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Derris Indica Leaves Extract as a Green Inhibitor for the Corrosion of Aluminium in Alkaline Medium
The corrosion inhibitive effect of Derris indica leaves extract (DILE) on aluminium in 1 M NaOH is investigated at different temperatures. For this purpose, weight loss studies and electrochemical methods including potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) technique are employed. Surface analysis of the treated and untreated aluminium coupons are done by using metallurgical microscopy. About 60.2% of maximum corrosion inhibition efficiency is attained with an optimum inhibitor concentration of 1.2 g/L. Both weight loss and electrochemical studies confirmed that DILE plays a crucial role in the formation of a protective layer over metal surfaces. Also, electrochemical measurements revealed that DILE behaves as a mixed type of corrosion inhibitor. The kinetic parameters and thermodynamic parameters are calculated using Arrhenius theory and transition state theory. Langmuir adsorption isotherm was found to be the best fit and physical adsorption mechanism was proposed. En ineered Science Publisher LLC 2022 -
Depth Wise Separable Convolutional Neural Network with Context Axial Reverse Attention Based Sentiment Analysis on Movie Reviews
Sentiment Analysis (SA) in movie reviews involves using natural language processing techniques to determine the sentiment expressed in reviews. This analysis helps in understanding the overall audience sentiment towards a movie, categorizing reviews as positive, negative, or neutral. It's useful for filmmakers, marketers, and audiences. The existing methods does not provide sufficient accuracy, error rate and complexity was increased. To overcome the aforementioned problem, Depth Wise Separable Convolutional Neural Networks with Context Axial Reverse Attention Network (DWSCNN-CARAN) is proposed for accurately classifying SA in movie reviews. In this input image is taken from two datasets such as IMDB dataset and Polarity dataset. The pre-processing is done using six steps namely, Cleaning, Tokenization, Case Folding, Normalization, Stop Word Elimination, and Stemming for the purpose of removing noises. Following that feature extraction are done using Bag-Of-Words and Term Frequency-Inverse Document Frequency (BOW-TF-IDF). After that classification are done using Depth Wise Separable Convolutional Neural Networks with Context Axial Reverse Attention Network (DWSCNN-CARAN)for classifying the AS in movie reviews. The efficiency of the proposed DWSCNN-CARAN-BOA is analyzed using a dataset and attains 99.94% accuracy, 98.76% recall and attains better results compared with the existing methods. In the future, this approach will use the adversarial instances it generated to conduct adversarial training and assess the potential improvement in classification performance. It also looks into the possibilities of creating adversarial examples at the word and sentence levels by combining structured knowledge from high-quality knowledge bases. 2024 IEEE. -
Depth Comparison of Objects in 2D Images Using Mask RCNN
Getting distance of an object from a single 2D image has always been a task. Due to various reasons, it was difficult to compare from images whether an object is closer or farther from camera. In this paper, we propose an idea to compare multiple images taken from same focal length cameras and specifying the distance of an object in those images with respect to each other. Our dataset contains images of palm of hand with particular distance from camera, and the output difference can specify in which image the palm is closer to camera as compared to others and vice versa. For this model, we are using Mask RCNN to recognize the object; in our case, it has been trained to identify palm, and then giving the output of masked RCNN to a depth identifier model to specify the distance of the palm from the camera. Directly using depth identifier model cannot give correct output as distance of background from camera results in different value for distance of targeted object in different images. So, we will be using mask RCNN to specify which part of image depth model should find distance from the camera. In the final step, we take the output of the depth model and take the mean of the output generated by it and compare the means of various images to specify relative distance from each other. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Deprotection induced modulation of excited state intramolecular proton transfer for selective detection of perborate and ammonia
Acetate protected Naphthalene Coupled Benzothiazole (NCB) has been designed and synthesized for selective detection of perborate (BO3) and ammonia (NH3) based on modulation of excited-state intramolecular proton transfer (ESIPT) process by chemodosimetric deacetylation pathway. In presence of nucleophilic species like BO3 and NH3, acetyl group deprotection of NCB resulted ESIPT within the molecule exhibiting a significant enhancement of absorption and emission signals at 425 nm and 472 nm respectively. The emission enhancement of NCB has been observed by 31-folds and 14-folds in presence of BO3 and NH3 respectively. The selectivity and fast sensitivity of NCB have been shown by the lower detection limit (1.32 M for BO3, 1.74 M for NH3 in UVvis study and 0.60 M for BO3 and 4.39 M for NH3 in fluorescence study) and fast response (rate constants: 12.36 s?1 and 5.54 s?1 for BO3 and NH3 respectively). Analytes induced deacetylation pathway of NCB followed by ESIPT has been clearly demonstrated by theoretical calculation. The test strips based on NCB with BO3 and NH3 are fabricated, which can act as a convenient and efficient test kits for both these analytes. In the practical applications, the sensor NCB can be utilized as low cost food spoilage indicator and soil analysis by fluorometric method. 2024 Elsevier B.V. -
