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An Integrated Reinforcement DQNN Algorithm to Detect Crime Anomaly Objects in Smart Cities
In olden days it is difficult to identify the unsusceptible forces happening in the society but with the advancement of smart devices, government has started constructing smart cities with the help of IoT devices, to capture the susceptible events happening in and around the surroundings to reduce the crime rate. But, unfortunately hackers or criminals are accessing these devices to protect themselves by remotely stopping these devices. So, the society need strong security environment, this can be achieved with the usage of reinforcement algorithms, which can detect the anomaly activities. The main reason for choosing the reinforcement algorithms is it efficiently handles a sequence of decisions based on the input captured from the videos. In the proposed system, the major objective is defined as minimum identification time from each frame by defining if then decision rules. It is a sort of autonomous system, where the system tries to learn from the penalties posed on it during the training phase. The proposed system has obtained an accuracy of 98.34% and the time to encrypt the attributes is also less. 2021. All Rights Reserved. -
Efficacy of Natural Zeolite and Metakaolin as Partial Alternatives to Cement in Fresh and Hardened High Strength Concrete
Urbanization and industrialization have dramatically increased the manufacture of cement causing substantial pollution of the environment. The primary global concern related to cement manufacture has been the management of the large carbon footprints. The usages of environmentally friendly cementitious materials in the construction of structures have proved to be a viable option to deal with this environmental concern. Therefore, it is necessary to further explore the usage of cementitious materials which can replace cement albeit partially. In this direction of research, two such cementitious materials, namely, natural zeolite and metakaolin have been investigated in this study. High-strength concrete M60 with natural zeolite and metakaolin as the partial replacements for the cement has been prepared in this work. Polycarboxylic ether-based superplasticizer solution has been used to enhance workability. The test specimen cast and cured for 3, 7, 28, 60, and 90 days at ambient room temperature has been tested for compressive strength, split tensile strength, and flexural strength as per the Indian standards. The optimum mix of high-strength concrete thus manufactured has met the Indian standards, and the combination of cement +5% natural zeolite +10% metakaolin has exhibited the highest compressive, split tensile, and flexural strengths at 90 days of curing. Natural zeolite and metakaolin when used in smaller proportions have increased the concrete strength, and these materials are recommended for partial replacement of cement. 2021 Iswarya Gowram et al. -
DROUGHT MITIGATION THROUGH HYDROGEL APPLICATION IN RICE (Oryza sativa L.) CULTIVATION
Sustainability in irrigation is an essential step towards responsible water consumption. In recent years, many studies have sketched climate-resilient agricultural practices to fight drought and uncertain rainfall patterns. Major rain-fed crops such as paddy and wheat require aid when there are abnormal dry spells. To mitigate the loss of crops from such events, superabsorbent polymers can be used. Soils amended with hydrogel or Superabsorbent polymer (SAP) retain moisture during drought to prevent loss of water through evaporation and percolation. This allows the crop to grow with less shock from drought. This study compares rice (Oryza sativa L.) growth rate under application (treatment groups) and non-application (control groups) of hydrogel, considering their high-water requirement. NDLR07 (recently developed) and BPT5204 (local variety) rice varieties were chosen for the current study. Randomized controlled trials were performed for each variety on a control group (NC & BC) and 3 treatment groups with 20% (NT20 & BT20), 40% (NT40 & BT40), and 60% (NT60 & BT60) deficit water supplies respectively. N, T, C refers to seed type, treatment group, control group respectively. Intermittent drought condition was imposed for 14 days to assess the resilience of crops. The water retention capacity of the sandy loam soil was better for treatment groups by 20% than control groups even at an average temperature of 40 ?. Treatment groups continued growing through the drought phase and after, while control groups showed stagnation. Among the tested treatment groups, NT20 had the highest growth among all trials. The results of the study suggested that hydrogel application can help to combat droughts and thereby contribute to sustainable agricultural production by restricting the involvement of climate changes. 2021, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved. -
Parametric effect on machining characteristics of laser machined Al7075TiB2 in-situ composite
The effect of laser parameters on the machining characteristics of an Al7075 based in-situ metal matrix composite reinforced with Titanium diboride(TiB2) is investigated. The cutting speed (at 10001200 m/hr), stand-off distance (SOD) (0.30.5 mm), and gas pressure (0.50.7 bar) were studied. Scanning electron microscopy (SEM) was used to validate the machining behaviour of in-situ composites. Surface roughness and dimensional error decrease as the SOD increases up to 0.4 mm, but both increases as the SOD increases to 0.5 mm. whereas the volumetric material removal rate (VMRR) increases up to 0.4 mm SOD and then decreases as SOD increases (0.5 mm). Surface roughness, VMRR, and dimensional error were all found to increase with laser speed. Surface roughness and dimensional error increase as gas pressure increase up to 0.5 bar, then decreases. The VMRR, on the other hand, increased continuously as the assist gas pressure increased. Copyright 2021 Inderscience Enterprises Ltd. -
