Current Chinese Computer Science - Current Issue
Volume 2, Issue 1, 2022
- Computer & Information Sciences
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Similarity Measures and Their Applications in Multiple Attribute Decision-Making Under Cubic Hesitant Environment
More LessAuthors: Yohannes Belayneh, Rui Yong and Yingying ZhangBackgroundCubic Hesitant Fuzzy Set (CHFS) is a hybrid set that can express uncertain and hesitancy fuzzy information simultaneously.
ObjectiveIn this paper, we introduced three trigonometric similarity measures (e.g., cosine, tangent, and cotangent similarity measures) to measure the degree of similarity between the alternative and the ideal set under the CHFS environment. Various desirable characteristics of the cubic hesitant fuzzy set are studied. Then, we developed multiple attribute decision-making methods based on the weighted cosine, tangent, and cotangent similarity measures of CHFSs.
MethodsIn this research, we presented the similarity measures of CHFSs based on the cosine, tangent, and cotangent functions. Then, illustrative examples of construction project management with CHFS information are presented to show the effectiveness and feasibility of the proposed Multiattribute Decision-making (MADM) method under CHFS environments.
ResultsBased on the weighted similarity measures between each alternative and the ideal set, this method provides the ranking order according to the values of their similarity measure. The best alternatives can be easily identified from the ranking order obtained.
ConclusionBased on the comparison of the decision results obtained, the tangent and cotangent similarity measures are better in similarity identification than the cosine similarity measure for solving MADM problems under a cubic hesitant environment.
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Towards Highly Intelligent Image Processing Techniques for Rice Diseases Identification: A Review
More LessBy R. ManavalanBackgroundRice is cultivated worldwide as one of the primary food crops. The responsible factors that rigorously affect rice crops' production are pests and various rice plant diseases, leading to considerable reduction in the agrarian and global economy. More sustainable farming methods for determining disease levels and the quality of paddy plants will be essential in the future.
ObjectiveThe disease discovery in rice crops by naked eyes may result in erroneous pesticide measurements. Therefore, early diagnosis of rice diseases can expedite disease control by properly selecting pest management methods to maximize the rice yield to cope with the demand of the world's growing population. A literature search is conducted and identifies 68 peer-reviewed research studies published in the period between 2007 and 2021, focusing on early disease detection of rice crops to maximize productivity.
ConclusionThis study has identified several key issues that must be resolved at each step of the computer-assisted diagnostic system to recognize diseases in paddy crops. Study results show that automated disease diagnosing techniques are still immature for rice plants. Hence, the ingenious design and evolution of a novel fully-automated farming system are widely essential as innovative methods for addressing and resolving diseases in the paddy crop to offer sustainability and productivity benefits to the agrarian sector.
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An Image-Based Information Hiding Approach with Chaotic Systems and Optimized Security
More LessAuthors: Abdiqani A. Saliban and Yinglei SongBackgroundRecently, information hiding has become an important approach to securely storing and transmitting important information in digital media.
ObjectivesThis paper proposes a new approach to hide information in a color image with optimized security.
MethodsThe approach performs the hiding in two phases. Firstly, the information that needs to be hidden in an image is represented by a sequence of binary bits, and the sequence is shuffled and encrypted with a set of three-dimensional chaotic systems. Secondly, the binary bits in the shuffled and encrypted sequence are hidden into the R, G, and B components of the pixels in the given color image with a dynamic programming approach.
ResultsExperimental results show that the proposed approach can securely hide information in a color image without generating significant changes in the visual contents of a color image. The analysis also shows that the proposed approach is robust against potential attacks.
ConclusionThe proposed approach is thus practically useful for applications aimed at image-based information hiding.
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An Overview of Face Image Forgery Detection
More LessAuthors: Defen He, Shuai Liu, Xin Jin, Shanshan Huang and Qian JiangWith the development of face forgery techniques, the spread and malicious abuse of forged images have become a thought-provoking problem, and the face forgery detection technique has also attracted people's attention. Academia has carried out in-depth research and discussion on detection techniques. This review discussed different face forgery methods and detection techniques. Four categories of detection methods are introduced: 1) detection method based on spatial domain, 2) detection method based on the frequency domain, 3) detection method based on biological information, and 4) detection method of multiple feature domains. This paper discussed each detection method's evolution and development in recent years. We paid special attention to the detection method of multiple feature domains and focused on the progress that has been made and the challenges it faced. In addition, this paper discussed open issues and future development trends that should be paid attention to in this field.
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