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Information Extraction Using Data Mining Techniques For Big Data Processing in Digital Marketing Platforms
In the dynamic landscape of digital marketing, harnessing the potential of big data has become paramount for informed decision-making. This study explores the integration of data mining techniques within big data processing frameworks to extract valuable information in digital marketing platforms. With the exponential growth of data generated through online interactions, social media, and e-commerce, traditional methods fall short of uncovering meaningful insights. This research focuses on leveraging advanced data mining algorithms to sift through vast datasets, identifying patterns, trends, and user behaviours. The proposed approach aims to enhance marketing strategies by extracting actionable intelligence from diverse data sources. Techniques such as association rule mining, clustering, and sentiment analysis will be employed to unveil hidden correlations, segment target audiences, and gauge consumer sentiment. The scalability of big data frameworks ensures efficient processing of massive datasets, allowing marketers to make real-time, data-driven decisions. Additionally, the study explores the challenges and opportunities associated with implementing data mining in big data environments for digital marketing. This research contributes to the evolving field of digital marketing by providing a comprehensive framework for extracting, processing, and utilizing information from big data. The findings promise to empower marketers with a deeper understanding of consumer behaviour, enabling the development of more personalized and effective marketing strategies in the ever-evolving digital ecosystem. 2023 IEEE. -
Study of two-dimensional, all-time dispersion of a solute in a fluid-saturated porous medium
The effect of interphase mass transfer on dispersion in a unidirectional flow through a horizontally extent of infinite porous channel is examined using the generalized dispersion model of Sankarasubramanian and Gill [91]. The model brings into focus three important coefficients namely the exchange coefficient, the convection coefficient and the dispersion coefficient. The exchange co- efficient exists due to interphase mass transfer. The effects of reaction rate parameter, ? porous parameter, ? and Brinkman number, ??, on the veloc- ity and thereby the convective and dispersion coefficients are discussed. The time-dependent dispersion coefficient and mean concentration distribution are computed and results are represented graphically for various values of ? ? and ??. The results have applications in heat exchangers, petroleum and chemical engineering problems, chromatography and bio-mechanical problems. -
Implementing quality healthcare strategies for improving service delivery at private hospitals in India /
Journal of Health Management, ISSN No. 0972-0634. -
Dynamic Pricing in Airline Industry
Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 1, pp. 15-29, ISSN No. 2249-7307 -
Effectiveness and Perception of 4P's on Green Products in FMCG
International Journal of Multidisciplinary Research and Development, Vol. 3, Issue 11, pp. 311-355, ISSN No. 2349-4182 -
Construction of Sorafenib Tosylate and Etoposide-loaded Liposomes: A Path to Precision Liver Cancer Therapy and its Apoptosis Induction
Nanotechnology is an effective tool in fighting against cancer, playing a crucial role in investigating and fabricating novel anticancer drugs. Recognizing the worldwide prevalence of cancer, we combined sorafenib tosylate (ST) and etoposide (ETP) within liposomes. We assessed their ability to kill human umbilical vein endothelial cells (HUVECs) and HepG2 liver cancer cells. The liposomes effectively contained ST and ETP, exhibiting a particle size distribution below 180nm, a polydisperse index (PDI) below 0.2, a spherical shape, a strong negatively charged zeta potential, and encapsulation efficiencies of 59% for ST, 88% for ETP, and 57% for ST combined with 87% for ETP. The FTIR analysis indicates that the drugs were incorporated within liposomes. Encapsulation of the drugs in liposomes resulted in a more significant cytotoxic impact on HepG2 cells and a reduced cytotoxic impact on HUVECs. The morphological assessment of the HepG2 liver cancer cells was investigated using AO-EB and Hoechst 33258 staining methods. Apoptosis mechanisms of HepG2 cells were examined by Annexin V and PI dual staining. Furthermore, the coadministration of ST and ETP, which were enclosed in liposomes, resulted in a synergistic impact on the drugs, leading to cell death by apoptosis. 2024 Wiley-VCH GmbH. -
