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Deep Convolutional Neural Networks for south Indian Mango Leaf Disease Detection and Classification

Computers, Materials & Continua 2023年第12期77卷 3593-3618页

作者： shaik Thaseentaj s.sudhakar ilango school of Computer science and Engineering VIT-AP UniversityAmaravatiVijayawada522237India

The south Indian mango industry is confronting severe threats due to various leaf diseases,which significantly impact the yield and quality of the *** management and prevention of these diseases depend mainly on their early identification and accurate *** central objective of this research is to propose and examine the application of Deep Convolutional Neural Networks(CNNs)as a potential solution for the precise detection and categorization of diseases impacting the leaves of south Indian mango *** study collected a rich dataset of leaf images representing different disease classes,including Anthracnose,Powdery Mildew,and Leaf *** maintain image quality and consistency,pre-processing techniques were *** then used a customized deep CNN architecture to analyze the accuracy of south Indian mango leaf disease detection and *** proposed CNN model was trained and evaluated using our collected *** customized deep CNN model demonstrated high performance in experiments,achieving an impressive 93.34%classification *** result outperformed traditional CNN algorithms,indicating the potential of customized deep CNN as a dependable tool for disease *** proposed model showed superior accuracy and computational efficiency performance compared to other basic CNN *** research underscores the practical benefits of customized deep CNNs for automated leaf disease detection and classification in south Indian mango *** findings support deep CNN as a valuable tool for real-time interventions and improving crop management practices,thereby mitigating the issues currently facing the south Indian mango industry.

关键词： south Indian mango tree customized deep CNN mango leaf disease classification accuracy

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shrinking fat,healing liver:unlocking the metabolic dysfunction associated steatohepatitis puzzle

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Hepatobiliary surgery and Nutrition 2024年第1期13卷 132-135页

作者： sudhakar K.Venkatesh Ilkay s.Idilman Jiahui Li Meng Yin Department of Radiology Mayo ClinicRochesterMNUSA Department of Radiology Hacettepe UniversityAnkaraTurkey

Metabolic dysfunction associated steatohepatitis(MAsH)is a silent epidemic,hiding in the shadows of obesity,and often silently advancing towards the grave complication of *** distinction between MAsH and simple hepatic steatosis,which is under the spectrum of metabolic dysfunction-associated steatotic liver disease(MAsLD),is highly desired as it provides critical information about the prognosis of the *** indicators,such as fibrosis-4(FIB-4)index and nonalcoholic fatty liver disease(NAFLD)fibrosis score that includes conventional laboratory data and clinical parameters.

关键词： Proton density fat fraction(PDFF) metabolic dysfunction associated steatohepatitis(MAsH) deep subcutaneous fat

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Efficient processed carbon soot@Mos2 hybrid Bi-functional electrode for dye-sensitized solar cell and asymmetric supercapacitor devices

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Nano Materials science 2024年第4期6卷 484-494页

作者： B.Arjun Kumar Gopal Ramalingam salah Addin Burhan Al Omari Zhumabay Bakenov sambasivam sangaraju sangarapani sudhakar Quantum Material Research Lab (QMRL) Department of Nanoscience and TechnologyAlagappa University Department of Mechanical and Aerospace Engineering United Arab Emirates University Department of Chemical and Materials Engineering Nazarbayev University National Water and Energy Center United Arab Emirates University Department of Physics Alagappa University

A feasible approach to rectify the world's energy demand using sustainable development of adequate energy generation and storage technologies in a single *** this respect,we made a holistic approach with a bifunctional electrode material to perform effectively in energy generation and storage ***2nanosheets were produced by the eco-friendly method and reduced graphene oxide is used to prepared by carbon soot which is derived from castor *** prepared soot and rGO were combined with Mos2nanosheets using a simple sonication *** as-prepared sample was introduced in the supercapacitor and DssC *** combination Mos2@rGO provides an enhanced conversion efficiency of 11.81%and the reproducibility of DssC is also ***,Mos2@rGO is used to fabricate an asymmetric supercapacitor to investigate its real-time *** device produced the maximum power density （1666.6 mW/kg） and energy density （25.69 mWh/Kg） at 1 A/*** asymmetric supercapacitor device holds a cyclic stability of 81.4%for 5000 cycles and it powered up an LED device for 4 min.

关键词： Carbon soot solar cells supercapacitors Mos 2 DssC

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Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information systems

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Computers, Materials & Continua 2024年第8期80卷 3123-3138页

作者： saket sarin sunil K.singh sudhakar Kumar shivam Goyal Brij Bhooshan Gupta Wadee Alhalabi Varsha Arya Chandigarh College of Engineering and Technology Chandigarh160019India Department of Computer science and Information Engineering Asia UniversityTaichung413Taiwan symbiosis Centre for Information Technology(sCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Department of Computer science Immersive Virtual Reality Research GroupKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut11022801Lebanon UCRD Chandigarh UniversityChandigarh140413India

In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic *** in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading *** meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading *** AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital *** research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital ***,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.

