department of the Charlesworth Group.

Hardeo Kumar Thakur, 博士，目前在印度法里達巴德的Manav Rachna大學的計算機科學與技術系擔任副教授。他擁有超過10年的教學和研究經驗，專注於數據挖掘、動態圖挖掘、機器學習和大數據分析。

Manpreet Kaur, 博士，是印度Manav Rachna大學計算機科學與技術系的副教授。她擁有超過14年的教學和研究經驗。她目前的研究方向是機器學習、深度學習和自然語言處理。

Parneeta Dhaliwal, 博士，擁有超過16年的教學和研究經驗。目前她是印度Manav Rachna大學計算機科學與技術系的副教授。她還擔任計算研究群集（RCC）的負責人，以協助學生進行研究項目。

Rajeev Kumar Arya, 博士，是印度帕特納國立工程學院電子與通信工程系的助理教授。他目前的研究興趣包括無線通信、軟計算技術、認知無線電、信號處理、通信系統和電路設計。

Joan Lu, 博士，是英國哈德斯菲爾德大學計算機科學系的教授，也是高智能計算中心信息與系統工程研究小組的研究組長，之前曾擔任查爾斯沃思集團IT部門的團隊負責人。