Volume 6 | Issue 4

 Abstract

Concrete, a widely common building material, has cement as its primary ingredient. Global warming-causing greenhouse gases are released into the environment as a result of cement manufacture. Current research is thus concentrating on other materials to replace and lessen the requirement for cement. Steel fibers are incorporated to geo-polymer concrete in this study using GGBS. GGBS is a by-product of the steel industry. Concrete has been strengthened by the use of steel fibers. This experiment used geo-polymer concrete with GGBS and steel fiber (0.5%) together with 8 and 10 mol alkaline activators. The ratio of these alkali activators is 1:2.5. The results showed that fiber may significantly enhance mechanical properties. As the fiber volume fraction grows, so does the augmentation.

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Alkaline Activator Solution, Geo-polymer, Ground Granulated Blast Furnace Slag (GGBS), Molarity, and Steel Fibers, split tensile strength (STS), compressive strength (CS), flexural strength (FS), geo-polymer concrete (GPC)

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IoT and Big Data have been the talk of the technological industry for a while, and they are now essential technologies rather than just "nice to have" items. Organizations are under pressure to accept big data, which has greatly increased the usage of big data analysis over the past several years. As a result, companies are also quickly realizing what they need for it. The Internet of Things (IoT), on the other hand, has inspired the globe by demonstrating the benefits that a fully networked world may provide. Though IoT and Big data evolved independently, they have become interrelated over the period. Furthermore, the relation between big data and IoT has shown a convergence of the two technologies which is aligning the technologies in the best possible way. Hence, if IoT big data combination separately gives plenty of reasons for excitement, then combining the two technologies multiplies the anticipation. In this paper, we will discuss how IoT and big data go hand in hand and how organizations are obtaining benefits by using the internet of things big data together.

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IoT, Big Data, Data Mining

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For conducting caesarean sections sub arachnoid blocks are shown to be an easy, safe, and most commonly followed anesthetics technique. Nonetheless its connotation with some side effects like perioperative hypotension, bradycardia nausea and vomiting can't be ignored. The majority of these side effects are induced by sympathetic blockade, hypovolemia and Bezold-Jarisch reflex through intra-cardiac serotonin (5HT3) receptors and vague nerve. Various studies have already established the use of 5HT3 antagonists like Ondansetron in preventing the serotonin induced BJR and thus peri-operative hypotension. In the present study, it was imaginedby blocking type 3 serotonin receptors by intravenous (i.v.) ondansetrondecreases the incidence of hypotension brought by spinalanesthesia After procurement approval of recognized ethical group, and printed informed consent we conducted a study in 100 pregnant patients aged between 18-45 years with ASA 1 and 2status planned for an elective caesarean section at term. This is a potential, randomized, measured, double blinded study. Group I (n=50) received 4milligram ondansetron in 10 ml saline intravenously 5 mins before spinal puncture. Group II (n=50) received10 ml saline in the same way and at the same timing. Patients in both the group I and II received 1000 ml of Ringers lactate solutionover30 minutes in the pre-operative room prior to induction of spinal anesthesia which was induced using2.2 ml of 0.5% Bupivacaine heavy injected in intrathecalspaceinboththegroupsbysameanesthesiologist.Standard ASA monitoring including, ECG, Pulse oximetry and NIBP was recorded in both the groups. Measurements of BP and heart rate (HR) was taken every 5 minutes for 60 minutes. Hypotension was defined as a reduction in mean arterial pressure (MAP) of more than 20%, and 3 mg of me phentermine was administered intravenously. Bradycardia was defined as a reduction in heart rate of more than 20%, and atropine 0.6 mg iv was administered intravenously. Results Both groups are comparable in demographic. Statistically significant difference was noted in the Systolic Blood Pressures in both the groups at 0, 10, 20, 30, 40, 50 mins and 1-hour post sub arachnoid block. Requirement of vasopressor was significantly low in Group I 9 patients (18%) with a p=0.005 as compared to group II 32 (64%)patients Conclusion:It was safely concluded that administering intravenous ondansetron prior to spinal puncture significantly depress the incidence of hypotension and requirement of vasopressors.

