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Novel task assignment policies using enhanced hyper-heuristic approach in cloud
Cloud computing plays a vital role in all fields of todays business. The processor sharing server farm is one of the most used server farms in the cloud environment. The key challenge for the mentioned server farms is to provide an optimal scheduling policy to process the computational jobs in the cloud. Many scheduling policies were introduced and deployed by the existing approaches to build an optimal cloud environment. The existing approaches of the heuristic algorithms such as meta-heuristic and hyper-heuristic approaches were the most frequently used scheduling algorithms for the past years. These approaches work well only in the limited types of tasks and resources in a processor sharing server farms in the cloud environment. In the proposed system, novel task assignment policies have been proposed by enhancing the hyper-heuristic approach for the type low task and high resource in the cloud environment. The results of the proposed approach are compared with the existing approaches and the performance evaluation of the proposed approach is also done. As a result, the proposed enhanced hyper-heuristic approach performs well for processor sharing server farms in the cloud environment. Copyright 2023 Inderscience Enterprises Ltd. -
Mapping extinction using GALEX and SDSS photometric observations
The primary objective of this work is to create an all sky extinction map of the Milky Way galaxy. We have cross-matched the Sloan Digital Sky Survey (SDSS data release 8) photometric observations with that of Galaxy Evolution Explorer (GALEX data release 6). This provides a wide range of wavelength coverage from Far Ultra-Violet through the optical spectrum and gives one unique SDSS source for every GALEX source. We discuss a sample of ?32000 objects in the north galactic pole (?75 latitude) from this combined database. The Castelli and Kurucz Atlas was fit to the photometric observations of each star, best fit being determined using a chi-square test. Best fit parameters provide the spectral type and extinction towards each of the objects. The shift in magnitude obtained during the best-fit can be used to determine the distance to each of the stars. With this data, a comprehensive extinction map can be made for the high-latitude objects and later extended to all-sky. 2013 AIP Publishing LLC. -
A Quality of Service Study for Downlink Scheduling Algorithms in Mobile Networks
Internet usage and the number of applications/users growth is going in an unprecedented manner. In these days, lot of users are changed themselves to use internet-based applications rather than traditional voice service. The fundamental of voice-based communication is shifted to packet data access for satisfying the human needs through internet based mobile applications. 4G network is an IP supported rising technology for the past decade and at present also because of un availability service of 5G in all the places. Still, 4G is ruling the globe and the number of subscribers kept growing only. In these days, this remains on the list of latest research topics. Under 4G technology lot of research problems are exist like QoS, Uplink and Downlink Scheduling, Security, Mobility etc., Inspite of discussing that several issues, this paper mainly focusing the QoS in Downlink scheduling algorithms. Also, it presents the issues of various existing QoS downlink scheduling algorithms, names, QoS aware/unaware, parameters used/simulated, drawbacks of those algorithms and result verifications etc. Packet scheduling plays a crucial role for providing Quality of Service (QoS) to the mobile users. Ultimately, it gives some suggestions to explore more further about QoS based research work in Mobile Networks. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Ebcqi: Enhanced bcqi downlink scheduling algorithm for voip in mobile networks
Long Term Evolution (LTE) is a currently growing technology. It gives high speed data with several useful applications. Voice over Internet Protocol (VoIP) is one of the top most applications in that LTE. Scheduling is the main issue in LTE. This paper proposing an updating version of Best Channel Quality Indicator (BCQI) downlink scheduling algorithm. The proposed algorithm assigns the highest priority to VoIP users followed by video traffic and then other remaining traffics in next priority order. The simulation reports give the better results of increased average throughput in all users, as well as the spectral efficiency development is also increased. Here, in the proposed algorithm, the percentage of packet loss is also consistent with the existing BCQI algorithm. And, it totally emits positive results in both rural and urban area environments with different mobility. Number of user access is also high when compared with BCQI algorithm. IJSTR 2019. -
Understanding document semantics from summaries: A case study on Hindi texts
Summary of a document contains words that actually contribute to the semantics of the document. Latent Semantic Analysis (LSA) is a mathematical model that is used to understand document semantics by deriving a semantic structure based on patterns of word correlations in the document. When using LSA to capture semantics from summaries, it is observed that LSA performs quite well despite being completely independent of any external sources of semantics. However, LSA can be remodeled to enhance its capability to analyze correlations within texts. By taking advantage of the model being language independent, this article presents two stages of LSA remodeling to understand document semantics in the Indian context, specifically from Hindi text summaries. One stage of remodeling is done by providing supplementary information, such as document category and domain information. The second stage of remodeling is done by using a supervised term weighting measure in the process. The remodeled LSA's performance is empirically evaluated in a document classification application by comparing the accuracies of classification to plain LSA. An improvement in the performance of LSA in the range of 4.7% to 6.2% is achieved from the remodel when compared to the plain model. The results suggest that summaries of documents efficiently capture the semantic structure of documents and is an alternative to full-length documents for understanding document semantics. 2016 ACM. -
