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Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

Computer Systems Science & Engineering 2022年第9期42卷 935-948页

作者： M.Manikandan r.subramanian M.S.Kavitha S.Karthik Department of Computer Science&Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatore641035India Department of Computer Science&Engineering SNS College of TechnologyCoimbatore641035India

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.

关键词： Cost effectiveness hybrid cloud optimal task scheduling virtual machine resource allocation make span

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Do foreign companies earn more and distribute more than domestic companies in India？

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Journal of Modern Accounting and Auditing 2010年第7期6卷 19-25,37页

作者： Dr. r.subramanian Bharathidasan Institute of Management Tiruchirappalli 620014 Tamilnadu lndia

There is a prevalent opinion in the corporate arena that the foreign companies are earning more but are less concerned with reinvesting their earnings in the foreign countries in which they operate and are more concerned in profit appropriations for quick repatriation of their investments by way of declaring high dividend payments. As compared to the foreign companies, domestic companies in India are relatively more concerned for reinvesting their profits and help to trigger the capital accumulation and industrial growth. This practice of comparatively paying higher dividend by foreign companies in India, if proved, supports the view that foreign companies are least concerned with the industrial growth of the country in which they operate. Hence the analyses of the dividend payments and the retained earnings of foreign and domestic firms assume economic importance. Considering the above hypothesis and the importance of the study, this paper made an attempt to empirically test the opinion and bring out any significant differences in the profitability and dividend payments between the two groups often pharmaceutical companies operating in India for the period of last 20 years.

关键词： dividend profitability foreign and domestic companies in India

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Hash Function Based Keyword Searchable Encryption Framework in Cloud Server Using MD5 and MECC

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Journal of Information Hiding and Privacy Protection 2021年第4期3卷 201-226页

作者： r.Lakshmana Kumar r.subramanian S.Karthik Department of Computer Science and Engineering SNS College of TechnologyCoimbatoreTamil NaduIndia Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatoreTamil NaduIndia

Cloud Computing expands its usability to various fields that utilize data and store it in a common space that is required for computing and the purpose of analysis as like the IoT *** devices utilize the cloud for storing and retrieving data since the devices are not capable of storing processing data on its *** Computing provides various services to the users like the IaaS,PaaS and *** major drawback that is faced by cloud computing include the Utilization of Cloud services for the storage of data that could be accessed by all the users related to *** use of Public Key Encryptions with keyword search(PEKS)provides security against the untrustworthy third-party search capability on publicly encryption keys without revealing the data’s *** the Security concerns of PEKs arise when Inside Keywords Guessing attacks(IKGA),is identified in the system due to the untrusted server presume the keyword in *** issue could be solved by using various algorithms like the Certificateless Hashed Public Key Authenticated Encryption with Keyword Search(CL-HPAEKS)which utilizes the Modified Elliptic Curve Cryptography(MECC)along with the Mutation Centred flower pollinations algorithm(CM-FPA)that is used in enhancing the performance of the algorithm using the Optimization in *** additional use of Message Digests 5(MD5)hash function in the system enhances the security Level that is associated with the *** system that is proposed achieves the security level performance of 96 percent and the effort consumed by the algorithm is less compared to the other encryption techniques.

关键词： Certificateless Hashed Public Key Authenticated Encryption with Keyword Search(CL-HPAEKS) modified elliptic curve cryptography(MECC) digest 5(MD5) inside keywords guessing attacks(IKGA) public key encryptions with keyword search(PEKS)

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role of Disclinations and Nanocrystalline State in the Formation of Quasicrystalline Phases on Mechanical Alloying of Cu-Fe Powders

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Journal of Materials Science & Technology 2000年第5期16卷 499-503页

作者： r.subramanian and S.S.raznakrishnan (Department of Metallurgy, P.S.G. College of Technology, Coimbatore-641004, Tamilnadu, India) P.Shankar+ (Materials Charasterisation Group, Indira Gandhi Centre for Atomic research, Kalpakkam-603102, Tamilnadu, India) Department of Metallurgy P.S.G. College of Technology Coimbatore-641004 Tamilnadu India Materials Characterisation Group Indira Gandhi Centre for Atomic Research Kalpakkam-603102 Tamilnadu India

Elemental powders of Cu and Fe were ball milled for various time durations up to 100 h. The various stages of forced alloying by ball milling, leading to instability of elemental crystalline phases and formation of quasicrystalline phases were monitored using X-ray diffraction. Diffusion of Fe into the Cu matrix is proposed as the cause which triggers the instability of crystalline phases and leads to the formation of quasicrystalline phases after 10 h of milling. Milling for 100 h resulted in two different quasicrystalline phases with different lattice constants. role of the nanocrystalline microstructure as an important criterion for the destabilisation of crystalline phases is explained. It is suggested that the formation of nanocrystalline microstructure and their subsequent transformation into quasicrystalline phases may be associated with a continuous increase in the disclination content of the system, which had formed as a result of continued milling and mechanical deformation.