关键词： Neurodynamic Fintech multi-agent reinforcement learning algorithmic trading digital financial frontier

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Assessing the Influence of Dykes on the Drainage Network of the shivan River in North Maharashtra

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International Journal of Geosciences 2024年第8期15卷 582-589页

作者： sandeep B. Bhise Tushar P. Raut suchitra s. Pardeshi sudhakar D. Pardeshi Department of Geography GMD Arts BW Commerce & Science College Sinnar Nashik India Department of Geography Prof. Ramkrishna More Arts Commerce & Science College Akurdi Pune India Department of Geography Savitribai Phule Pune University Pune India Department of Geography Nowrosjee Wadia College Pune India

The prominent linear dyke ridges outcropped in the Narmada-Tapi dykes’ swarm represent an intrusion in the Deccan Traps. Understanding the relationship among the underlying geological structures, the strike of the dykes, and the channel patterns is essential. Dykes act as obstructions to stream flow, causing diversions, and their geometry and patterns significantly impact the rivers and streams that drain and cross the dyke swarm zone. For this study, Google Earth images, LIss III images, and Cartosat DEM were used to delineate the shivan basin and extract dyke features. The shivan River basin is a sixth-order drainage system that reflects superimposed drainage systems within the Tapi dyke swarm zone. About 65% (169 km2) of its area is controlled by dyke orientation. The dyke ridges align predominantly in an East-West (E-W) direction, a pattern mainly followed by lower-order streams, which have developed an insequent, transverse drainage network within the dyke swarm zone. In the lower parts of the shivan basin, where the number of dykes decreases, the drainage network follows the general slope and is oriented in a North-south direction. The shivan River and its tributaries have partially adjusted to the dyke orientation, resulting in a transverse drainage pattern in areas characterized by parallel dyke ridges.

关键词： Deccan Traps Narmada-Tapi Dyke swarm Google Earth LIss III Cartosat DEM

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A Novel Approach for Network Vulnerability Analysis in IIoT

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Computer systems science & Engineering 2023年第4期45卷 263-277页

作者： K.sudhakar s.senthilkumar Department of Computer science and Engineering University College of EngineeringPattukkottaiRajamadam614701India

Industrial Internet of Things(IIoT)offers efficient communication among business partners and *** an enlargement of IoT tools connected through the internet,the ability of web traffic gets *** to the raise in the size of network traffic,discovery of attacks in IIoT and malicious traffic in the early stages is a very demanding issues.A novel technique called Maximum Posterior Dichotomous Quadratic Discriminant Jaccardized Rocchio Emphasis Boost Classification(MPDQDJREBC)is introduced for accurate attack detection wi th minimum time consumption in *** proposed MPDQDJREBC technique includes feature selection and ***,the network traffic features are collected from the *** applying the Maximum Posterior Dichotomous Quadratic Discriminant analysis to find the significant features for accurate classification and minimize the time *** the significant features selection,classification is performed using the Jaccardized Rocchio Emphasis Boost *** Rocchio Emphasis Boost Classification technique combines the weak learner result into strong *** Rocchio classification technique is considered as the weak learners to identify the normal and ***,proposed MPDQDJREBC technique gives strong classification results through lessening the quadratic *** assists for proposed MPDQDJREBC technique to get better the accuracy for attack detection with reduced time *** assessment is carried out with UNsW_NB15 Dataset using different factors such as accuracy,precision,recall,F-measure and attack detection *** observed results exhibit the MPDQDJREBC technique provides higher accuracy and lesser time consumption than the conventional techniques.

关键词： Industrial internet of things(iiot) attack detection features selection maximum posterior dichotomous quadratic discriminant analysis jaccardized rocchio emphasis boost classification

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Energy Efficient Clustering Protocol to Enhance Network Lifetime in Wireless sensor Networks

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Computers, Materials & Continua 2021年第9期68卷 3595-3614页

作者： s.Nanthini s.Nithya Kalyani sudhakar sengan Department of Computer science and Engineering Sri Ramakrishna College of EngineeringPerambalur621113India Department of Information Technology K.S.R College of EngineeringTiruchengode637215India Department of Computer science and Engineering PSN College of Engineering and TechnologyTirunelveli627152India

In this paper,the energy conservation in the ununiform clustered network field is *** fundamental reason behind the methodology is that in the process of CH election,nodes Competition Radius(CR)task is based on not just the space between nodes and their Residual Energy(RE),which is utilized in Energy-Aware Distributed Unequal Clustering(EADUC)protocol but also a third-degree factor,i.e.,the nearby multi-hop node *** contrast,a third-factor nearby nodes count is also *** surrounding data is taken into account in the clustering feature to increase the network’s life *** proposed method,known as Energy Conscious scattered Asymmetric Clustering(ECsAC),self-controls the nodes’energy utilization for equal allotment and un-equal ***,extra attention is agreed to energy consumption in the communication process by applying a timeslot-based backtracking algorithm for increasing the network’s *** proposed methodology reduces the clustering overhead and node communication energy consumption to extend the network’s *** suggested method’s results are investigated against the classical techniques using the lifetime of the network,RE,alive hop count and energy consumption during transmission as the performance metric.

