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重庆邮电大学学报（自然科学版） 2010年第6期22卷 720-723,760页

作者： sankar k Pal Indian Statistical Institute Calcutta Indian

Machine intelligence,is out of the system by the artificial intelligence *** is usually achieved by the average computer *** sets and Information Granules in uncertainty management and soft computing and granular computing is widely used in many fields,such as in protein sequence analysis and biobasis determination,TSM and Web service classification Etc.

关键词： machine intelligence rough sets information granules rough-fuzzy case generation protein sequence analysis and biobasis determination TSM web service classification

A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

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Intelligent Automation & Soft Computing 2023年第3期35卷 3331-3348页

作者： R.T.Pavendan k.sankar k.A.Varun kumar Department of Mathematics College of EngineeringAnna UniversityChennai600025India Department of Networking and Communications School of ComputingSRM Institute of Science and TechnologyKattankulathur602203India

Attacks on the cyber space is getting exponential in recent *** penetrations and breaches are real threats to the individuals and *** security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats(APTs)they *** APTs are targeted,more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing ***,there is a need for an effective defense system that can achieve a complete reliance of *** address the above-mentioned issues,this paper proposes a novel honeypot system that tracks the anonymous behavior of the APT *** key idea of honeypot leverages the concepts of graph theory to detect such targeted *** proposed honey-pot is self-realizing,strategic assisted which withholds the APTs actionable tech-niques and observes the behavior for analysis and *** proposed graph theory based self learning honeypot using the resultsγ(C(n,1)),γc(C(n,1)),γsc(C(n,1))outperforms traditional techniques by detecting APTs behavioral with detection rate of 96%.

关键词： Graph theory Domination Connected Domination Secure Connected Domination honeypot self learning ransomware

Lichens of the Sirumalai hills,Eastern Ghats with one genus and six species new to India

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Studies in Fungi 2021年第1期6卷 204-212页

作者： Nayaka S Joseph S Rajaram Sk Natesan S sankar k David MLR Upreti Dk Lichenology Laboratory CSIR-National Botanical Research InstituteRana Pratap MargLucknow-226001Uttar PradeshIndia Department of Biotechnology Kamaraj College of Engineering and TechnologyK.VellakulamNear VirudhunagarMadurai-625701Tamil NaduIndia

Lichens of Sirumalai hills are reported here for the first *** biota comprised of 95 *** genus Japewiella is reported for the first time in India and is represented by ***(***.)***,the following six taxa including one variety are new to India *** atra(Pers.)***.,Graphis brevicarpa ***.,kashiw.&***,Micarea erratica(körb.)Hertel,Rambold&Pietschm.,Pertusaria cicatricosa *** ***,Elix&Streimam,Porina subargillacea Müll Arg.,and Pyxine schmidtii *** accounts for all the new records to India are provided to facilitate their *** redingeri Grube and Lepraria caesiella *** are reported for the first time from south *** all above,29 species are recorded for the first time from the state of Tamil *** lichen biota of the area is primarily corticolous in habitats and dominated by crustose form.

关键词： lichenized fungi new records south India Tamil Nadu tropical lichens

Soft Computing, Machine Intelligence and Data Mining: Features, Applications and Prospects

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Soft Computing, Machine Intelligence and Data Mining: Featur...

A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

Rough集前景——粒计算理论国际论坛（2006）

作者： sankar k. Pal Indian Statistieal Institute Indian

＜正＞Different components of soft computing （e.g., fuzzy logic, artificial neural networks, rough sets and genetic algorithms） and machine intelligence and their relevance to data mining and knowledge discovery from pattern recognition points of view are explained. Different features of these tools are explained conceptually. Ways of integrating different tools for application specific merits are described. Problems like case （prototype） generation, rule generation, and classification are considered in general. Some of such integrations are explained along with their merits and suitability for data mining with real life applications. Significance of granular computing through rough sets is given emphasis. Finally, the application in bioinformatics and webmining are discussed.