Dual drug co-encapsulation of bevacizumab and pemetrexed clocked polymeric nanoparticles improves antiproliferative activity and apoptosis induction in liver cancer cells
Nanoparticle (NP) enabled approaches have been employed for chemotherapeutic administration due to their capacity to regulate drug release and reduce side effects. Additionally, these methods can use several drugs concurrently and impede the proliferation of cancer cells that have developed resistance. Bevacizumab (BVZ) and pemetrexed (PEM) have demonstrated encouraging outcomes in the treatment and management of cancer. This work investigates the combined antiproliferative efficacy of BVZ and PEM co-loaded PLGA-PEG NPs (BVZ/PEM@PLGA-PEG NPs) against HepG2 liver cancerous cells. The BVZ/PEM@PLGA-PEG exhibited a sphere-shaped and consistent nanosized distribution. In addition, we evaluated the potential mechanisms for inhibiting cell growth and inducing apoptosis using DAPI staining and cell cycle study. The beneficial combined antiproliferative activity and the apoptosis pathway were detected in the HepG2 cells exposed to BVZ/PEM@PLGA-PEG NPs. Our study determined that the combinational drug treatment of BVZ/PEM@PLGA-PEG NPs has a significant effect on promoting the effectiveness of liver cancer treatment. 2024 Wiley Periodicals LLC. -
Advanced Machine Vision Paradigms for Medical Image Analysis
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. 2020 Elsevier Inc. All rights reserved. -
Unveiling the Redox Characteristics of Rutin Trihydrate-Canvas-Based Sensor for Hydrazine Sensing in Water Samples
The inclusion of redox mediators into electrocatalytic systems facilitates rapid electron shuttling kinetics and boosts the overall catalytic performance of the electrode. This approach overcomes the sluggish reaction dynamics associated with direct electron transfer, which may be impeded by restricted analyte access to the electrodes active sites. In contrast to conventional synthetic redox mediators, naturally sourced phytomolecule rutin trihydrate (RT), extracted from apple juice, offers potential ecological advantages. This bands with green chemistry principles and sustainability in electroanalytical approaches. The current work presents an eco-friendly and direct electrochemical approach to fabricate a redox-active RT-immobilized MWCNT-infused PEDOT hybrid material-modified glassy carbon electrode (GCE/MWCNT + PEDOT@RT). The developed electrode showcased a sharp and stable redox signal at E0 = 0.63 V vs Ag/AgCl with no surface-fouling characteristics. The efficacious functionalization of RT onto MWCNT + PEDOT was corroborated by a remarkable increase in the surface characteristics, enhanced electrochemical current responses, and low charge transfer resistance. The GCE/MWCNT + PEDOT@RT exhibited highly selective and sensitive sensing responses toward the toxic and potentially carcinogenic hydrazine (HZ) via cyclic voltammetry and differential pulse voltammetry techniques, yielding a low detection limit (DL) of 1.02 ?M and a sensitivity of 0.032 ?A ?M-1 in a linear dynamic range between 0 and 1350 ?M. In addition, the method was highly efficient for HZ detection in real samples of tanker, tap, and wastewater samples, producing a good recovery of ?98%. 2025 American Chemical Society. -
Carboplatin-loaded zeolitic imidazolate framework-8: Induction of antiproliferative activity and apoptosis in breast cancer cell
The challenge with breast cancer is its ongoing high prevalence and difficulties in early detection and access to effective care. A solution lies in creating tailored metalorganic frameworks to encapsulate anticancer drugs, enabling precise and targeted treatment with less adverse effects and improved effectiveness. Zeolitic imidazolate framework-8 (ZIF-8) and carboplatin (CP)-loaded ZIF-8 were synthesized and characterized using various analytical techniques. High Resolution-transmission electron microscopy of ZIF-8 and CP@ZIF-8 indicates that the particles had a spherical shape and were nanosized. The drug release rate of CP is 98% under an acidic medium (pH 5.5) because of the dissolution of ZIF-8 into its coordinating ions, whereas 35% in a physiological medium (pH 7.4) with the addition of CP, the high porosity, and pore diameter of ZIF-8 decrease from 1243 to 1041m2/g. Breast cancer MCF-7 cells were shown greater IC50 in CP@ZIF-8 (15.013.03g/mL) than free CP (34.984.25g/mL) in an in vitro cytotoxicity assessment. The cytotoxicity of the CP@ZIF-8 against MCF-7 cells was studied using the methylthiazolyldiphenyl-tetrazolium bromide method. The morphological changes were examined using fluorescent staining (acridine orangeethidium bromide and Hoechst 33258) methods. The comet assay assessed the DNA fragmentation (single-cell gel electrophoresis). The results from the study revealed that CP@ZIF-8 can be used in the treatment of breast cancer. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Biogenic synthesis of dopamine/carboxymethyl cellulose/TiO2 nanoparticles using Psidium guajavaleaf extract with enhanced antimicrobial and anticancer activities