Depression, anxiety, stress and marital adjustment among women
Marriage, especially for women in a patriarchal society involves a huge transition process. The struggle with new responsibilities and expectations is overwhelming in itself. But with the feelings of worthlessness and feeling trapped and bound in a loveless and thankless bond, come distress and adjustment issues. According to a recent Nielsen survey on 'Women of Tomorrow', out of 21 nations and 6500 women, India is a leading nation when it comes to stress in women. About 87% of women were stressed most of the time and 82% claimed that they did not find time to relax. Women in the age range from 22 years to 55 years are the most stressed and are struggling hard to strike a balance between their home lives, social activities and jobs. The present study aims to examine depression, stress, anxiety and adjustment issues among women. A total of 80 married women were selected for the study with 40 working and 40 non-working women. The Revised Dyadic Adjustment Scale and Depression Anxiety Stress Scales were administered to collect data. Negative relationship was obtained between stress, anxiety depression and marital adjustment among married women. Anxiety and Marital adjustment are moderately correlated (-.346) while Stress (-.454) and Depression (-0.487) are highly correlated with marital adjustment. 2020 Journal of International Women's Studies. -
Deposition and characterization of ZnO/CdSe/SnSe ternary thin film based photocatalyst for an enhanced visible light-driven photodegradation of model pollutants
A heterogeneous photocatalytic pathway is a possible approach to global energy and environmental issues. Sol-gel spin coating and physical vapour deposition were used to create a new ternary ZnO/CdSe/SnSe nanocomposite thin film photocatalyst. X-ray diffractometry, energy-dispersive X-ray spectroscopy (EDS), field emission-scanning electron microscopy, UV-Vis, and photoluminescence (PL) spectrophotometers were used to characterize the deposited films. When exposed to solar light, the ternary photocatalyst exhibits high photocatalytic activity in photocatalytic dye degradation processes. it demonstrates excellent visible light absorption, enhanced charge carrier separation, and solar light simulation. It was proposed that the charge in the ternary ZnO/CdSe/SnSe photocatalyst moves in a double type-II and cascade manner between the various components. In this study, ternary thin film heterostructures are synthesized, exhibiting outstanding stability and solar light-induced photocatalytic activity.The thin film composed of ZnO/CdSe/SnSe exhibits a degradation efficiency of 96% when exposed to visible light, and a degradation efficiency of 90% for methylene blue under sunlight within a time period of 150 min. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Deposition and characterization of ZnO thin films on corning glass substrate using Magnetron sputtering
The Zinc Oxide (ZnO) thin films were deposited on corning glass substrates using RF Magnetron sputtering at a substrate temperature of 400 C and thicknesses of 1000 nm and 2000 nm. SEM, EDX, XRD, and UV-Vis spectrometers were used to analyse the thin films' morphological, structural, and optical characteristics. SEMwas used to analyse the surface morphology of the thin films. The composition of the created thin films was evaluated using EDX. XRD was used to examine the crystalline structure of the deposited ZnO films. Using the Debye-Scherrer equation, the average sample crystal size was determined. Uv-Vis was used to analyse the optical characteristics of the thin films. The findings showing how well-piezoelectric the produced thin films are may be useful in developing Surface Acoustic Wave Devices. 2024 Author(s). -
Deploying NLP techniques in Twitch application to comprehend online user behaviour
Sentiment analysis of emotion entails identifying and analyzing subjective information from language, such as views and attitudes, and helps to improve data visualization by employing a variety of strategies, tactics, and tools. New media channels have significantly changed how people interact, exchange ideas, and share information. Numerous businesses have begun to mine this data, concentrating on social media since it is a popular platform for customers to voice their ideas about various brands or goods and because it gives users an audience, enhancing the visibility and potential effect of this input. So far, as the internet expands and modern technology advances, new avenues have emerged with a higher ability to offer businesses pertinent feedback on their goods. The goal of this study is to investigate the many forms of online behaviour by analyzing chat interactions from the well-known streaming service Twitch. Emotes were occasionally employed in place of letters, to get attention, or to communicate emotions. We propose a system that may take in chat logs from a certain stream, use a sentiment analysis algorithm to classify each message, and then display the data in a way that might permit users to analyze the results according to its polarity (positive message, negative message, or neutral message). This application must be sufficiently versatile to be used with any platform broadcast type and to handle the datasets at very huge level. 2023 IEEE. -
