Synovial Sarcoma Classification Technique Using Support Vector Machine and Structure Features

Arunachalam, P.; Janakiraman, N.; Sivaraman, Arun Kumar; Balasundaram, A.; Vincent, Rajiv; Rani, Sita; Dey, Barnali; Muralidhar, A.; Rajesh, M.

doi:10.32604/iasc.2022.022573

Cited by 13 publications

(4 citation statements)

References 39 publications

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“…By a realistic example discussed in [22][23][24][25][26][27][28][29], we further explain the possible application of the generation in this report.…”

Section: Introductionmentioning

confidence: 83%

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Dhanalakshmi¹,

Samanta²,

Sivaraman³

et al. 2023

Computer Systems Science and Engineering

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Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov's intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation process. Hesitant bipolar valued fuzzy set (HBVFS) is a generalization of HFS. This paper aims to introduce a general framework of multi-attribute group decision-making using social network. We propose two types of decision-making processes: Type-1 decision-making process and Type-2 decision-making process. In the Type-1 decision-making process, the experts' original opinion is proces for the final ranking of alternatives. In Type-2 decision making processs, there are two major aspects we consider. First, consistency tests and checking of consensus models are given for detecting that the judgments are logically rational. Otherwise, the framework demands (partial) decision-makers to review their assessments. Second, the coherence and consensus of several HBVFSs are established for final ranking of alternatives. The proposed framework is clarified by an example of software packages selection of a university.

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“…By a realistic example discussed in [22][23][24][25][26][27][28][29], we further explain the possible application of the generation in this report.…”

Section: Introductionmentioning

confidence: 83%

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Dhanalakshmi¹,

Samanta²,

Sivaraman³

et al. 2023

Computer Systems Science and Engineering

Self Cite

View full text Add to dashboard Cite

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“…In the realm of medical image scrutiny, the research on classifying Synovial Sarcoma using SVM highlights the potential of advanced techniques in cancer diagnosis [6]. By fusing discrete wavelet transformation and structural attributes, the proposed framework demonstrates the synergy between machine learning and digital histopathology.…”

Section: State-of-the-art Studies Regarding Support Vector Machinementioning

confidence: 99%

Optimization Strategy of Credit Scoring System based on Support Vector Machine

2024

AETR

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This article proposes a novel optimization strategy for credit scoring systems that exploits the capabilities of SVM. Focusing on the importance of personal credit scoring in today's credit dynamics, the article explores SVM's versatility in various domains through a literature review. The theoretical background underscores the unique approach and computational efficiency of SVM. The optimization strategy encompasses four critical aspects: debt solvency, earning potential, operational prowess, and growth capability using metrics such as asset-liability ratios. Experimental validation with credit card datasets from Australia and Germany illustrates the nuanced relationship between different K-values and performance metrics, and demonstrates the adaptability of SVM in improving credit scoring. In short, the article presents an original, comprehensive approach to credit risk management that integrates theoretical foundations, literature findings, and empirical experiments to improve the accuracy of credit scoring in the dynamic economic landscaper.

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“…A trust-based routing mechanism [19] was proposed for MANET. Initially, the challenging issues in MANET routing security were investigated.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Reputation Based Trust Mechanism for Mitigating Attacks in MANET

S.¹,

Vijayabhasker²

2023

Intelligent Automation &Amp; Soft Computing

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Mobile Ad-hoc Networks (MANET) usage across the globe is increasing by the day. Evaluating a node's trust value has significant advantages since such network applications only run efficiently by involving trustable nodes. The trust values are estimated based on the reputation values of each node in the network by using different mechanisms. However, these mechanisms have various challenging issues which degrade the network performance. Hence, a novel Quality of Service (QoS) Trust Estimation with Black/Gray hole Attack Detection approach is proposed in this research work. Initially, the QoS-based trust estimation is proposed by using a Fuzzy logic scheme. The trust value of each node is estimated by using each node's reputation values which are determined based on the fuzzy membership function values and utilizing QoS parameters such as residual energy, bandwidth, node mobility, and reliability. This mechanism prevents only the black hole attack in the network during transmission. But, the gray hole attacks are not identified which in turn increases the packet drop rate significantly. Hence, the gray hole attack is also detected based on the Kullback-Leibler (KL) divergence method used for estimating the statistical measures. Additional QoS metrics are considered to prevent the gray hole attack, such as packet loss, packet delivery ratio, and delay for each node. Thus, the proposed mechanism prevents both black hole and gray hole attacks simultaneously. Finally, the simulation results show that the effectiveness of the proposed mechanism compared with the other trust-aware routing protocols in MANET.

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Synovial Sarcoma Classification Technique Using Support Vector Machine and Structure Features

Cited by 13 publications

References 39 publications

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Optimization Strategy of Credit Scoring System based on Support Vector Machine

Fuzzy Reputation Based Trust Mechanism for Mitigating Attacks in MANET

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