关键词： Fe role of Disclinations and Nanocrystalline State in the Formation of Quasicrystalline Phases on Mechanical Alloying of Cu-Fe Powders Cu

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Coarse to Fine: The role of Severe Plastic Deformation in Advancing Titanium-Based Medical Implants - A Comprehensive review

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 295-306页

作者： Dragana r Mihajlović Bojan I Međo Ivana Lj Cvijović-Alagić Veljko r Djokić Faculty of Technology and Metallurgy University of BelgradeKarnegijeva 411120 BelgradeSerbia Vinča Institute of Nuclear Sci-ences-National Institute of the republic of Serbia University of Belgrade11001BeogradSerbia Innovation Centre of the Faculty of Technology and Metallurgy Karnegijeva 411120 BelgradeSerbia

This paper describes severe plastic deformation(SPD)procedures,which are utilized to form an ultrafine-grained structure in metallic *** the SPD process,a solid material sample is subjected to very high loads without a significant change in sample *** the present work,the high-pressure torsion(HPT)process,as one of the SPD techniques,which achieves a high degree of deformation and ensures refinement of the microstructure,will be discussed in more *** that grain size control is accepted as a method to obtain materials with desired characteristics,an overview of the properties of ultrafine-grained titanium-based biomaterials to be used in medicine is ***,particular attention is dedicated to the influences of HPT process parameters,primarily hydrostatic pressure,and number of revolutions during torsion,on the grain size and physical and mechanical characteristics(modulus of elasticity,microhardness,and tensile properties),corrosion resistance,and biocompatibility of the titanium-based biomaterials.A review of the literature indicates that titanium-based materials obtained by the SPD process show improved mechanical and physical properties without losing biocompatibility and corrosion resistance,which suggests that these methods of obtaining implants are something that should be further developed in the future.

关键词： high-pressure torsion process ultrafine-grained titanium-based materials electrochemical anodization physical properties mechanical properties

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Emerging potential of progranulin-dependent SorCS2 signaling in healthy and diseased nervous systems

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Neural regeneration research 2025年第9期20卷 2591-2593页

作者： Alena Salasova Anders Nykjær Danish research Institute of Translational Neuroscience DANDrITE-Nordic EMBL Partnership for Molecular Medicine and Centre of Excellence PROMEMODepartment of BiomedicineAarhus UniversityAarhusDenmark

The formation of the mammalian nervous system and its maturation into sensory,motor,cognitive,and behavioral circuits is a complex process that begins during early embryogenesis and lasts until young *** neurodevelopm... 详细信息

关键词： progr jointly CS2

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Security Strategy of Digital Medical Contents Based on Blockchain in Generative AI Model

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Computers, Materials & Continua 2025年第1期82卷 259-278页

作者： Hoon Ko Marek r.Ogiela Division of Computer Science and Engineering Sunmoon UniversityAsan31460Republic of Korea AGH University of Krakow Cryptography and Cognitive Informatics LaboratoryKrakow30-059Poland

This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements

关键词： Digitalmedical content medical diagnostic visualization security analysis generativeAI blockchain vulnerability pattern recognition

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Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

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Computer Systems Science & Engineering 2022年第4期41卷 339-355页

作者： r.Siva subramanian D.Prabha Anna University Chennai600025India Department of Computer Science and Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India

Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efﬁcient and in-depth *** investigation of customer patterns helps theﬁrm to develop efﬁcient decisions and in turn,helps to optimize the enter-prise’s business and maximizes consumer satisfaction *** con-duct an effective assessment about the customers,Naive Bayes(also called Simple Bayes),a machine learning model is ***,the efﬁcacious of the simple Bayes model is utterly relying on the consumer data used,and the existence of uncertain and redundant attributes in the consumer data enables the simple Bayes model to attain the worst prediction in consumer data because of its presumption regarding the attributes ***,in practice,the NB pre-mise is not true in consumer data,and the analysis of these redundant attributes enables simple Bayes model to get poor prediction *** this work,an ensem-ble attribute selection methodology is performed to overcome the problem with consumer data and to pick a steady uncorrelated attribute set to model with the NB classiﬁ*** ensemble variable selection,two different strategies are applied:one is based upon data perturbation(or homogeneous ensemble,same feature selector is applied to a different subsamples derived from the same learning set)and the other one is based upon function perturbation(or heterogeneous ensemble different feature selector is utilized to the same learning set).Further-more,the feature set captured from both ensemble strategies is applied to NB indi-vidually and the outcome obtained is ***,the experimental outcomes show that the proposed ensemble strategies perform efﬁciently in choosing a steady attribute set and increasing NB classiﬁcation performance efﬁciently.

关键词： Naive bayes or simple bayes variable selection homogeneous ensemble heterogeneous ensemble customer prediction

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Antisense oligonucleotides provide optimism to the therapeutic landscape for tauopathies

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Neural regeneration research 2025年第3期20卷 803-804页

作者： Glenn A.Harris Lauren r.Hirschfeld rainwater Charitable Foundation Fort WorthTXUSA

Tauopathies are a group of neurodegenerative diseases characterized by abnormal metabolism of the misfolded tau protein. Tau is encoded by the microtubule-associated protein tau gene(MAPT) and can be classified as either 3-repeat(3r) or 4-repeat(4r) based on the number of repeat domains from alternative splicing of exon 10 of the MAPT gene.

关键词： tau metabolism diseases

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Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of Sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree regression(DTr),and Gaussian Process regression(GPr)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPr method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

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