Jun Ye

Bernard J. Jansen

Haibo Liang

This book contains papers presented at the International Conference on Cognitive based Information Processing and Applications (CIPA) held during August 21, 2021, online conference (since COVID 19), which is divided into a 2-volume book. The papers in the second volume represent the various technological advancements in network information processing, graphics and image processing, medical care, machine learning, smart cities. It caters to postgraduate students, researchers, and practitioners specializing and working in the area of cognitive-inspired computing and information processing.

Volume 2

International Conference on Cognitive based Information Processing and Applications (CIPA 2021)

Qingyuan Zhou

This book contains papers presented at the 2nd International Conference on Cognitive based Information Processing and Applications (CIPA) in Changzhou, China, from September 22 to 23, 2022. The book is divided into a 2-volume series and the papers represent the various technological advancements in network information processing, graphics and image processing, medical care, machine learning, smart cities. It caters to postgraduate students, researchers, and practitioners specializing and working in the area of cognitive-inspired computing and information processing.

Proceedings of the 2nd International Conference on Cognitive Based Information Processing and Applications (CIPA 2022)

Jiqian Chen 

 Shigui Du 

A reﬁned single-valued/interval neutrosophic set is very suitable for the expression and application of decision-making problems with both attributes and sub-attributes since it is described by its reﬁned truth, indeterminacy, and falsity degrees.

Vector Similarity Measures between Reﬁned Simpliﬁed Neutrosophic Sets and Their Multiple Attribute Decision-Making Method

Three Essays on China's Industrial Reforms in the 1990s

Liping Zhao

Wei Hu

Hua Peng

Keli Hu

Jiatian Pi

An online neutrosophic similarity-based objectness tracking with a weighted multiple instance learning algorithm (NeutWMIL) is proposed. Each training sample is extracted surrounding the object location, and the distribution of these samples is symmetric. To provide a more robust weight for each sample in the positive bag, the asymmetry of the importance of the samples is considered. The neutrosophic similarity-based objectness estimation with object properties (super straddling) is applied.

Online Visual Tracking ofWeighted Multiple Instance Learning via Neutrosophic Similarity-Based Objectness Estimation

Florentin Smarandach

The concept of Information is to disseminate scientific results achieved via experiments and theoretical results in depth. It is very important to enable researchers and practitioners to learn new technology and findings that enable development in the applied field.

Neutrosophic Information Theory and Applications

Changxing Fan

En Fan

Based on the multiplicity evaluation in some real situations, this paper firstly introduces a single-valued neutrosophic multiset (SVNM) as a subclass of neutrosophic multiset (NM) to express the multiplicity information and the operational relations of SVNMs.

The Cosine Measure of Single-Valued Neutrosophic Multisets for Multiple Attribute Decision-Making

Lilian Shi 

The neutrosophic cubic set can describe complex decision-making problems with its single-valued neutrosophic numbers and interval neutrosophic numbers simultaneously. The Dombi operations have the advantage of good flexibility with the operational parameter. In order to solve decision-making problems with flexible operational parameter under neutrosophic cubic environments, the paper extends the Dombi operations to neutrosophic cubic sets and proposes a neutrosophic cubic Dombi weighted arithmetic average (NCDWAA) operator and a neutrosophic cubic Dombi weighted geometric average (NCDWGA) operator. Then, we propose a multiple attribute decision-making (MADM) method based on the NCDWAA and NCDWGA operators. Finally, we provide two illustrative examples of MADM to demonstrate the application and effectiveness of the established method.

Dombi Aggregation Operators of Neutrosophic Cubic Sets for Multiple Attribute Decision-Making

Keli Hu 

En Fan 

Changxing Fan 

Shigen Shen 

 Yuzhang Gu 

Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions.

Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking

Jihong Chen  

Kai Xue

Tiancun Huang

Yan Tian

Chengying Hua

Yuhua Zhu

Smart ports represent the current trend of port development. Intelligent operations reduce the daily production cost of ports, facilitate ecient production, strengthen the risk mitigation ability and comply with the requirements for long-term development. However, a systematic and scientific smart port evaluation method is missing to nail down the evaluation indicators of a smart port and enable accurate evaluation of a port’s degree of intelligence. This paper analyzes the concept of the smart port, establishes a set of smart port evaluation indicator systems, and applies a single-valued neutrosophic exponential similarity measure to port evaluation to enable quantitative evaluation of port integrity. This evaluation method is capable of decision-making in the event of incomplete, uncertain, and inconsistent information during general evaluation, opening up a new method for smart port evaluation, and acting as a helpful tool for ports to carry out improvements during actual application.

Simplified Neutrosophic Exponential Similarity Measures for Evaluation of Smart Port Development

Jun Ye

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