A computational approach for shallow water forced KortewegDe Vries equation on critical flow over a hole with three fractional operators
The KortewegDe Vries (KdV) equation has always provided a venue to study and generalizes diverse physical phenomena. The pivotal aim of the study is to analyze the behaviors of forced KdV equation describing the free surface critical flow over a hole by finding the solution with the help of q-homotopy analysis transform technique (q-HATT). he projected method is elegant amalgamations of q-homotopy analysis scheme and Laplace transform. Three fractional operators are hired in the present study to show their essence in generalizing the models associated with power-law distribution, kernel singular, non-local and non-singular. The fixed-point theorem employed to present the existence and uniqueness for the hired arbitrary-order model and convergence for the solution is derived with Banach space. The projected scheme springs the series solution rapidly towards convergence and it can guarantee the convergence associated with the homotopy parameter. Moreover, for diverse fractional order the physical nature have been captured in plots. The achieved consequences illuminates, the hired solution procedure is reliable and highly methodical in investigating the behaviours of the nonlinear models of both integer and fractional order. 2021 Balikesir University. All rights reserved. -
Towards an Epistemology of Reading: Defining the Process of Reading in Modern Terms
The chaotic space caused by information explosion in present times has made the process and purpose of reading to be always questioned. Technological advancement has made reading appear as a mere mockery at the very outset. But the world still prioritizes knowledge that is acquired through observation, valuation and interpretation. At the time of Big Data, there still persists a sense of agency to define a given information as episteme. The present essay emphasizes on looking at reading as a modern phenomenon by presupposing the epistemological presence at the centre of any rational pursuit. Based on the Kantian precepts on enlightenment, the paper attempts to understand this presence of knowledge by delving into the major disciplines of modern philosophy that help in observing, valuing and interpreting the act of reading in present times. More than laying terms for defining the text within the modern space, the study essentializes reading in a virtually driven algorithmic world. AesthetixMS 2021 -
Transmission Jeopardy of Adenomatosis Polyposis Coli and Methylenetetrahydrofolate Reductase in Colorectal Cancer
Colorectal cancer (CRC) is one of the globally prevalent and virulent types of cancer with a distinct alteration in chromosomes. Often, any alterations in the adenomatosis polyposis coli (APC), a tumor suppressor gene, and methylenetetrahydrofolate reductase (MTHFR) gene are related to surmise colorectal cancer significantly. In this study, we have investigated chromosomal and gene variants to discern a new-fangled gene and its expression in the southern populations of India by primarily spotting the screened APC and MTHFR variants in CRC patients. An equal number of CRC patients and healthy control subjects ((Formula presented.)) were evaluated to observe a chromosomal alteration in the concerted and singular manner for APC and MTHFR genotypes using standard protocols. The increasing prognosis was observed in persons with higher alcoholism and smoking ((Formula presented.)) with frequent alterations in chromosomes 1, 5, 12, 13, 15, 17, 18, 21, and 22. The APC Asp 1822Val and MTHFR C677T genotypes provided significant results, while the variant alleles of this polymorphism were linked with an elevated risk of CRC. Chromosomal alterations can be the major cause in inducing carcinogenic outcomes in CRCs and can drive to extreme pathological states. 2021, SAGE Publications Ltd. All rights reserved. -
Corpus based sentimenal movie review analysis using auto encoder convolutional neural network
In natural language processing, most prominent branch is sentiment analysis. Peoples emotions and attitudes are analyzed using this sentiment analysis towards service, some product, etc. In prediction of the future scope of a product, some benefits are given by sentiment analysis. However, manual analysis of such a huge amount of documents is a highly tedious task, especially with limited time. Hence, for solving this problem, various attempts are made in literature and proposed different sentiment analysis methods. However, in generation of lexicon, popular NLP tools has some drawbacks. The accuracy of lexicons based on humans is less and they are limited too. On the other hand, lexicons based on dictionary are highly general and they are domain specific. So, a technique called Corpus Integrated Autoencoder Convolutional Neural Network based Sentiment Analysis (CI-AECNN) is proposed in this work for solving this issue. The sentiment lexicon generation based on corpus is performed in this work. Candidates sentiment orientation are computed using this and seed lexicon are added with recognized sentiment words and from seed lexicon, words with incorrect sentiment are removed. The long short-term memory (LSTM) is used for performing Word Sense Disambiguation. Conditional random fields are used for extracting features. At last, auto-encoder, convolutional neural network is used for performing classification. In MATLAB simulation environment, conducted this research works overall analysis and it indicates that better results are produced by proposed technique when compared with available techniques. 2021 Taru Publications. -