The green synthesis of metal oxide nanoparticles (NPs) has garnered considerable attention from researchers due to its utilization of eco-friendly solvents during synthesis and cost-effective approaches. This study focuses on the synthesis of titanium oxide (TiO2) and dopamine (DA) carboxymethyl cellulose (CMC)-doped TiO2 (DA/CMC/TiO2) NP using Psidium guajava leaf extract, while also investigating the structural, optical, and morphological and biocidal potential of the prepared NPs. Significantly larger zones of inhibition were observed for DA/CMC/TiO2 NPs compared to TiO2 against various pathogens. Moreover, the MTT assay was carried out to evaluate the anticancer activity of the prepared samples against MG-63 cells, and the results revealed that DA/CMC/TiO2 NPs exhibited significantly higher level of anticancer activity compared to TiO2. The experimental results demonstrated that DA/CMC/TiO2 NPs exhibited enhanced anticancer activity in a dose-dependent manner when compared to TiO2 NPs. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Biocidal activities of nickel oxide nanoparticles modified by copper and manganese, synthesized by green process
In recent years, the development of dual dopant-based nanoparticles (NPs) has gained significant attention as they possess exceptional physico-chemical and biomedical properties, making them potential candidates for antimicrobial and anticancer uses. In this research, we successfully synthesized nickel oxide (NiO) and copper, manganese-doped NiO (CuMn:NiO) NPs using a green synthesis method. The synthesis process involved Trigonella foenum-graecum (T.f.graecum) leaves extract as a nucleating agent. The synthesized nanoparticles were confirmed by various physico-chemical studies. Based on X-ray diffraction analysis, the median size was determined as 36 nm for NiO and 32 nm for CuMn:NiO NPs. The antibacterial study revealed that CuMn:NiO NPs exhibited a higher zone of inhibition in contrast to both Gram-positive (Streptococcus pneumoniae, Bacillus subtilis, Bacillus megaterium) and Gram-negative bacteria (Klebsiella pneumoniae, Escherichia coli, Vibrio cholerae) compared with NiO NPs and commercial amoxicillin. The antifungal studies conducted against Candida albicans demonstrated that CuMn:NiO NPs exhibited enhanced efficacy in comparison to NiO NPs. In vitro testing against human breast cancer cells (MCF-7) demonstrated the anticancer potential of NiO and CuMn:NiO NPs, supported by IC50 concentrations of 11 and 9?g/mL, respectively. The photoluminescence (PL) spectra of NiO and CuMn:NiO NPs exhibited a green emission at 508 and 518 nm, respectively, which indicated the generation of active free radicals by the NPs. These findings suggest that CuMn:NiO NPs hold promise in the healthcare industry. 2024 John Wiley & Sons Ltd. -
Sexual Relationship Decision Making Based on Entertainment Media: A Qualitative Perspective Among Young Couples
As important as physical, mental, or social health is sexual health. Teenage pregnancy, STDs/STIs, and unsafe abortions are just a few of the population health issues that can arise from the absence of adequate sex education for young people. The purpose of this study is to investigate the process of sexual decision-making as influenced by media intervention among couples. Entertainment education (EE) is an approach that uses storytelling to influence large-scale behaviour change. EE has been used as a potent tool to educate, enlighten, and influence society and individual behaviour change worldwide. Through entertainment education, people have been taught about themes like HIV, family planning, pregnancy and child health, violence against women, and other subjects. Web series or movies that are accessible on the online subscription service, Netflix was taken into consideration for this study. Although there is a great deal of research on adolescent sexuality, studies of sexual decision-making have traditionally been gendered, meaning that men and women have been examined separately. This study is designed for a qualitative investigation using a phenomenological approach. Thematic analysis was employed to analyse semi-structured interviews of couples in a heterosexual romantic relationship. The findings will reveal the influence of entertainment education on young couples choices in their intimate relationships. 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students. 2023 by IGI Global. All rights reserved. -