Including category information as supplements in latent semantic analysis of Hindi documents
Latent semantic analysis (LSA) is a mathematical model that is used to capture the semantic structure of documents by using the correlations between the textual elements in them. LSA captures the semantic structure very well being independent of external sources of semantics. However, the model's performance increases when it is supplemented with extra information. The work presented in this paper is to modify the model to analyse word correlations in documents by considering the document category information as supplements in the process. This enhancement is called supplemented latent semantic analysis (SLSA). SLSA's performance is empirically evaluated in a document classification application by comparing the accuracies of classification against plain LSA for various term weighting schemes. An increment of 1.14%, 1.30% and 1.63% is observed in the classification accuracies when SLSA is compared with plain LSA for tf, idf and tfidf respectively in the initial term-bydocument matrix. Copyright 2017 Inderscience Enterprises Ltd. -
Understanding document semantics from summaries: A case study on Hindi texts /
ACM Transactions on Asian Low-Resource Language Information Processing, Vol.16, Issue 1, pp.1-20, ISSN: 2375-4699. -
Self-Discrepancy as a Moderator Between Romantic Attachment and Body Image Satisfaction
Body image satisfaction is about appreciating our body the way it is. One's romantic attachment style with their partner may impact their body image which this study wants to assess. The present study looks at romantic attachment and its effect on body image satisfaction, with self-discrepancy playing the moderator's role. Romantic attachment was measured through avoidance and anxiety dimensions along with trust, commitment, intimacy, physical proximity, support, and partner's suggestions on dressing and looks. Individuals in the age group of 18-25 in a romantic relationship (N=170) were sent an online questionnaire. The questionnaire included scales on body image satisfaction, self-discrepancy and romantic attachment. Correlations results revealed that attachment styles and specifiers of romantic relationships correlate highly with body satisfaction. Regression results indicated a high impact with attachment-related emerging as the single most impactful predictor for the model. The findings from the study can be used by individual and couple therapists dealing with romantic and body image concerns. In a period where romantic relationships are becoming very important in young adults' lives, this study probes into the possibility of romantic relationships affecting body image issues. Studies in the past have given more importance to body image dissatisfaction and parental attachment but this study looks at body satisfaction along with romantic attachment. In a collectivistic Indian culture where the concept of dating is gradually gaining popularity, the findings of this study are unique. 2021 RESTORATIVE JUSTICE FOR ALL. -
Non-invasive glucometer /
Patent Number: 201941025125, Applicant: CHRIST (Deemed To Be University) -
Sexual Narcissism among Men with Sexual Dysfunctions: An Exploratory Study
Objective: Previous studies have associated sexual narcissism with aggressive behaviours prevalent among most Cluster B populations. Recent evidence shows that certain characteristics of sexual narcissism could be beneficial for sexual and marital satisfaction. The present study is an exploration of the role of narcissism in Sexual dysfunctions. Method: A cross-sectional design involving a sample of 62 men aged 2260 years was used for the study. The sample consisted of 31 men having sexual dysfunctions and a matched control group of 31 men free from sexual dysfunctions. Tools used were the International Index for Erectile Functioning, Modified MINI, Sexual Dysfunctional Beliefs Questionnaire, Sexual Narcissism Scale, and Questionnaire for Cognitive Schema Activation in Sexual Context. Scores were subjected to discriminant analysis, and relevant variables were correlated to assess the strength of the association. Results: Results indicated that beliefs about Female Sexual Power (FSP), Helplessness Schema, and Exploitative behaviours of Sexual Narcissism were the best predictors that differentiated the two groups. The higher the scores on these variables, the lower the erectile functioning. FSP shared a positive correlation with both Exploitation and Helplessness, while the latter two variables were unrelated. Conclusions: A higher need to stick to traditional gender roles and fear of being overpowered could be contributing to sexually exploitative behaviours and relationship distress, which in turn, could affect self-efficacy and contribute to Sexual dysfunction. (2023), (Online Journal of Health and Allied Sciences). All Rights Reserved. -
OpenStackDP: a scalable network security framework for SDN-based OpenStack cloud infrastructure
