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SR-Mine: Adaptive Transaction Compression Method for Frequent Itemsets Mining
Extraction of frequent itemsets is a key step in association rule mining. Frequent Pattern (FP) mining from a very large dataset is still a challenging research problem. The basic frequent itemset algorithms are Apriori and FP-growth. FP-growth uses Frequent Pattern Tree (FP-tree) to store the database information in a compressed form. A large number of research papers have been proposed as an improvement of the basic frequent itemset mining algorithms. Several researchers have proposed modifications to existing data structures as well as new data structures to improve the mining process. A new method, Size Reduced Mining (SR-Mine), is proposed to speed up the FP-tree creation. The proposed work is implemented with the basic FP-growth algorithm and with the other two recent algorithms based on FP-tree. The three modified algorithms have been tested with standard datasets and compared with the original algorithms. The proposed method can be applied with the frequent itemset mining algorithms which consider each transaction one by one to construct a data structure for mining. The experimental results show that the proposed method can improve the performance of the mining. 2021, King Fahd University of Petroleum & Minerals. -
Sputter deposited tungsten oxide thin films and nanopillars: Electrochromic perspective
Tungsten oxide (WO3) thin films and nano pillars were grown on FTO and corning substrates by using DC magnetron sputtering. Structural properties, surface morphology, optical properties, and electrochromic properties were systematically characterized by using SEM, XRD, UVVis Spectrometer, and Electrochemical Analyser respectively. Increased oxygen partial pressure resulted a rise in the optical transmittance from 72% to 89% at a wavelength of 600 nm. Moreover, coloration efficiency was also found to vary with partial pressures for both planar and glad from 30.48 cm2C-1 to 78.36 cm2C-1. We observe that glad deposited nano pillars showing higher coloration efficiency as compared to the planar thin film. The coloration efficiency found for the planar thin film and nano pillars at optimized partial pressure are 37.04 cm2C-1 and 78.36 cm2C-1 respectively. A strong influence of oxygen partial pressure and surface to volume ratio has been observed on the coloration efficiency, which can play a major role in the electrochromic application. 2022 Elsevier B.V. -
Sprouting in Seeds Aided by Nitrogen Sourced from Ammonia Fumes Leached from Aluminum Dross
Nitrogen and water are nutrients essential for the sprouting of seeds and healthy growth of plants. The seeds derive nitrogen from ammonia (NH3), found in ammonium hydroxide commonly added as manure to the soil. In a materials synthesis process, NH3 gas was released when Aluminum-dross (Al-dross), a hazardous industrial foundry waste was beneficiated to extract useful materials (metallic Al, oxides of Al and Mg, etc.) from the waste. Chemical tests, SEM with EDS and XRD were used to characterize sieved black Al-dross (starting raw material) before and after the beneficiation process. Al-dross also contained significant quantities of aluminum nitride (AlN). When treated with an aqueous media (plain or carbonated water), the AlN reacted to release NH3 gas fumes. This work explored the potential of using this gas to act as a source of nitrogen to accelerate the sprouting of seeds and plant germination. Vegetable and fruit seeds were sown in the soil that was directly infused with the NH3 released from Al-dross for two hours, followed by several (8 to 12) hours of self-diffusion time for homogeneous distribution of the gas in the soil. Five pairs of soils (untreated regular and NH3 fumes treated soils) were prepared under similar conditions. 5 different vegetable and fruit seedlings were planted in these pairs of soils. The germination patterns and growth of the sprouts with time were observed. The seeds that preferred an alkaline environment for germination (e.g., ridge gourd and watermelon seeds) sprouted early and in good health in the NH3 treated soil. Seeds preferring acidic soils did not germinate well in NH3 fume-infused soils. The experiments confirmed the viability of the novel concept, where the waste ammonia fumes released from Al-dross could be favorably generated and used in a controlled manner to promote sprouting of certain agricultural seedlings. 2023 Elsevier Ltd. All rights reserved. -
SPREADING RELIGION AND CULTURE THROUGH INTERNET MEMES