关键词： Wireless sensor networks energy conservation lifetime enhancement clustering cluster head

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A review:Advances in microbial remediation of trichloroethylene (TCE)

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Journal of Environmental sciences 2010年第1期22卷 116-126页

作者： Prabhakar Pant sudhakar Pant Applied Research Center Florida International University Department of Biology St. Xavier's College

Research works in the recent past have revealed three major biodegradation processes leading to the degradation of trichloroethylene. Reductive dechlorination is an anaerobic process in which chlorinated ethenes are used as electron acceptors. On the other hand, cometabolism requires oxygen for enzymatic degradation of chlorinated ethenes, which however yields no benefit for the bacteria involved. The third process is direct oxidation under aerobic conditions whereby chlorinated ethenes are directly used as electron donors by microorganisms. This review presented the current research trend in understanding biodegradation mechanisms with regard to their field applications. All the techniques used are evaluated, with the focus being on various factors that influence the process and the outcome.

关键词： biodegradation trichloroethylene reductive dechlorination cometabolism direct oxidation

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Contrasting Productivity and Redox Potential in Arabian sea and Bay of Bengal

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Journal of Earth science 2014年第2期25卷 366-370页

作者： suhas s shetye Maruthadu sudhakar Rahul Mohan Babula Jena National Centre for Antarctic & Ocean Research Ministry of Earth sciences

Understanding the past and present changes is critical for evaluating the future climatic changes. In order to understand the paleoproductivity and depositional environments of Northern In- dian Ocean, two sediment cores were collected, one each from the Arabian sea （lat. 16°51.40′N and long. 71°54.37′E, water depth 803 m） and the Bay of Bengal （lat. 13°05.35′N and long. 91°28.21′E, wa- ter depth 3 054 m）. The surface seawater samples indicate higherpCO2 values in Arabian sea as com- pared to the Bay of Bengal. The sediment organic carbon variations along with sedimentological and other geochemical parameters were studied. sediment organic carbon varied from 0.5%--4.7% and 0.3%-1.22% in Arabian sea and the Bay of Bengal, respectively. In Arabian sea, low productivity, oxic conditions and less intense southwest monsoon prevailed during the deglacial period, whereas productivity has increased from last 16 kyr to the modern age. In the Bay of Bengal, organic carbon decreased from the Last Glacial Maxima （LGM） to the modern age, indicating higher productivity in the past as compared to modern age. Fe was associated with organic carbon in the Bay of Bengal and increased during LGM, showing similar trend to that of organic carbon, indicating that Fe may be the limiting factor for the growth of phytoplankton in the Bay of Bengal in the modern age. In the Bay of Bengal, Mn is enriched during modern age and is depleted during LGM, whereas chromium showed the opposite trend indicating anoxic conditions during the LGM, whereas in Arabian sea the trends are opposite to the Bay of Bengal.

关键词： paleoproductivity geochemical deglacial organic carbon.

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Petroleum hydrocarbon concentrations in eight mollusc species along Tamilnadu coast, Bay of Bengal, India

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Journal of Environmental sciences 2011年第7期23卷 1129-1134页

作者： s. Veerasingam R. Venkatachalapathy s. sudhakar P. Raja V. Rajeswari Department of Physics Annamalai University Centre of Advanced study in Marine Biology Faculty of Marine Sciences Annamalai University

Eight mollusc species and sediment samples collected from three different stations along Tamilnadu coast, Bay of Bengal, India were analysed for the levels of petroleum hydrocarbons to elucidate the status of the petroleum residues in mollusc meant for human consumption. The concentrations of petroleum hydrocarbons in sediments along Tamilnadu coast varied from 5.04–25.5 μg/g dw （dry weight）. High concentration of petroleum hydrocarbons in the sediment of Uppanar estuary （25.5 ± 1.45 μg/g dw） was perhaps land and marine based anthropogenic sources of this region. The petroleum hydrocarbon residues in eight mollusc species collected from Uppanar, Vellar and Coleroon estuaries varied between 2.44–6.04 μg/g ww （wet weight）. Although the concentration of petroleum hydrocarbons in sediment of the Uppanar region was markedly higher than the background, the petroleum hydrocarbon residues in mollusc collected from Uppanar estuary did not suggest bioaccumulation. The results signified that industrial growth has affected the aquatic environments and regular monitoring will help to adopt stringent pollution control measures for better management of the aquatic region.

关键词： petroleum hydrocarbons sediment mollusc pollution Tamilnadu coast

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