Network Intrusion Detection Systems (NIDS) and firewalls are the de facto solutions in the modern cloud to detect cyberattacks and minimize potential hazards for tenant networks. Most of the existing firewalls, perimeter security, and middlebox solutions are built on static rules/signatures or simple rule matching, making them inflexible, susceptible to bugs, and difficult to introduce new services. This paper aims to improve network management in OpenStack Clouds by taking advantage of the combination of software-defined networking (SDN), Network Function Virtualization (NFV), and machine learning/artificial intelligence (ML/AI) and for making networks more predictable, reliable, and secure. Artificial intelligence is being used to monitor the behavior of the virtual machines and applications running in the OpenStack SDN cloud so that when any issues or degradations are noticed, the decision can be quickly made on how to handle that issue, being able to analyze data in motion, starting at the edge. The OpenStackDP framework comprises lightweight monitoring, anomaly-detecting intelligent sensors embedded in the data plane, a threat analytics engine based on ML/AI algorithms running inside switch hardware/network co-processor, and defensive actions deployed as virtual network functions (VNFs). This network data plane-based architecture makes high-speed threat detection and rapid response possible and enables a much higher degree of security. We have built the framework with advanced streaming analytics technologies, algorithms, and machine learning to draw knowledge from this data that is in motion before the malicious traffic goes to the tenant compute nodes or long-term data store. Cloud providers and users will benefit from improved Quality-of-Services (QoS) and faster recovery from cyber-attacks and compromised switches. The multi-phase collaborative anomaly detection scheme demonstrates an accuracy of 99.81%, average latencies of 0.27 ms, and response speed within 9 s. The simulations and analysis show that the OpenStackDP network analytics framework substantially secures and outperforms prior SDN-based OpenStack solutions for Cloud architectures. 2023, The Author(s). -
Highly secured authentication and fast handover scheme for mobility management in 5G vehicular networks
The Fifth Generation (5 G) networks exhibit high flexibility and diversity in their design and deployment strategies. Transitions between base stations (BSs), heterogeneous networks (HetNets) and other cellular networks provide significant vulnerabilities and expose users to substantial risks associated with cybersecurity attacks. This article evaluates current handover authentication methods in the context of 5 G networks while proposing a set of security criteria for handover authentication. This study presents a novel authentication technique called SHK (Secure Handover Key) that utilizes SDNs (Software Defined networks). The proposed scheme integrates recycled lightweight dynamic key cryptography and combines security features such as perfect forward secrecy and robustness to leakages. The significance of the proposed approach is assessed in terms of computations, communications, signals, and energy costs on 5 G mobility applications and Vehicular Communication Networks (VCNs). The scheme employed in this study demonstrates enhanced security measures and improved changeover performance compared to conventional schemes. 2024 Elsevier Ltd -
Transformation of hydrocarbon soot to graphenic carbon nanostructures
Graphenic carbon nanostructures were synthesized from different precursors of petroleum and agricultural origin by oxidative scissoring. In the present study soot, an environmental pollutant is converted to a value-added product by facile synthesis techniques. The physicochemical changes of the nanostructures are investigated by means of XRD, AFM, FTIR, Raman spectroscopy, XPS analyses SEM-EDS and TEM analysis. XRD analysis confirms the formation of few layer oxidized carbon nanostructures with smaller lateral dimensions. Raman spectra reveal the existence of graphenic layer with a fewer defect. AFM and SEM analyses reveal the formation of stacked tiny fragments of graphenic carbon lamellae. XPS and IR analyses confirm the incorporation of oxygen functionalities into the carbon backbone. 2018 by the authors. -
Raman spectroscopy investigation of camphor Soot: Spectral analysis and structural information
Raman spectra of camphor soot has been investigated and optimised with a Raman microscope system operated at laser excitation wavelength of 514.5 nm. Several band combinations for spectral analysis have been tested, and a combination of three Lorentian bands ( G,D1,D2) at about 1580, 1350 and 1620 cm-1, respectively, with Gaussian-shaped band (D3) at 1500 cm-1and 1200 cm-1 (D4) was best suited for the first order spectra. The second-order spectra were best fitted with Lorentian shaped bands at about 2450, 2700, 2900 and 3250 cm-1. The results are discussed and compared with X-ray diifraction measurements and SEM analysis. The camphor soot shows ? and P{cyrillic} bands which reveals the presence of crystalline graphitic carbon. The SEM micrographs of camphor show the presence of carbon nanostructures. 2013 by ESG. -
Design and analysis of single stage Step-up converter for Photovoltaic applications
Main novelty of the proposed work is dual leg single stage DC-AC converter for DC\AC grid and solar based applications. Operating principles, components design and modulation techniques are presented. Initially proposed concept is simulated in MATLAB Simulink platform and after validated in a real time prototype model is the future work. Proposed idea has some advantages like few passive components, less leakage current due to few switching frequency components, wide range voltage with absence of DC link capacitor. High efficiency due to single stage operation so this circuit is highly suitable for high\low voltage photo-voltaic energy conversion. Electromagnetic interference also less with continuous current. 2023 IEEE. -
Identification of Dry Bean Varieties Based on Multiple Attributes Using CatBoost Machine Learning Algorithm