Indian government bonds sensitivity to macroeconomic and non-macroeconomic factors: A quantile regression approach
This paper introduces a new dataset of Clearing Corporation of India Limiteds broad total return index (BTRI) and liquid total return index (LTRI). The paper examines the impact of macroeconomic and non-macroeconomic factors on BTRI and LTRI during monthly periods from January 2010 to December 2018 using quantile regression methodology. This paper finds that the GDP has positive and significant impact on BTRI and LTRI for the upper quantiles. Further, CPI shows positive impact on both BTRI and LTRI. Moreover, both the indices are influenced by IR and there is an inverse relationship between them. ER also significantly affects both the indices. The EPUI has negative and significant impact on BTRI and LTRI for the intermediate and upper quantiles. No clear relationship is found between BTRI and Nifty, whereas Nifty has significant impact on LTRI. BTRI is not affected by VIX but LTRI is affected for the intermediate quantiles. Copyright 2021 Inderscience Enterprises Ltd. -
Market Reaction to Dividend Announcements During Pandemic: An Event Study
This study analyses the difference in stock market reactions to dividend announcement during the pandemic. The thirty constituent stocks of Sensex, the index of Bombay Stock Exchange (BSE), is used for analysis. This allows cross-industry comparison of the market reaction. The study examines stock market reactions covering 44 days around the dividend announcement dates. The primary objective of this study is to understand whether the price adjustment linked to the dividend announcement news during the pandemic was different from the earlier years. This empirical study employs the conventional event study methodology using abnormal returns (ARs) to examine the stock market reaction to dividend announcement. The market reaction to dividend announcement was increasingly positive during the pandemic, compared to previous years. The statistical pooled t-tests showed there was a significant relationship between the pandemic and ARs. The findings also indicate that the difference in the market reaction to dividend announcement was more prominent in services stocks than that in manufacturing. Further, the results also verify the weak-form of efficiency of Indian stock exchange. 2021 Management Development Institute. -
Selfie Segmentation in Video Using N-Frames Ensemble
Many camera apps and online video conference solutions support instant selfie segmentation or virtual background function for entertainment, aesthetic, privacy, and security reasons. A good number of studies show that Deep-Learning based segmentation model (DSM) is a reasonable choice for selfie segmentation, and the ensemble of multiple DSMs can improve the precision of the segmentation result. However, it is not fit well when we apply these approaches directly to the image segmentation in a video. This paper proposes an N-Frames (NF) ensemble approach for a selfie segmentation in a video using an ensemble of multiple DSMs to achieve a high-performance automatic segmentation. Unlike the N-Models (NM) ensemble which executes multiple DSMs at once for every single video frame, the proposed NF ensemble executes only one DSM upon a current video frame and combines segmentation results of previous frames to produce the final result. For the experiment, we use four state-of-the-art image segmentation models to make an ensemble. We evaluated the proposed approach using 81 videos dataset with a single-person view collected from publicly available websites. To measure the performance of segmentation models, Intersection over Union (IoU), IoU standard deviation, false prediction rate, Memory Efficiency Rate and Computing power Efficiency Rate parameters were considered. The average IoU values of the Two-Models NM ensemble, Two-Frames NF ensemble, Three-Models NM ensemble and Three-Frames NF ensemble were 95.1868%, 95.1253%, 95.3667% and 95.1734% each, whereas the average IoU value of single models was 92.9653%. The result shows that the proposed NF ensemble approach improves the accuracy of selfie segmentation by more than 2% on average. The result of cost efficiency measurement shows that the proposed method consumes less computing power like single models. 2021 IEEE. -
Multi-class SVM based network intrusion detection with attribute selection using infinite feature selection technique
An intrusion detection mechanism is a software program or a device that monitors the network and provides information about any suspicious activity. This paper proposes a multi-class support vector machine (SVM) based network intrusion detection using an infinite feature selection technique for identifying suspicious activity. Single and multiple classifiers generally have high complexity. To overcome all the limitations of single and multiple classifiers, we used a multi-class classifier using an infinite feature selection technique, which performed well with multiple classes and gave better results than other classifiers in terms of accuracy, precision, recall, and f_score. Infinite feature selection is a graph-based filtering approach that analyses subsets of features as routes in a graph. We used a standard dataset, namely the UNSW_NB15 data set generated by the IXIA perfect-storm tool in the Australian Centre for Cyber Security. This dataset has a total of nine types of attacks and 49 features. The comparative analysis of the manuscript work is done against eight different techniques, namely, hybrid intrusion detection system (HIDS), C5, one-class support vector machine, and others. The proposed work gave better simulation results using the 2015a Matlab simulator. 2021 Taru Publications. -
