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A Way Towards Next-Gen Networking System for the Development of 6G Communication System
In this talk, the advancements announced by sixth-generation mobile communication (6G) as compared to the earlier fifth-generation (5G) system are carefully examined. The analysis, based in existing academic works, underscores the goal of improving diverse communication aims across various services. This study finds five crucial 6G core services designed to meet distinct goal requirements. To explain these services thoroughly, the framework presents two central features and delineates eight significant performance indices (KPIs). Furthermore, a thorough study of supporting technologies is performed to meet the stated KPIs. A unified 6G design is suggested, imagined as a combination of these supporting technologies. This design plan is then explained by the lens of five prototype application situations. Subsequently, possible challenges contained in the developing track of the 6G network technology are carefully discussed, followed by suggested solutions. The debate ends in an exhaustive examination of possibilities within the 6G world, seeking to provide a strategy plan for future research efforts. 2024 IEEE. -
ENHANCING home security through visual CRYPTOGRAPHY
Home security systems in the recent times have gained greater importance due to increasing threat in the society. Biometrics deals with automated approaches of recognizing a user or verifying the user identity based on behavioral or physiological features. Visual cryptography is a scheme of secret sharing where a secret image is encrypted into shares which disclose no data independently about the original secret image. As the template of biometric are stored in centralized database due to the threats of security the template of biometric may be changed by attacker. If the template of biometric is changed then the authorized user will not be permitted to access the resource. To manage this problem the schemes of visual cryptography can be used to secure the face recognition. Visual cryptography offers huge ways for supporting such needs of security as well as additional authentication layer. To manage this problem the visual cryptography schemes can be used to secure digital biometric information privacy. In this approach the face or private image is dithered in two varied host images that is sheets and are stored in separate servers of data so as to assure that the original image can get extracted only by accessing both sheets together at a time and a single sheet will not be capable to show any data of private image. The main aim of the study is to propose an algorithm which is a combination of CVC and Siamese network. This research implements visual cryptography for face images in a biometric application. The Siamese network is essential to solve one shot learning by representation of learning feature that are compared to verification tasks. In this research face authentication helps in accomplishing robustness by locating face image from an n input image. This research explores the availability of using visual cryptography for securing the privacy to biometric data. The results of the proposed approach provide an accuracy of 93% which is found to be superior when compared with that of the approaches that are already in practice. 2020 -
Secure visual cryptography scheme with meaningful shares
Visual cryptography is an outstanding design, which is also known as visual secret sharing. It used to encode a secret portrait into various pointless share images. Normally, item bossed on transparencies and decrypts as loading one or two or the entire share images by means of the human visual system. Suppose, if we encompass great sets of secret shares then the pointless shares are complicated to handle. In this paper, a meaningful secret sharing algorithm and a modified Signcryption algorithm is used to enhance the security of the Visual Cryptography encryption schemes. The foremost intend of the anticipated format is to extend consequential shares and similarly make sure the isolation on conveying the secret data. The anticipated process is executed in the functioning platform of MATLAB and the presentation results are investigated. 2020, Engg Journals Publications. All rights reserved. -
Unveiling Cutting Edge Innovations in the Catalytic Valorization of Biodiesel Byproduct Glycerol into Value Added Products
The increasing production of biodiesel has led to a glut in the production of glycerol, which is a byproduct. This has resulted in the quest for alternative applications using glycerol as a cheap and readily available starting material. One promising approach is the catalytic valorization of glycerol, which converts glycerol into valuable chemicals such as 1,2-propanediol, lactic acid, and acrolein. The glycerol formed affects the efficiency of the biodiesel, and hence it must be removed. Different processes can convert glycerol to various useful products like glycerol carbonate, glycidol, solketal, lactic acid, and glyceric acid. These different products, the processes used for synthesis, and the various catalysts used have been discussed. The most effective methods for the syntheses, the numerous catalyst systems, mechanisms of the reactions, and applications of these products in different fields are discussed in this review. The paper also discusses the challenges and opportunities of glycerol valorization, including the need for improved catalyst selectivity and activity and the potential for integrating glycerol valorization with other biorefinery processes. Overall, the catalytic valorization of glycerol offers a promising pathway for utilizing this abundantly available resource, and this review provides valuable insights for researchers and practitioners working in this area. 2023 Wiley-VCH GmbH. -