This paper delves into the use of Internet memes as a means of spreading religion and ethical values in modern society. With the rise of the Internet and social media, memes have gained popularity as a form of shared content with the ability to convey meaningful messages. The research evaluates the prevalence and impact of memes in religious and ethical contexts. Through this research, the authors present their viewpoint after mulling over the findings of authors like Limor Shifman. The study asserts that memes can facilitate discussions, promote religious literacy, reinforce beliefs, and instil ethical values. Additionally, it anticipates that religious and ethical memes may influence individuals' actions in their daily lives. This research is significant as it examines the potential of memes to serve as a contemporary tool for spreading religion and ethics in a digital world. 2023 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore),. -
Spray dried nano oxide ceramics for free flowing plasma spray coating powders and battery material processing
Advanced materials are widely used in electronics, aerospace and automobile industry devices and also in substances synthesized for food, medical and pharmaceutical industries. The quality of the base material powder has high influence on the resulting material body (the product) which goes into the manufacture of the device. To name a few (a) flowable ceramic powders from agglomerated nano ceramic powders for plasma spray coatings with the right sprayable powder characteristics (b) advanced graphene encapsulated nano ceramic oxide powders with uniform conductive coating layers as promising electrodes in Li-Ion batteries, (c) advanced bio-ceramic oxides such as hydroxy-apatite ceramic materials with right amounts of moisture, density and composition consistency as bone and dental implants in bio-ceramics research are examples. Among the many processing methods to achieve the base powders from nano ceramic raw materials the most capable and efficient is 'Spray Drying' which results in powders with high purity with well-defined properties. Complex composite by spray drying is achieved where the 'matrix host' material is encapsulated by the 'guest layer' with special properties. This paper illustrates results pertaining to experimentation via spray drying and microscopic investigation by using SEM associated with EDS on (a) Yttria stabilized zirconia plasma sprayable powders for Thermal Barrier Coatings application and (b) nano yttria stabilized zirconia incorporated into microns sized alumina powders for enhanced densification, to understand the significant role of process parameters on uniformity and consistency of the spray dried products. Information based on review on spray dried Li-ion battery materials is also included. Published under licence by IOP Publishing Ltd. -
SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies
NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Sports Tourism and Community Development: Exploring the Links and Sentiments
Sports tourism has emerged as one of the most effective forms of tourism through its ability to satisfy the need of modern-day tourists who prioritize novelty, engagement, and experience. Meanwhile, the sustainable community (development) agenda is also parallelly getting its due attention in the form of SDG11. Recently, the power of sports tourism and events in harnessing community development has been discussed in various patches. However, the structure and mechanism of this growing linkage are rarely discussed holistically, making generalizability a challenging goal to achieve. Further, the aspect of sustainability needs to be studied more. In this regard, the authors of this chapter have attempted to develop a conceptual framework mapping the linkages of sports events and community development, keeping the sustainability agenda in the backdrop. Further, sentiment analysis through NVivo has been performed on all significant works to understand the general sentiments across various communities regarding sports tourism contributing to their development. While the framework development objective is conceptual in nature, the retrieval of the significant themes and sentiments is attained through analytical research. It is concluded that the impacts of sports tourism and events on communities align with the three (triple) bottom lines of sustainable development, i.e., economic, sociocultural, and environmental. These influences result in the sustainable development of the communities. Sentiment analysis points toward the positive sentiment for sports tourism resulting in community development in most cases analyzed. This research will assist both academicians and practitioners in better understanding the linkage between sports tourism and community development and devise measures to make this linkage more sustainable. Springer Nature Singapore Pte Ltd 2024. -
SPORTS FANDOM AND CONSUMER BUYING BEHAVIOUR
The dissertation aims to find whether the features of sports celebrity endorsements such as- credibility, ensured attention, high degree of recall of the product or service, psychographic connect, associative benefit, motivate a fan specifically, in this case, in their purchase decisions. It is an attempt to understand whether fan clubs, fans and fan cultures are unreceptive to the propagation of celebrity endorsements of products and services through conventional and unconventional advertising. The research aims to identify whether fandom of any kind influences their buying decisions. The theory employed in this research is the Two Step Flow theory of communication, wherein sports stars act as opinion leaders in advertising influence.The research is an attempt to understand if the growing sports celebrity brand endorsements actually have an effect on the buyer to the extent of buying decisions. By the end of the research conducted with the help of questionnaires that were administered to the target audience, the researcher aims to arrive at the conclusion, whether sports fandom indeed affects consumer buying patterns. -
Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security
Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security tech-niques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of frames to overcome the above-said problems. This research offers a novel Edge-Net autoencoder to select convoluted and dominant features of the input diffused structure. First, this pro-posedmethodistestedwiththeCross-ethnicityFaceAnti-spoofing (CASIA), Fetal alcohol spectrum disorders (FASD) dataset. This database has three models of attacks: distorted photographs in printed form, photographs with removed eyes portion, and video attacks. The images are taken with three different quality cameras: low, average, and high-quality real and spoofed images. An extensive experimental study was performed with CASIA-FASD, 3 Diagnostic Machine Aid-Digital (DMAD) dataset that proved higher results when compared to existing algorithms. 2023, Tech Science Press. All rights reserved. -
Spontaneous hydrogen production using gadolinium telluride
Developing materials for controlled hydrogen production through water splitting is one of the most promising ways to meet current energy demand. Here, we demonstrate spontaneous and green production of hydrogen at high evolution rate using gadolinium telluride (GdTe) under ambient conditions. The spent materials can be reused after melting, which regain the original activity of the pristine sample. The phase formation and reusability are supported by the thermodynamics calculations. The theoretical calculation reveals ultralow activation energy for hydrogen production using GdTe caused by charge transfer from Te to Gd. Production of highly pure and instantaneous hydrogen by GdTe could accelerate green and sustainable energy conversion technologies. 2023 -
Spoken Language Identification using Deep Learning
A crucial problem in natural language processing is language identification, which has applications in speech recognition, translation services, and multilingual content. The five main Indian languages that are the subject of this study are Hindi, Bengali, Tamil, English, and Gujarati. A Deep Neural Network is introduced in the paper which is specifically made to use Mel-Frequency Cepstral Coefficients (MFCCs) for sophisticated language categorization. The suggested architecture of the model, which includes batch normalisation and tightly linked layers, helps it to be adept at identifying complex linguistic patterns. Comparing the research to the source work [18], promising improvements are shown, highlighting the potential of the model in language detection. 2024 IEEE. -
Spirocyclic isatin-derivative analogues: Solvation, structural, electronic, topological, reactivity properties, and anti-leukaemic biological evaluation
The present work investigates, via computational methods, three spirocyclic isatin derivatives with ?-methylene-?-butyrolactone cores, whose synthesis, experimental data and structural-activity relationships have been reported, to compare their properties and biological action. DFT (Density Functional Theory) studies, including geometry optimisation, FMO Analysis, theoretical UV spectral analysis, NBO and NLO studies, are performed using Gaussian 09 W with a standard basis set. The IEFPCM model is employed to investigate the solvent effect on the reactivity and stability of the compounds. Topological analyses are also performed, including ELF, LOL, RDG and charge transfer studies. ADME profiling is performed using SwissADME online tool. Anti-leukaemic target proteins are selected and docked with the title compounds to understand their suitability to act against leukaemic conditions. 2023 Elsevier B.V. -
Spiritual Intelligence and Spiritual Care in Nursing Practice: A Bibliometric Review