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Ondansetron, hypotension, subarachnoid-block caesarean section

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This original copy examines the use of a fuzzy logic circuit (FLC) based dynamic voltage restorer (DVR) to alleviate voltage droops. Subordinate types of assistance, such as voltage and receptive force control, are offered by the electric framework that is urgently needed to ensure expanded appropriated age dispersion framework disabling capacity wanted to remain connected lists, ensuring the operational soundness of the force framework. This paper investigates how the current systems for dynamic and receptive force infusion sway the activity of lattice tied inverters as far as required force, current streaming, and decrease of dynamic force conveyance during the voltage hangs. Such informational resources are important for measuring converters for use in problematic situations. Moreover, incorporates stage lattice thinking and stable pinnacle dynamic force control approaches about characteristic () reference outline. The plan and execution of the examined power infusion methodologies are talked about, and their adequacy and specialized practicality are investigated through unique computational reenactments under even/topsy-turvy voltage hangs, and variety of the short out proportion.

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Fuzzy logic circuit, dynamic voltage regulator

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Context: One of the leading causes of death in India is severe hepatic dysfunction. The primary goal of this study is to determine whether the polyherbal combination of chosen fruit peel extracts and hepatoprotective efficacy. Environment and Design: 1. With CCl4, induce hepatotoxicity 2. Investigation of the PHM and hepatoprotective properties of certain peel extracts. 3 Calculating different enzymes to determine liver function. Materials and Procedures After inducing hepatotoxicity, male Wistar albino rats (180-200 g) were separated into 12 groups and treated with PHM and specific extracts. Blood and liver samples were then taken and analysed on the 14th day. The experimental findings were reported as the mean of the statistical analysis (SEM). ANOVA was applied to the data where appropriate.Results and Discussion: All the selected plant extracts and PHM shown to prevent the leakage of SGOT, SGPT, and ALP in CCl4 induced hepatotoxicity. The order of potency was PHM>APMP>APCM>APMI>APAC. The APMP was the better hepatoprotective among the selected plant extracts. The activities might be due to the conditioning of hepatocytes by protecting the integrity of the membrane from CCl4 induced leakage of serum markers into circulation. All the selected plant extracts and PHM shown to revert back the SOD, CAT and GSH to the normal values in CCl4 induced rats in a dose dependent manner in liver homogenates.

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Fruit peels, Hepatoprotective effects, hepatotoxicity, poly herbal mixture, non enzymatic antioxidants.

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HR analytics, often known as people analytics, is the methodical application of analytical methodologies to human resources (HR) data. Estimating turnover, locating knowledge and skills inside a company, and forecasting job performance are common issues in HR analytics. Instead than only employing key performance indicators, HR analytics is an area of significant interest. This is because the amount, velocity, and diversity of HR data are all quickly increasing as a result of the digitalization of work processes. Steel cabinets were used to store personnel files. It is now kept in the business systems together with information from emails, process data, employee satisfaction surveys, and the hiring process. The ethics of human resource analysis need to be discussed as it becomes more common. The purpose of this paper is to discuss the ethical implications of applying sophisticated analytical methods to human resource management problems.

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Big data, company, Ethical dilemmas, HR Analytics, Human resource management

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The current study makes an effort to explain how Indian customers feel about insurance services. Due to the availability of broad knowledge about insurance, consumers are now impacted by numerous insurance kinds, including health insurance, vehicle insurance, property insurance, and travel insurance. People are increasingly choosing to invest in these types of insurance, which aids con artists in defrauding victims. Insurance fraud is banned, whether it comes from the customer or the insurance provider. Client-side insurance fraud might take the shape of postponed policies, overstated claims, and other issues. However, insurance vendor fraud is seen in the form of policies from fictitious firms and inability to pay premiums, and as a result. In this paper, we perform a comparative analysis on various classification algorithms

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India, attitude, demography, insurance services, marketing activities.

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The goal of our study, which is summarized in this article, is to create a machine learning model that can determine if reviews in Yelp's dataset are authentic or not. To determine which machine learning categorization approach would produce the best results, we specifically applied and contrasted them. To make it easier to understand why some approaches are preferable to others in specific situations, brief explanations are provided for each of the categorization strategies. The SVM classification algorithm produced the best result, with an F-1 score of 0.91 in the forecast

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Classification, regression, svm, navie bayes, logestic regression, supervised learning

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SA213 T12, HVOF, SEM/EDX, Porosity etc

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Real photographs frequently contain complex blur, such as the combination of space-variant and space-invariant blur, which is challenging to mathematically represent. In this work, we provide a cutting-edge blur kernel-free picture deblurring technique. We use two photographs, one fuzzy with low shutter speed and low ISO noise, and the other noisy with fast shutter speed and high ISO noise, both of which may be easily obtained in low-light conditions. By dividing the blurred picture into patches, we can use the corresponding patches in the noisy image to extend the Gaussian mixture model (GMM) and describe the underlying intensity distribution of each patch. Utilizing an analysis of the optical flow between the two pictures, we generate patch correspondences. The Expectation Maximization (EM) algorithm is utilized to estimate the parameters of GMM. To preserve sharp features, we add an additional bilateral term to the objective function in the M-step. We eventually add a detail layer to the deblurred image for refinement. Extensive experiments on both synthetic and real-world data demonstrate that our method outperforms state-of-the terms of robustness, visual quality, and quantitative metrics.