Influence of Short Glass Fibre Reinforcement on Mechanical Properties of 3D Printed ABS-Based Polymer Composites
One of the most promising and widely used additive manufacturing technologies, fused deposition modelling (FDM), is based on material extrusion and is most commonly used for producing thermoplastic parts for functional applications with the objectives of low cost, minimal waste and ease of material conversion. Considering that pure thermoplastic materials have a significantly poor mechanical performance, it is necessary to enhance the mechanical properties of thermoplastic parts generated using FDM technology. One of the conceivable techniques is to incorporate reinforcing materials such as short glass fibre (SGF) into the thermoplastic matrix in order to produce a polymer composite that can be used in engineering applications, such as structural applications. The morphological and mechanical properties of SGF (short glass fibre) reinforced ABS- (Acrylonitrile Butadiene Styrene) based polymer composites created via the method of FDM (fused deposition modelling) were investigated in this work. Properties were evaluated at three different weight percentages (0, 15 and 30 wt%). The composite filaments were developed using the process of twin screw extrusion. The comparison was made between ABS + SGF (short glass fibre) composites and pure ABS of mechanical properties that include surface roughness, tensile strength and low-velocity impact. The tests were carried out to analyze the properties as per ASTM standards. It has been found that the impact strength and tensile strength show an improvement in glass fibre inclusion; moreover, alongside the direction of build, the surface roughness had been reduced. The studies also focused on studying the dispersion characters of SGF in ABS matrix and its impact on the properties. Strength and modulus of SGF reinforced ABS composite has been significantly improved along with reduction of ductility. A 57% increase in tensile strength has been noted for 30 wt% addition of SGF to ABS in comparison to pure ABS. It was also interesting to note the reduction in surface roughness with every incremental addition of SGF to ABS. A 40% reduction in surface roughness has been observed with a 30 wt% addition of SGF to ABS in comparison to pure ABS. 2022 by the authors.Licensee MDPI, Basel, Switzerland. -
Cached-N-Proxy: An Intelligent Proxy Algorithm for Preventing Insider Email Threats to Mail Servers
Insider threats are serious security risks that come from people who work for or are contracted by an organization, such as partners, employees, or contractors. These people use their authorized access to commit hostile acts against the infrastructure, data, or assets of the company. Serious ramifications could result from these dangers, such as financial losses, reputational harm, data breaches, and possible threats to national security. Enterprises must strengthen their defenses with strong intrusion detection and prevention systems because of the growing attack surface for insider threats caused by the increasing adoption of digital technology and remote work habits. Organizations must use a combination of preventive strategies and detection mechanisms, such as privileged access management (PAM), role-based access control, data loss prevention (DLP) techniques, two-factor authentication, and thorough insider threat awareness training, to effectively combat insider threats. 2024 IEEE. -
Visible light responsive Gd, N co-doped mesoporous titania in the photo-oxidation of some novel 9-(N,N-Dimethylaminomethyl)anthracene systems
Oxidative semiconductor catalysis by light can be considered as an easy method for the conversion of harmful aromatics to less harmful products and at the same time move towards a sustainable chemistry. The present work reports the preparation of Gd, N co-doped TiO2 system by hydrothermal technique followed by calcination at 500C and checks its activity in photo-oxidation reactions. The prepared system was characterized by various physico-chemical techniques such as X-ray diffraction, Raman spectroscopy, IR spectroscopy, TGDTG, UV-DRS, SEM, TEM and XPS. Structural identity and mesoporous nature were identified from XRD and BET measurements respectively. On reaction, Tertiary amine appended anthracene and its phenyl substituted derivative in CH3CN yielded Anthraquinone as the major product. Substituted Anthracenemethanamine reacted slowly and a relatively stable intermediate could be isolated at shorter periods of time. The products were separated and purified by column chromatography and the resultant products were characterized thoroughly by 1H NMR, IR spectroscopy and GCMS analysis. 2014, Springer Science+Business Media New York. -
Cu/Pd bimetallic supported on mesoporous TiO2 for suzuki coupling reaction
Generally bimetallic catalysts are more superior to monometallic catalysts and provide a better platform for the development of novel catalysts with enhanced activity, selectivity, and stability. In the current work we have prepared Cu/Pd bimetallic supported on mesoporous TiO2 by hydrothermal method. The prepared system was characterized by various physico-chemical techniques such as XRD, TG-DTG, SEM, EDAX, BJH isotherm, and XPS. Thermal stability and complete electronic structure were identified from TG and XPS measurements respectively. The bimetallic system was found to be very active in Suzuki cross-coupling reaction using different substrates. The products were separated and purified by column chromatography and the resultant products were characterized thoroughly by 1H NMR, and FT-IR analysis. Copyright 2018 BCREC Group. All rights reserved. -
Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest Based FinTech Application for Hyper-automation
Hyper automation is the group of approaches and software companies utilised to automate manual procedures. Financial Technology (FinTech) was processed as a distinctive classification that highly inspects the financial technology sector from a broader group of functions for enterprises with utilise of Information Technology (IT) application. Financial crisis prediction (FCP) is the most essential FinTech technique, defining institutions financial status. This study proposes an Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest (ESAOA-ODCF) based FinTech Application for Hyperautomation. The ESAOA-ODCF technique has achieved exceptional performance with maximum accu y of 98.61%, and F score of 98.59%. Extensive experimental research revealed that the ESAOA-ODCF model beat more modern, cutting-edge approaches in terms of overall performance. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Identification of Driver Drowsiness Detection using a Regularized Extreme Learning Machine
In the field of accident avoidance systems, figuring out how to keep drivers from getting sleepy is a major challenge. The only way to prevent dozing off behind the wheel is to have a system in place that can accurately detect when a driver's attention has drifted and then alert and revive them. This paper presents a method for detection that makes use of image processing software to examine video camera stills of the driver's face. Driver inattention is measured by how much the eyes are open or closed. This paper introduces Regularized Extreme Learning Machine, a novel approach based on the structural risk reduction principle and weighted least squares, which is applied following preprocessing, binarization, and noise removal. Generalization performance was significantly improved in most cases using the proposed algorithm without requiring additional training time. This approach outperforms both the CNN and ELM models, with an accuracy of around 99% being achieved. 2023 IEEE. -
Sales Promotion Practices In Apparel Retail Sector And Challenges Ahead
International Journal of Research in Commerce & Management, Vol-5 (1), pp. 25-28. ISSN-0976-2183 -
Study on factors influencing purchase of branded formal apparel in Indian apparel industry /
International Journal of Business, Management & Social Sciences, Vol-3 (5(2), pp. 51-54. ISSN-2249-7463. -
Enhanced Edge Computing Model by using Data Combs for Big Data in Metaverse
The Metaverse is a huge project undertaken by Facebook in order to bring the world closer together and help people live out their dreams. Even handicapped can travel across the world. People can visit any place and would be safe in the comfort of their homes. Meta (Previously Facebook) plans to execute this by using a combination of AR and VR (Augmented Reality and Virtual Reality). Facebook aims to bring this technology to the people soon. However, a big factor in this idea that needs to be accounted for is the amount of data generation that will take place. Many Computer Science professors and scientists believe that the amount of data Meta is going to generate in one day would almost be equal to the amount of data Instagram/Facebook would have generated in their entire lifetime. This will push the entire data generation by at least 30%, if not more. Using traditional methods such as cloud computing might seem to become a shortcoming in the near future. This is because the servers might not be able to handle such large amounts of data. The solution to this problem should be a system that is designed specifically for handling data that is extremely large. A system that is not only secure, resilient and robust but also must be able to handle multiple requests and connections at once and yet not slow down when the number of requests increases gradually over time. In this model, a solution called the DHA (Data Hive Architecture) is provided. These DHAs are made up of multiple subunits called Data Combs and those are further broken down into data cells. These are small units of memory which can process big data extremely fast. When information is requested from a client (Example: A Data Warehouse) that is stored in multiple edges across the world, then these Data Combs rearrange the data cells within them on the basis of the requested criteria. This article aims to explain this concept of data combs and its usage in the Metaverse. 2023 IEEE. -
Graphene and graphene enhanced nanomaterials from biological precursors synthesis characterization and proliferant applications
Graphene family materials with non-photocatalytic biocidal properties are highly sought after in the field of biomedicine and nanobiotechnology. But the applications of graphene-based materials were often hampered by their high production cost, low yield, non-renewable precursors, harmful processing newlinetechniques, etc. In this context, this study presented the successful usage of biomass materials as sustainable feedstock for the production of graphene derivatives. Five raw materials of biological origin namely, coconut shell, wood, sugarcane bagasse, Colocasia esculenta leaves and Nelumbo nucifera leaves, were investigated. The graphitized forms of the above materials were newlineused as precursors for the graphene nanomaterial synthesis. They were chemically oxidized and functionalized with tin oxide nanoparticles to form the composite. Nano-systems obtained using an identical chemical route from a universal source of carbon nanomaterials, namely carbon black, were also newlinestudied for the purpose of validation and comparison. The synthesis protocols adopted for the preparation of graphene-based materials were