Spiritual intelligence (SI) has recently gained traction in various fields, including nursing. Given the increasing emphasis on patient-centred care and the holistic well-being of patients and nurses, SI is particularly relevant in nursing practice. A bibliometric analysis of recent publications (20142024) in the field helps synthesise and evaluate the existing research on SI in the general field of nursing, identify literature gaps, suggest future research directions and raise awareness of the importance of SI in nursing practice. The present study reports bibliometric data (n = 461) from the Scopus database on SI, spiritual quotient and spiritual care in nursing and health care. The data are analysed using MS Excel and VOSviewer software. The publications trend analysis revealed a significant increase in SI-related publications since 2015. The study presents top-cited articles. Journal of Religion and Health was found to be a prominent journal with the maximum number of publications, and Sage was found to be the top publisher of journals with articles on SI. Network visualisation reveals central figures such as Wilfred McSherry, Trove Giske, Elizabeth Johnston Taylor, Fiona Timmins, Silvia Caldeira and Linda Ross as key researchers in the field. The United States and Iran have the most substantial connections of authors publishing on SI. This study reveals an increasing interest in SI and care within nursing research, confirming its growing significance in the field. By reporting areas where research on SI in nursing remains underdeveloped, the study paves the way for the development of new or updated curricula in nursing programs. The study can guide faculty development initiatives by highlighting the importance of SI and providing resources for educators to incorporate these concepts into their teaching. This study presents specific research questions to address these knowledge gaps. Future studies which can address these questions will enrich nursing education and practice, leading to improved patient outcomes and enhanced nurse well-being using the full potential of SI in nursing practice. 2024 Published by Scientific Scholar on behalf of Indian Journal of Palliative Care. -
Spiritual Dispositional Coping and Health Hardiness on Stress and Related Illnesses: Aftermath COVID-19
The COVID-19 pandemic has caused an array of challenges that have taken a significant toll on psychological well-being and health. Public fear-mongering, hopelessness, and uncertainty have contributed to many negative emotions during the pandemic. The psychological ramifications of these emotions include stress, anxiety, and depression. The extreme stress that people experienced caused mental conditions like post-pandemic stress disorder. Literature suggests there is also an increased susceptibility to stress-related chronic illness. Another major concern post-coronavirus contraction is long COVID (post-acute sequelae of SARS-CoV-2 infection, or PASC), which further leads to complications impacting physical, cognitive, and mental health dimensions and multiple organ system syndromes. As a result of this predicament, there is an increased reliance on various complementary and alternative approaches and interventions for engaging in health-promoting behaviours. The chapter focuses on how spiritual dispositional coping and health hardiness can be used as health protective measures. It also focuses on various strategies that spiritual dispositional coping and health hardiness offer for overall well-being and better adaptation to post-pandemic complications. Therefore, this chapter aims to understand the pandemics stress-related health consequences, re-affirm the relationship between health hardiness and spiritual dispositions, and demonstrate how combining these strategies will provide effective coping methods. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
Spiking neural network with blockchain for tampered image detection using forensic steganography images
Accurate tools are required to acknowledge misleading images in order to maintain image legitimacy, and these tools must allow for legal operations on images. Additionally, after posting their images to the Internet, image owners lose rights over the images because there are no measures in place to safeguard them from misuse. One of the most well-liked techniques for addressing copyright disputes is the use of steganography technologies. The embedded steganography images can, sadly, be easily altered or deleted. To address this problem, this work presents the spiking neural network (SNN) with blockchain for tampered image detection utilizing forensic steganography images. Forensic steganography images that have been altered can be found with this SNN. Using steganography images from the database, SNN is trained in this model. The blockchain stores the owners access policies. The Python platform is used to implement the proposed strategy. F-measure, specificity, accuracy, precision, recall false positive rate (FPR), and false negative rate (FNR) are used to gauge how well the proposed approach performs. When compared to state-of-the-art approaches, the proposed approach obtained an impressive rise of 98.65%, in classification accuracy. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval
The epidemic increase in online reviews' growth made the sentiment classification a fascinating domain in academic and industrial research. The reviews assist several domains, which is complicated to gather annotated training data. Several sentiment classification methodologies are devised for performing the sentiment analysis, but retrieval of information is not accurately performed, less effective, and less convergence speed. In this paper, we propose a sentiment paper proposes a sentiment classification model, namely Spider Monkey Crow Optimization algorithm (SMCA), for training the deep recurrent neural network (DeepRNN). In this method, the telecom review is employed to remove stop words and stemming to eliminate inappropriate data to minimize user's seeking time. Meanwhile, the feature extraction is performed using SentiWordNet to derive the sentiments from the reviews. The extracted SentiWordNet features and other features, like elongated words, punctuation, hashtag, and numerical values, are employed in the DeepRNN for classifying sentiments. To retrieve the required review, the Fuzzy K-Nearest neighbor (Fuzzy-KNN) is employed to retrieve the review based on a distance measure. With rigorous assessments and experimentation, it is observed that the proposed SMCA-based DeepRNN performs better in terms of accuracy of 97.7%, precision of 95.5%, recall of 94.6%, and F1-score 96.7%, respectively. 2013 IEEE. -
Spherulitic crystallization of ?-In2Te3 by physical vapour deposition
Different morphologies of indium telluride (In2Te3) including novel spherulites were crystallized using the physical vapour deposition (PVD) method, by varying the difference in the growth and source zone temperature (?T) of a dual zone horizontal furnace assembled indigenously. Whiskers and kinked needles of In2Te3were grown at ?T = 250 K and 300 K respectively, maintaining the growth zone at 500 C. At high supersaturation (? T = 400 K), spherulitic crystals were obtained. The stoichiometric composition of these crystals has been confirmed using energy dispersive analysis by x-rays (EDAX). The structure of ?-In2Te3 spherulitic crystals is identified as zinc blende with lattice parameter a = 6.159 from x-ray diffraction (XRD) studies. The scanning electron microscope (SEM) images revealed the radial structure of the grown spherulites. The growth mechanism for the spherulitic crystallization of ?-In2Te3 crystals has been discussed based on the theoretical models. Copyright 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. -
Speech to text conversion and summarization for effective understanding and documentation
Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Speech disabilities in adults and the suitable speech recognition software tools - A review
Speech impairment, though not a major obstacle, is still a problem for people who suffer from it, while they are making public presentations. This paper describes the different speech disabilities in adults and reviews the available software and other computer based tools that facilitate better communication for people with speech impairment. The motivation for this writing has been the fact that stuttering, one of the types of speech disability has affected about 1 percentage of the people worldwide. This fact was provided by the Stuttering Foundation of America, a Non-profit Organization, functioning since 1947. A solution to stuttering is expected to benefit a considerable population. Speech recognition software tools help people with disabilities use their computers and other hand held devices to satisfy their day-to-day needs which otherwise, require dedicated domestic help and also question the person's ability to be independent. ASR (Automatic Speech Recognition) systems are popular among the common people and people with motor disabilities, while using these techniques for the treatment of speech correction is a current research field and is of interest to SLPs/SLTs (Speech Language Pathologist / Speech Language Therapist). On-going research also includes development of ASR based software to facilitate comfortable oral communication with people suffering from speech dysfunctions, i.e., in the domain of AAC (Augmentative and Alternative Communication). 2015 IEEE. -
Speculative investment decisions in cryptocurrency: a structural equation modelling approach
Cryptocurrency markets are inclined towards speculative usage due to the inherent high risk of financial loss and the potential for substantial gains during transaction completion. In response to this phenomenon, this study represents the inaugural effort to explore the influence of variables such as subjective norms, domain knowledge, impulsive investment tendencies, and self-control on decisions related to speculative investments. Utilising structural equation modelling with a dataset of 367 responses in India, the study is the first of its kind. The research reveals that subjective norms and domain knowledge play a significant role in influencing impulsive investment and self-control. Additionally, impulsive investment exhibits significant associations with decisions involving speculative investments. This insight underscores the complexity wherein individuals, despite exercising self-control, may still engage in speculative decisions that lead to adverse consequences. The findings have practical implications for investors and regulators, offering valuable insights into investment behaviours within the cryptocurrency realm. 2024 Informa UK Limited, trading as Taylor & Francis Group.