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Image deblurring, optical flow, gaussian mixture model(GMM)

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There is an increasing trend to use products manufactured from the Carbon Fiber Reinforced Plastics or Carbon Fiber Reinforced Polymer (CFRP) composites in the industry like aerospace, automotive, sports, medical, renewable energy etc. It is because of the lighter weight, higher strength, hence, higher strength-to-weight ratio of these materials, their higher corrosion resistance, higher fatigue resistance etc. Manufacturing of products from CFRP composites need precise machining, including cutting. Cutting of these materials is very difficult and inefficient with non-laser traditional techniques. Using continuous wave (cw) or pulsed fiber lasers solves many of these limitations of cutting CFRP composites. These processes have been optimized by many researchers for reducing the heat affected zones (HAZ) by optimizing the laser parameters like its power, pulse duration, feeding speed etc. Finally the environmental hazards of laser-based cutting of CFRP composites and the safety measures are also discussed in this paper.

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Laser cutting, CFRP composites, Carbon Fiber Reinforced Plastics, Polymers.

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The development of MEMS has been driven by the need for miniaturization and lowering the overall manufacturing cost. The field of MEMS is concerned with the development of integrated systems of sensors, actuators and associated electronics. Even though the electronics industry provides an economy of scale for the silicon industry, crystalline silicon is still a complex and relatively expensive material to produce. The development of polymer micromachining technologies that complement traditional silicon approaches has enabled the broadening of microelectromechanical systems (MEMS) applications. Polymeric Bio-MEMS (Biomedical Micro-Electro-Mechanical Systems) have great potential in their current and future applications which include genomics, proteomics, molecular diagnostics, point-of-care diagnostics, tissue engineering, single cell analysis and implantable micro-devices. The polymeric materials are very fragile and not rigid which restrict their manufacturing processes. To minimize many such problems, excimer lasers and femtosecond lasers have been used for the precise micromachining of Bio-MEMS, the details of which are discussed in this paper.

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excimer laser, femtosecond laser, micromachining, polymers, MEMS, Bio-MEMS

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Aadhunik sahitya mein naari chetna

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Aadhunik sahitya mein naari chetna

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Neural Machine Translation (NMT) has significantly advanced the quality of automated translation by leveraging deep learning architectures such as encoder-decoder models with attention mechanisms. However, most NMT systems rely heavily on large-scale parallel corpora, making them less effective for low-resource languages where annotated bilingual data is scarce. This paper investigates the key challenges associated with NMT for low-resource languages, including data sparsity, vocabulary limitations, domain mismatch, and evaluation difficulties. It further explores effective solutions proposed in prior research, such as data augmentation through back-translation, transfer learning from high-resource languages, multilingual NMT, subword modeling, and the use of linguistic knowledge. By reviewing established techniques and architectures developed before 2018, the paper highlights how these approaches help mitigate data scarcity and improve translation quality. The study emphasizes that combining multiple strategies--particularly multilingual learning and synthetic data generation--offers promising performance gains for low-resource settings. Overall, this work provides a concise and structured overview of NMT methodologies for low-resource languages and serves as a useful reference for researchers and practitioners working in this domain

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Neural Machine Translation, Low-Resource Languages, Encoder-Decoder Model, Attention Mechanism, Back-Translation, Transfer Learning, Multilingual NMT, Data Augmentation, Machine Translation