devoid of hazardous reducing agents or byproducts. The products obtained after each stage of treatment were characterized with the help of various spectroscopic and microscopic techniques. newlineEven though structural properties of all the precursors appeared to be broadly the same, a variation in their morphology and defect density was discerned. Various analyses revealed the formation of graphene oxide domains with distinct dimensions after the oxidative treatment. An increase in defect newlinedensity was also observed due to the intercalation of oxygen groups to the carbon layers. Post composite formation, a distribution of ultrafine tin oxide newlinenanoparticles on the graphene surface was observed. The distribution of oxygen newlinefunctionalities on the carbon backbone were found to play a major role in governing the dispersal of tin oxide particles during the nanocomposite formation. -
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A Study of In-store Factors Affecting Impulse Buying of Apparels amongst College Students and Young Professionals in Bangalore
Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 3, pp. 1-15, ISSN No. 2249-7307. -
A Study on the Factors Influencing Customer Satisfaction in Multi-brand Apparel Retail
International Academic Research Journal of Business and Management Vol.1, Issue No. 7 ISSN No. 2227-1287 -
Improved Henon Chaotic Map-based Progressive Block-based visual cryptography strategy for securing sensitive data in a cloud EHR system
The core objective of secret sharing concentrates on developing a novel technique that prevents the destruction and leakage of original data during the distribution and encoding processes. Progressive Visual Cryptography (VC) is considered for the potential over the traditional VC schemes since the former does not require and does not suffer from the limitations of requiring a minimum number of participants during the process of encryption and sharing. The chaotic map-based Progressive VC is superior in facilitating predominant secrecy under sharing and encryption. In this paper, an Improved Henon Chaotic Map-based Progressive Block-based VC (IHCMPBVC) scheme is proposed to prevent the leakage and destruction of sensitive information during an exchange and encryption. This proposed IHCMPBVC technique uses the merits of Henon and Lorentz maps for effective encryption since it introduces the option of deriving non-linear behavior that results in sequence generation that covers the complete range with proper distribution in order to minimize the degree of leaks in sharing. The simulation results of the proposed IHCMPBVC technique investigated using entropy, PSNR, and Mean Square Error were improved at an average rate of 27%, 23%, and 31%, predominant to the baseline VC approaches considered in the comparison. 2022 The Authors -
Effect of Short Glass Fiber Addition on Flexural and Impact Behavior of 3D Printed Polymer Composites
Fused deposition modeling (FDM), one of the most widely used additive manufacturing (AM) processes, is used for fabrication of 3D models from computer-aided design data using various materials for a wide scope of applications. The principle of FDM or, in general, AM plays an important role in minimizing the ill effects of manufacturing on the environment. Among the various available reinforcements, short glass fiber (SGF), one of the strong reinforcement materials available, is used as a reinforcement in the acrylonitrile butadiene styrene (ABS) matrix. At the outset, very limited research has been carried out till date in the analysis of the impact and flexural strength of the SGF-reinforced ABS polymer composite developed by the FDM process. In this regard, the present research investigates the impact and flexural strength of SGF-ABS polymer composites by the addition of 15 and 30 wt % SGF to ABS. The tests were conducted as per ASTM standards. Increments in flexural and impact properties were observed with the addition of SGF to ABS. The increment of 42% in impact strength was noted for the addition of 15 wt % SGF and 54% increase with the addition of 30 wt % SGF. On similar lines, flexural properties also showed improved values of 44 and 59% for the addition of 15 and 30 wt % SGF to ABS. SGF addition greatly enhanced the properties of flexural and impact strength and has paved the path for the exploration of varied values of reinforcement into the matrix. 2023 The Authors. Published by American Chemical Society -
Epidemic Prediction using Machine Learning and Deep Learning Models on COVID-19 Data
A catastrophic epidemic of Severe Acute Respiratory Syndrome-Coronavirus, commonly recognised as COVID-19, introduced a worldwide vulnerability to human community. All nations around the world are making enormous effort to tackle the outbreak towards this deadly virus through various aspects such as technology, economy, relevant data, protective gear, lives-risk medications and all other instruments. The artificial intelligence-based researchers apply knowledge, experience and skill set on national level data to create computational and statistical models for investigating such a pandemic condition. In order to make a contribution to this worldwide human community, this paper recommends using machine-learning and deep-learning models to understand its daily accelerating actions together with predicting the future reachability of COVID-19 across nations by using the real-time information from the Johns Hopkins dashboard. In this work, a novel Exponential Smoothing Long-Short-Term Memory Networks Model (ESLSTM) learning model is proposed to predict the virus spread in the near future. The results are evaluated using RMSE and R-Squared values. 2022 Informa UK Limited, trading as Taylor & Francis Group.