Deploying NLP Techniques for Earnings Call Transcripts for Financial Analysis: A Reverse Phenomenon Paradigm
This study analyses the influence of quarterly board room discussions conducted in the form of "Earnings Call Transcripts"and company's stock price changes in the subsequent periods. In this study, sentiments were extracted from the "textual quarterly transcripts"of three major software companies for the last ten years. The extracted sentiments were statistically analyzed for patterns and types. The study led to the development of a new response variable called the 'Inverse Effect'. The 'Inverse Effect' simply refers to the discordance between the sentiment in the boardroom discussions available in the document form and changes in the stock price movements. If the sentiment for the current quarter is positive and the changes in the stock price movements is also positive in the subsequent quarter, it is considered as "concordance"and if the changes in the stock price movements is opposite to the sentiments it will be called as "discordance"which is the inverse effect. The study basically looks at the areas where the Weak Market Hypothesis (WMH) is not valid.The findings emerged from the study suggest a possible causality between the sentiments in the transcripts and the stock price changes. It was also found that sentiment polarity, three-quarter average stock price and the previous quarter stock price are the key determinants of the 'Inverse Effect'. Based on the findings from the study, appropriate machine learning models were developed and evaluated to predict the 'Inverse Effect' on the performance of individual stocks of a few select companies. 2023 IEEE. -
Deploying Fact-Checking Tools to Alleviate Misinformation Promulgation in Twitter Using Machine Learning Techniques
In the present era, the rising portion of our lives is spending interactions online with social media platforms. Thanks to the latest technology adoption as well as smartphones proliferation. Gaining news from the platforms of social media is quicker, easier as well as cheaper in comparison with other traditional media platforms such as T.V and newspapers. Hence, social media is being exploited in order to spread misinformation. The study tends to construct fake corpus that comprises tweets for a product advertisement. The FakeAds corpus objective is to explore the misinformation impact on the advertising and marketing materials for a particular product as well as what kinds of products are targeted mostly on Twitter to draw the consumers attention. Products include cosmetics, fashions, health, electronics, etc. The corpus is varied and novel to the topic (i.e., Twitter role in spreading misinformation in relation to production promotion and advertising) as well as in terms of fine-grained annotations. The guidelines of the annotations were framed through the guidance of domain experts as well as the annotation is done with two domain experts, which results in higher quality annotation, through the agreement rate F-scores as higher as 0.976 using text classification. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Depletion studies in the interstellar medium
We report interstellar Si depletion and dust-phase column densities of Si along 131 Galactic sight lines using previously reported gas-phase Si II column densities, after correcting for the differences in oscillator strengths. With our large sample, we could reproduce the previously reported correlations between depletion of Si and average density of hydrogen along the line of sight () as well as molecular fraction of hydrogen (f(H2). We have also studied the variation of amount of Si incorporated in dust with respect to different extinction parameters. With the limitations we have with the quality of data, we could find a strong relation between the Si dust and extinction. While we cannot predict the density dependent distribution of size of Si grains, we discuss about the large depletion fraction of Si and the bigger size of the silicate grains. 2013 AIP Publishing LLC. -
Depiction ofNifty Midcap Index Efficiency Using ARIMA
In recent years, the desirability of midcaps in Indian stock markets has received considerable attention from researchers, academicians, and financial analysts due to expectation of multi-bagger returns. The present study is undertaken to determine the market efficiency of Indian stock market using Nifty Midcap Index at High Frequency. The market efficiency of Nifty Midcap Index is determined using ARIMA technique. The fitted ARIMA model had a MASE value close to one. Hence, the findings suggest that the Nifty Midcap Index is inefficient. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Dependence of Eigen frequency on the output performance of a piezoelectric nano sensor: A comparative study