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The present investigation was carried out at Banana Research Station, Nanded. "Studies on plant geometry and levels of potassium on growth, yield and quality of banana (Musa acuminata L.)", for two trial years. In the present experiment, there were four main treatments of plant density, viz. D1 (1.5 m x 1.2 m), D2 (1.5 m x 1.5 m), D3 (1.5 m x 1.8 m) and D4 (1.5 m x 2.1 m), three sub- treatment of potassium levels, viz. K1 (100 g K2 O/plant), K2 (200 g K2O/plant), K3 (300 g K2O/plant) and thus comprising twelve treatment combinations. From the results obtained in the present investigation, it can be revealed that the lowest acidity (0.085%) was recorded in D3 1.5 m x 1.8 m (3,703 plants/ha) which was at par (0.089%) with D2 1.5 m x 1.5 m (4,444 plants/ha), the highest acidity (0.110%) was noted in D1 1.5 m x 1.2 m (5,555 plants/ha). The effect of potassium levels on acidity in pooled was found to be non-significant. In the interaction effect the lowest acidity (0.064%) was equally recorded in three treatments D2K2 (1.5, x 1.5, at 200 g K2O/plant) D3K3 (1.5 m x 1.8 mm at 300 g K2O/plant), D4K1(1.5mx 2.1m at 100 g K2O/plant), which was at par (0.0075%) with D2K3 (1.5 m x 1.5 mm at 300 g K2O/plant) and then equally at par (0.085%) with three treatments D1K2 (1.5 m x 1.2 m at 200 g K2O/plant)D3K1 (1.5 m x 2.1 m at 100 g K2O/plant) D4K2 (1.5 m x 2.1 m at 200 g K2O/plant)at a time and lastly at par (107%) with D3K2 (1.5 m x 1.8 mm at 200 g K2O/plant). The highest acidity (0.128%) was recorded equally In three treatment D1K3 (1.5 m x 1.2 m at 300 g K2O/plant), D2K1 (1.5, x 1.5m at 100 g K2O/plant) D4K3 (1.5 m x 2.1 m at 300 g K2O/plant) at a time and which is significantly at par (0.117%) with D1K1 (1.5 m x 1.2 m at 100 g K2O/plant).

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Study of Levels of Potassium and Plant Geometry on Acidity of Banana (Musa acuminata L.) cv. Ardhapuri

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The banking sector has undergone a significant transformation with the adoption of Artificial Intelligence (AI). Prior to AI adoption, many banks faced challenges such as inefficient manual processes, inadequate risk management, loan processing , credit scoring, poor customer experience and major cyber crime issues. However, AI has emerged as a game-changer, enabling banks to streamline operations, improve customer service, enhance security, personalize offerings, fraud detection, ROI maximization and tailor solutions. This research explores the current state of AI in banking and financial services, as well as how AI can overcome cyber crime in banks with the help of cyber security wing. Stepping up AI adoption it will predict online frauds, loan defaults by using AI algorithms and to train the data to learn how to respond to different situations. The AI industry in India is expected to reach$7.8 billion by 2026, with a significant chunk of this investment coming from the banking sector. This study also gives an insight into the positive and negative impact of an Artificial Intelligence in Indian Banking Industries and also cyber crime issues related to banking sector. This paper gives the detail of the descriptive nature of customer awareness And perception toward the Artificial intelligence

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Artificial Intelligence, Banking, Financial Services, Security, CyberCrime

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Rohinton Mistry's Such a Long Journey (1991) is a seminal work in Indian English literature, narrating the plight of the middle-class Parsi protagonist Gustad Noble amidst the socio-political turbulence of 1970s Bombay. The novel is a rich interplay of private loss and public betrayal, examining how personal lives are deeply impacted by the larger forces of history and politics. This paper investigates how Mistry portrays the decay of urban life, the erosion of moral and political ideals, and the spiritual crisis faced by the individual. It also situates the novel within the broader framework of postcolonial literature, exploring its thematic complexity, historical consciousness, and literary craftsmanship. Through a close reading of the text and engagement with secondary scholarship, the paper offers a comprehensive understanding of Such a Long Journey as both a historical document and a humanist narrative.

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Urban Disillusionment and Political Betrayal in Rohinton Mistry's Such a Long Journey

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The movement for the unification of Karnataka was a historic and transformative process aimed at integrating all Kannada-speaking regions into one administrative entity. The unification movement, spanning several decades, culminated in 1956 with the establishment of Karnataka state, reshaping the political, cultural, and social landscape of the region. This article presents a qualitative analysis of the significance of this movement, delving into its causes, the challenges encountered, the post-unification scenario, and suggestions for the region's future growth. By exploring the intricacies of the movement and its aftermath, this paper aims to provide a comprehensive understanding of the impact of the unification on Karnataka's identity, unity, and development.

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Unification, Karnataka, Kannada, Language Movement, Political Integration, Cultural Identity, Regional Politics, Social Harmony, Challenges, Post-Unification Development

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