Dry beans are the most widely grown edible legume crop worldwide, with high genetic diversity. Crop production is strongly influenced by seed quality. So, seed classification is important for both marketing and production because it helps build sustainable farming systems. The major contribution of this research is to develop a multiclass classification model using machine learning (ML) algorithms to classify the seven varieties of dry beans. The balanced dataset was created using the random undersampling method to avoid classification bias of ML algorithms towards the majority group caused by the unbalanced multiclass dataset. The dataset from the UCI ML repository is utilised for developing the multiclass classification model, and the dataset includes the features of seven distinct varieties of dried beans. To address the skewness of the dataset, a Box-Cox transformation (BCT) was performed on the dataset's attributes. The 22 ML classification algorithms have been applied to the balanced and preprocessed dataset to identify the best ML algorithm. The ML algorithm results have been validated with a 10-fold cross-validation approach, and during validation, the CatBoost ML algorithm achieved the highest overall mean accuracy of 93.8 percent, with a range of 92.05 percent to 95.35 percent. 2023 S. Krishnan et al. -
Pore size matters!a critical review on the supercapacitive charge storage enhancement of biocarbonaceous materials
A circular economy targets zero waste converting both natural and synthetic wastes to valuable products, thereby promoting sustainable development. The porous nanocarbon synthesized from bio-waste is one such product used in applications such as energy storage, catalysis, and sensors. Different techniques are employed for synthesizing carbon from the biowastes and each route results in different properties toward end-user applications. Among them, surface area and porosity are the two critical factors that influence the energy storage capabilities of these synthesized carbon nanostructures. Besides the high surface area of the bio-derived carbons, the hindrance in supercapacitive performance is owing to its low porosity. Fewer review/research papers report the porosity tuning of these carbons for their influence on enhancing the performance of energy storage devices (supercapacitors). This critical review analyses the importance of porosity in these bio-derived carbons and reviews the recent development in its synthesis techniques along with its improvement in the energy storage capability. Special attention is also delivered to identify the ambient source of biowaste for carbon electrodes (fabrication) in supercapacitors. The recent research progress in tuning the porosity of these bio-derived carbons and the influence of electrolyte with porosity in affecting its supercapacitive energy storage is elucidated here. The research challenges, future research recommendations, and opportunities in the synthesis of bio-derived porous carbon for supercapacitor applications are briefed. 2022 Taylor & Francis Group, LLC. -
Physical Unclonable Function and OAuth 2.0 Based Secure Authentication Scheme for Internet of Medical Things
With ubiquitous computing and penetration of high-speed data networks, the Internet of Medical Things (IoMT) has found widespread application. Digital healthcare helps medical professionals monitor patients and provide services remotely. With the increased adoption of IoMT comes an increased risk profile. Private and confidential medical data is gathered across various IoMT devices and transmitted to medical servers. Privacy breach or unauthorized access to personal medical data has far-reaching consequences. However, heterogeneity, limited computational resources, and lack of standardization in authentication schemes prevent a robust IoMT security framework. This paper introduces a secure lightweight authentication and authorization scheme. The use of the Physical Unclonable Function (PUF) reduces pressure on computational resources and establishes the authenticity of the IoMT. The use of OAuth 2.0 open standard for authorization allows interoperability between different vendors. The resilience of the model to impersonation and replay attacks is analyzed. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Zero Trust-Based Adaptive Authentication using Composite Attribute Set
Rapid evolution of internet-oriented applications has increased the threats to confidential data. Single-factor authentication approaches are no longer sufficient to ensure user credibility. Multi-factor authentication schemes are also not tamper-proof. A Zero Trust, adaptive authentication-based approach that uses the user's past behavior can offer protection in this scenario. This paper proposes a system that collects a composite attribute set that includes the user behavior, attributes of the application through which the user is requesting access, and the device used. The enhanced collection allows the creation of detailed context that allows granular variance calculation and risk score. 2021 IEEE. All Rights Reserved. -
A JSON Web Signature Based Adaptive Authentication Modality for Healthcare Applications
In the era of fast internet-centric systems, the importance of security cannot be stressed more. However, stringent and multiple layers of security measures tend to be a hindrance to usability. This even prompts users to bypass multi-factor authentication schemes recommended by enterprises. The need to balance security and usability gave rise to Adaptive authentication. This system of utilizing the user's behavioral context and earlier access patterns is gaining popularity. Continuously analyzing the user's request patterns and attributes against an established contextual profile helps maintain security while challenging the user only when required. This paper proposes an Open standards based authentication modality that can seamlessly integrate with an Adaptive Authentication system. The proposed authentication modality uses JavaScript Object Notation(JSON), JSON Web Signature(JWS) and supports a means of verifying the authenticity of the requesting client. The proposed authentication modality has been formally verified using Scyther and all the claims have been validated. 2022 IEEE.