Energy harvesting is an approach to generating electricity that uses the energy of the local environment directly. Instead of relying on batteries or power generated elsewhere, the world needs a new generation of energy-producing products. Generation or accumulation and energy consumption must be balanced when designing such a system. Before implementation into the real world, simulations are available for optimizing device designs, comparing them, predicting them, and formulating methodologies. In this comparative study, using a finite element simulation software COMSOL Multiphysics, an Eigen frequency analysis is performed to validate the relationship between Eigen frequency and output voltage and also shows how much the selection of a piezo electric base material depends on the natural frequency, excitation frequency, and output voltage relationship. A piezoelectric sensor is constructed with an initial base material and using material sweeps, another six materials are added and switched for the purpose. After applying allowable stress and frequency analysis, measured the output electric potential for the first five eigenmodes. Selecting seven different piezo electric base materials that possess unique properties from traditional lead zirconate titanate (PZT) to upcoming polymer material polyvinylidene fluoride (PVDF), there reveals the role of selecting suitable energy harvesting medium in generating proper output. From the experimented materials, zinc oxide (ZnO), aluminum nitride (AlN), and PVDF are found to be reliable towards the resonance concept and attaining optimum electric potential. Thus, our study strongly supports previous works carried out by the researchers regarding the effect of various piezo electric base materials on output response. 2023 -
Dependence between Sugar Industry Specific Factors and Sugar Companies Share Prices: Evidence from India
We assess the effects of sugar industry-specific macroeconomic factors on share prices of sugar companies in India using quantile regression approach from January 2001 to December 2017. We detect grounds to affirm the dependence between sugar industry specific macroeconomic factors and sugar companies share prices. The results indicate that the change in sugarcane cultivation area has both positive and negative effect on the share prices of sugar companies. Further, it shows that the impact of sugar production on share prices of sugar companies varies across the different quantiles except an insignificant effect on two companies for all quantiles. Moreover, most of the companies share prices are highly and positively influenced by sugar import. The study pointed out that the risk of sugar industry specific macroeconomic factors noticed in the sugar companies share prices is heterogenous. Indian Institute of Finance Vol. XXXVI No. 4, December 2022. -
Denial of Service Attacks in the Internet of Things
A DoS attack is the most severe attack on IoT and creates a crucial challenge for the detection and mitigation of such attacks. A DoS attack occurs at multiple layers of the IoT protocol stack and exploiting the protocol vulnerabilities disrupts communication. Traditional mechanisms employ single-layer detection of DoS attacks, which individually detect and mitigate attacks. However, it is essential to establish a general framework for detecting DoS attacks in a real-time environment and coping with diversified applications. This can be achieved by fetching attack features of multiple layers to create a pool of numerous attacks and then designing a system that detects the attack when fed with specific attack features. This chapter comprehensively analyzes the research gap in the DoS attack detection techniques proposed. Secondly, we offer a two-stage framework for DoS attack detection, comprising Fuzzy Rule Manager and Neural Network (NN), to detect cross-layer DoS attacks in real time. The Input Data Type (IDT) is derived using a fuzzy rule manager that can identify the type of input dataset as usual or attack in real time. This IDT is passed to the NN along with the real-time dataset to increase detection accuracy and decrease false alarms. 2024 selection and editorial matter, Vinay Chowdary, Abhinav Sharma, Naveen Kumar and Vivek Kaundal; individual chapters, the contributors. -
Denial of Desire Depictions of Elderly Intimacy in Malayalam Cinema
[No abstract available] -
Demystifying Data Justice: Legal Response To India's Privacy And Security Standards: Challenges In Cloud Computing
Data is the new oil of this economy. Cloud Computing acts in the capacity of storing databases, in operational analytics, networking and intelligence. Indian cloud computing market is valued at 2.2 billion dollars, which is said to scale by 30 percent in 2022. It's therefore pertinent to understand Indian's data protection landscape in the light of Personal Data Protection Bill, 2018 to answer the questions of ownership, controlling, processing of data in order to reflect upon the liability, obligations, and compliances by intermediaries, dispute resolution forums, data portability and indemnification. The authors will explore by means of doctrinal method, the challenges posed on the content regulatory mechanism for the internet architecture which paves responsibility of data classification into lawful and unlawful, with the exception of section 79 of Information Technology Act. The authors will further examine the encryption standard tools exhibiting data security and the obstacles created by the 40-bit limit encryption standard as part of the DoT's telecom licensing conditions and section 84A IT Act, 2008, to provide suggestions towards pragmatic delimitation. Cloud computing being the next growth frontier of the IT industry, makes it more evident to enable cloud forensics in entrusting with investigations and establishing confidence within the end-users. Goal 16 of SDG's deal with Promote just, peaceful and inclusive societies. The Electrochemical Society -