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Computers, Materials & Continua 2024年第5期79卷 3111-3138页

作者： Sujithra sankar S.Sathyalakshmi Department of Computer Applications Hindustan Institute of Technology and ScienceChennaiTamil NaduIndia Department of Computer Engineering Hindustan Institute of Technology and ScienceChennaiTamil NaduIndia

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable *** predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce ***,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and *** paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present *** study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction *** the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the *** original dataset is used in trainingmachine learning models,and further used in generating SHAP values *** the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based *** new integrated dataset is used in re-training the machine learning *** new SHAP values generated from these models help in validating the contributions of feature sets in predicting *** conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making *** this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the *** study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of *** proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area un

关键词： Explainable AI machine learning clinical decision support systems thyroid cancer association-rule based framework SHAP values classification and prediction

RNA Secondary Structure Prediction in Soft Computing Framework: A Review

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RNA Secondary Structure Prediction in Soft Computing Framewo...

Acanthus ilicifolius plant extract prevents DNA alterations in a transplantable Ehrlich ascites carcinoma-bearing murine model

2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Shubhra sankar Ray Munia Bachhar sankar k. Pal Center for Soft Computing Research Machine Intelligence Unit Indian Statistical Institute Kolkata 700108 India

This article provides an overview of the application of certain soft computing tools namely, genetic algorithms （GAs）, simulated annealing （SA）, and artificial neural networks （ANNs） in certain tasks of RNA secondary structure prediction. Different tasks like prediction of helix, bulge, hairpin curve, internal loop, and multiloop are, first of all, described along with their basic features. The relevance of using soft computing tools to these problems is then mentioned. These are followed by different approaches along with their merits for addressing some of the aforesaid tasks. Finally some limitations of the current research activity are provided.

关键词： RNA combinatorial optimization dynamic programming soft computing genetic algorithms simulated annealing neural networks.

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World Journal of Gastroenterology 2007年第48期13卷 6538-6548页

作者： Tridib Chakraborty Dipak Bhuniya Mary Chatterjee Mosiur Rahaman Dipak Singha Baidya Nath Chatterjee Subrata Datta Ajay Rana kartick Samanta Sunil Srivastawa sankar k Maitra Malay Chatterjee Chemical Carcinogenesis and Chemoprevention Laboratory Division of Biochemistry Department of Pharmaceutical Technology Jadavpur University Division of Medicinal Chemistry Indian Institute of Chemical Biology Jadavpur East Calcutta Girls' College Lake Town Cell Signaling Laboratory Cardiovascular and Cancer Research Institute College of Medicine The Texas A&M University System HSC Temple TX 76504 United States

AIM： To investigate the chemopreventive efficacy of the Indian medicinal plant Acanthus ilicifolius L Acanthaceae in a transplantable Ehrlich ascites carcinoma （EAC）- bearing murine model.METHODS： Male Swiss albino mice were divided into four groups： Group A was the untreated normal control; Group B was the EAC control mice group that received serial, intraperitoneal （ip） inoculations of rapidly proliferating 2 × 10^5 viable EAC cells in 0.2 mL of sterile phosphate buffered saline; Group C was the plant extract-treated group that received the aqueous leaf extract （ALE） of the plant at a dose of 2.5 mg/kg body weight by single ip injections, once daily for 10, 20 and 30 consecutive days following tumour inoculation （ALE control）; and Group D was the EAC ＋ ALE- treatment group. The chemopreventive potential of the ALE was evaluated in a murine model by studying various biological parameters and genotoxic markers, such as tumour cell count, mean survival of the animals, haematological indices, hepatocellular histology, immunohistochemical expression of liver metallothionein （MT） protein, sister-chromatid exchanges （SCEs）, and DNA alterations.RESULTS： Treatment of the EAC-bearing mice with the ALE significantly （P 〈 0.001） reduced viable tumour cell count by 68.34% （228.7 × 10^6 ± 0.53） when compared to EAC control mice （72.4 × 10^6 ± 0.49）, and restored body and organ weights almost to the normal values. ALE administration also increased （P 〈 0.001） mean survival of the hosts from 35 ± 3.46 d in EAC control mice to 83 ± 2.69 d in EAC ＋ ALE-treated mice. Haematological indices also showed marked improvement with administration of ALE in EAC-bearing animals. There was a significant increase in RBC count （P 〈 0.001）, hemoglobin percent （P 〈 0.001）, and haematocrit value （P 〈 0.001） from 4.3 ± 0.12, 6.4 ± 0.93, and 17.63 ± 0.72 respectively in EAC control mice to 7.1 ± 0.13, 12.1 ± 0.77, and 30.23 ± 0.57 respectively in EAC ＋ ALE-treated group, along with concurrent de