Improved Crypto Algorithm for High-Speed Internet of Things (IoT) Applications
Modern technologies focus on integrated systems based on the Internet of Things (IoT). IoT based devices are unified with various levels of high-speed internet communication, computation process, secure authentication and privacy policies. One of the significant demands of present IoT is focused on its secure high-speed communication. However, traditional authentication and secure communication find it very difficult to manage the current need for IoT applications. Therefore, the need for such a reliable high-speed IoT scheme must be addressed. This proposed title introduces an enhanced version of the Rijndael Cryptographic Algorithm (Advanced Encryption Standard AES) to obtain fast-speed IoT-based application transmission. Pipeline-based AES technique promises for the high-speed crypto process, and this secure algorithm targeted to fast-speed Field Programmable Gate Array (FPGA) hardware. Thus, high-speed AES crypto algorithms, along with FPGA hardware, will improve the efficiency of future IoT design. Our proposed method also shows the tradeoff between High-Speed communications along with various FPGA platforms. 2020, Springer Nature Switzerland AG. -
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Non-invasive glucometer /
Patent Number: 201941025125, Applicant: CHRIST (Deemed To Be University) -
Combinational edge detection using multiple color channels and GrabCut
Identification of edges is very important in feature extraction and pattern recognition. An edge of an image detected by converting it from RGB format to a Grayscale image and can sometimes be inefficient and inaccurate. This inefficiency is caused due to various color differences that get erased or rewritten during the process of grayscale conversion. Edge locations in a colored image are derived by analysing the variations in the multiple color channels and merging the gradients in these channels to compute a single edge snapping vector field, which is derived using the Euclidean distances between two distinct pixels in an image. This lets to retain the various multidimensional characterizations of color channels of an image as the color differences can be closely calculated using human perceptions. Hence this method is proved to provide more accuracy in edge detection. Furthermore, the results are improved when combined with a finer edge detection method GrabCut, which allows the user to detect the edges in an image using reduced iterations. The proposed paper uses a combinational approach to efficiently acquire edges in the image by enhancing the color properties of an image and then using the GrabCut method to retrieve the edges present in an image. IAEME Publication. -
An Examination of Methodological Approaches for Segmentating Fetal Brain MRI Images - Analysis
In today's world and in the country like India, Women's health needs more care. Especially the women's health during the pregnancy period plays a vital role in both the mother as well as the baby's care. As per a survey, among thousands three of them found to have fetal brain abnormalities. If these abnormalities are predicted at the early stage, then it will be an added advantage in saving both the life of mother and baby. During the pregnancy number of tests have to be performed to monitor fetal development. Tests like fetal ultrasound, Chorionic Villus Sampling, Amniocentesis, Fetal Echocardiogram, Fetal MRI imaging SCAN etc. The fetal brain abnormality can be predicted as well as treated at the early stage by analyzing the fetal brain MRI during the gestational period. Identifying abnormalities in fetal brain MRI images involves several essential steps, including image segmentation, analyzing images involves extracting distinctive features, refining their quality, identifying relevant patterns, and categorizing them based on specific criteria. The process of classification determines whether an abnormality is present or not. Analyzing images presents a complex undertaking owing to the diversity in shapes, spatial arrangements, and intensity levels within the images. This paper focuses on reviewing and comparing various segmentation techniques, highlighting their respective strengths and weaknesses. 2024 IEEE.