Demystifying artificial intelligence and customer engagement: A bibliometric review using TCCM framework
Artificial intelligence (AI) has grabbed the attention of the extent of literature and customer engagement of many business organizations in the past decade, especially with the advancement of machine learning and deep learning. However, despite the great potential of AI to solve customer problems and engage customers, there are still many issues related to practical uses and lack of knowledge to create value through customer engagement. In this context, the present study aims to full fill the gap by providing a critical literature review based on 53 A* and A categories of Australian Business Deans Council (ABDC) journals (2011-2023) by highlighting the benefits, challenges, framework, and future research directions in theory, context, characteristic and methodology (TCCM) areas. These findings contribute to both theoretical and managerial perspectives for developing a future novel theory and new forms of management practices. 2024, IGI Global. All rights reserved. -
Demography-Based Hybrid Recommender System for Movie Recommendations
Recommender systems have been explored with different research techniques including content-based filtering and collaborative filtering. The main issue is with the cold start problem of how recommendations have to be suggested to a new user in the platform. There is a need for a system which has the ability to recommend items similar to the users demographic category by considering the collaborative interactions of similar categories of users. The proposed hybrid model solves the cold start problem using collaborative, demography, and content-based approaches. The base algorithm for the hybrid model SVDpp produced a root mean squared error (RMSE) of 0.92 on the test data. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Demographic Variables Influence on Work Engagement of Nurses and Doctors in Hospitals.
It has been foreseen that the healthcare sector in India will be at par with the IT services as well as education in terms of revenue, and would largely contribute to the countrys economy. The health-care industry is presently worth $ 7 Billion dollars (USD), and is predicted to grow at the rate of 13% every year. At this pace, work levels in hospitals have increased, and an employees contribution towards work has decreased. The psychological connection of employees towards their work has gained critical importance; as organizations find that their employees are not giving their best in these times when the demand is on its rise. Work engagement is a positive-fulfilling work-related state of mind characterized by vigor, dedication and absorption, where vigor being high energy levels and mental resilience, dedication being a state of mind where an individual is strongly involved in ones work, and absorption is characterized by engrossment and concentration towards ones work. Literature review on work engagement from the last decade has focused on the relationship of engagement with job satisfaction, employee turnover, performance, and other human resource related constructs. A sample of 372 respondents comprising of doctors and nurses form 20 hospitals (corporate, government and private/trust) of 150 beds and above. Respondents were chosen by using judgmental sampling technique. The variables under investigation were Work engagement and eight demographic characteristics of the respondents. Utrecht Work engagement scale (UWES), by Wilmar Schaufeli and Arnold Baker, (2003), and based on the objectives the eight demographics were included. Fourteen hypotheses were tested and the major findings were that the overall work engagement for doctors was significantly high, and for nurses it was found to be moderate. Significant difference on work engagement levels on doctors was found across gender, educational qualification, age of the respondents, marital status, number of children, and types of hospitals. No significant difference on work engagement levels was found across work experience for doctors. Significant difference on work engagement levels on nurses was found across educational qualification, age of the respondents, work experience, marital status, number of children, and type of hospitals for nurses. No significant difference on work engagement levels was found across gender for nurses. Implications suggested that hospitals develop a flexible training, and therapeutic program for men and women to manage stress customized to their requirement. Focus should be given on encouraging employees to continue higher education. Younger and less experienced employees should be encouraged to interact with senior staff as their sharing of ideas and thoughts would be beneficial to both older and younger employees. Hospitals should imbibe values and ethics which are based on compassion, love for mankind and development of society through good leadership which would inspire them to go that extra mile. Key words: Work engagement, Demographic influence, Doctors, Nurses.