关键词： Acanthus ilicifolius Chemoprevention DNA strand-breaks Ehrlich ascites carcinoma Haematological indices Medicinal plants Metallothionein Sister- chromatid exchange Transplantable tumour

Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

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Energy Geoscience 2024年第2期5卷 202-213页

作者： Anjali Dixit Animesh Mandal Shib sankar Ganguli Department of Earth Sciences Indian Institute of Technology KanpurKanpur208016India Marine and Deep Seismic CSIR-NGRIHyderabad500007India

Reservoir heterogeneities play a crucial role in governing reservoir performance and ***,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive *** researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir ***,these attributes take seismic data as input and might not be sensitive to lateral lithology *** incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance *** proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as *** evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,*** study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional *** addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir *** study also suggests a well-bounded potential reservoir facies distribution along the parallel fault ***,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

关键词： Seismic texture attributes Seismic acoustic impedance Multi-directional texture attributes Reservoir heterogeneity Reservoir characterization Poseidon field

Chemically Radiative MHD Flow of a Micropolar Nanofluid over a Stretching/ Shrinking Sheet with a Heat Source or Sink

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Fluid Dynamics & Materials Processing 2024年第2期20卷 257-274页

作者： Parakapali Roja Shaik Mohammed Ibrahim Thummala sankar Reddy Giulio Lorenzini Department of Mathematics Annamacharya Institute of Technology and SciencesKadapa516126India Department of Engineering Mathematics College of EngineeringKoneru Lakshmaiah Education FoundationVaddeswaram522302India Department of Mathematics Annamacharya Institute of Technology and SciencesKadapa516003India Department of Engineering and Architecture University of ParmaParma43124Italy

This study examines the behavior of a micropolar nanoﬂuidﬂowing over a sheet in the presence of a transverse magneticﬁeld and thermal *** addition,chemical(ﬁrst-order homogeneous)reactions are taken into account.A similarity transformation is used to reduce the system of governing coupled non-linear partial differ-ential equations(PDEs),which account for the transport of mass,momentum,angular momentum,energy and species,to a set of non-linear ordinary differential equations(ODEs).The Runge-kutta method along with shoot-ing method is used to solve *** impact of several parameters is *** is shown that the micro-rota-tional velocity of theﬂuid rises with the micropolar ***,the radiation parameter can have a remarkable inﬂuence on theﬂow and temperature proﬁles and on the angular momentum distribution.

关键词： Chemical(ﬁrst order homogeneous)reaction magnetohydrodynamics micropolar nanoﬂuid stretching/shrinking sheet heat source

Emergence of biomass-derived single-atom catalysts for platform chemicals production

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Journal of Bioresources and Bioproducts 2024年第2期9卷 127-129页

作者： Adrian Chun Minh Loy sankar Bhattacharya Department of Chemical and Biological Engineering Monash UniversityClayton 3800VictoriaAustralia

The envisioned exponential growth in the utilization of single-atom catalysts(SACs)has recently emerged as a frontier in the spectrum of material *** is attributed to the distinctive properties of SACs,which encompass 100%atomic efficiency,superior selective performance,tunable coordination environment,and unique electronic structures(Wu et al.,2022b;Loy et al.,2023;Wang et al.,2023).The concept of single-atom isolation was initially introduced by Qiao et al.(2011),with the objective to explore the superior catalytic activity of Pt single-atom compared to Pt nanoparticles/nanoclusters in CO ***,Zhou et al.(2019)in-novatively developed the biomass-derived CO-based SACs and introduced for the oxidative esterification of *** there are many good pieces of news on the SACs,the large-scale fabrication of SACs remains a formidable challenge,impeding their potential to drive scalable production of drop-in *** primary challenge lies in the cost-intensive process of reducing the size of embedded metal particles to sub-angstrom dimensions,a necessary step for creating well-dispersed atomic active ***,this complexity arises from the inherent behavior of individual atoms that are inclined to migrate and cluster into nanoparticles due to their high surface free energy(Chen et al.,2021).

关键词： dimensions frontier attributed