Value Addition for Technology Start-Ups Through Physical Co-Location
Numerous economic theories, knowledge, social, and communication theories have extensively explored the phenomenon of physical co-location in various contexts. However, limited scholarly attention has been given to co-location in emerging contexts such as co-working spaces, predominantly used by start-ups. One of the critical questions examined is how co-location adds value to technology start-ups in the early and growth stages of their development. We chose a premium coworking space in Bangalore, Indias start-up capital, as the studys research setting during January March 2020. The qualitative research employed semi-structured interviews to explore the phenomenon. Our findings revealed that start-ups actively used co-located resources to explore, experiment, and validate new business ideas in the early stage. As they transitioned into the growth phase, they exploited co-located industry networks to expand into new markets. They also learned vicariously from other co-located resources and used them to solve complex problems and refined their processes and routines. As start-ups begin to grow and expand, co-location infrastructure-related costs are not justifiable, operations are less secure, and the meta culture of the co-located environment is in conflict with the firms operating culture. The results of this study have the potential to be significant for technology start-ups that are exploring new ways of working and addressing uncertainties during the early and growth stages of their development. 2021, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Comic Memes and Sexist Humor in India: Tools for Reinforcement of Female Body-Image Stereotypes
Memes have been described as communicative and aesthetic practices that serve cultural, social, political purpose on a digital platform. Several studies, in the last decade, have attempted to study this digital aesthetic knowledge production as a powerful tool for political, racial, and gender-related discourses. Most often this knowledge is produced through comic multi-media texts. Many theorists believe that, digital media reinforces inequality, marginalization and such other social issues through the audio-visual-textual medium as much as it establishes the counter-discourses for equality, body activism, racial activism and the like. Speed and lack of censorship can be the cardinal reasons for the popularity of these memes. Among the mass-influencing gender-related memes are those encouraging fat-talk and body-image stereotypes. In the Indian context, 'Tag a Friend' memes is one such widely circulated meme which communicates body-shaming messages through sexist humor. It mainly targets the fat/colored/transgender women. The current study examines these memes using multimodal discourse analysis methodology. The paper attempts to investigate the revival/reproduction potential of color-shaming and body-shaming stereotypes via comic memes through Shiffman's memetic dimensions. The analysis establishes that memes can be a prominent site for the re-production of the problematic ideology of body/color shaming even in the 21st century. AesthetixMS 2021 -
SCREEN TIME BEYOND GAMING AND SOCIAL MEDIA: EXCESSIVE AND PROBLEMATIC USE OF OVER THE TOP (OTT) PLATFORMS AMONG COLLEGE STUDENTS DURING COVID-19 PANDEMIC
There is a gap in existing literature regarding Over the Top (OTT) platform use contributing to the excessive and problematic screen time. We aimed to assess OTT platform use among college students and its associations with increased screen time, mental well-being, COVID-19 related anxiety and personality traits. A total of 1039 students from a college in India were invited to participate in this web-based survey. A majority of participants used OTT platforms regularly. Subscription to paid OTT platforms, poor mental well-being were associated with problematic OTT use; whereas personality trait of conscientiousness seemed to offer protection against problematic OTT use. 2021 Medicinska Naklada Zagreb. All rights reserved. -
Information Management Capacity and Supply Chain Performance: Mediating Effects of Supply Chain Practices, Competencies and Concerns
The present study aims to identify the impact of the information management capacity (IMC) of an organization on its supply chain performance (SCP). Also, this study attempts to understand the mediating role of the various components of supply chain management, namely, practices, competencies and concerns. A survey instrument was used to collect primary data from 250 SMEs which were selected randomly. Structural equation modeling (SEM) technique is used to test the hypotheses using SmartPLS. The final model indicated that information management capacity significantly influences the supply chain performance and supply chain management components, namely supply chain competence, practices and concerns mediate the relationship between information management capacity and supply chain performance. The results of this study provide a significant contribution to the theory of resource-based view. The number of managerial perspectives for improving operational capabilities was explained in this study. 2021 Management Development Institute. -
Cytogenetic Consequences Of Food Industry Workers Occupationally Exposed To Cooking Oil Fumes (Cofs)
Background: Cooking oil fumes (COFs) with smoking habits is a substantial risk that aggravates genetic modifications. The current study was to estimate the biological markers of genetic toxicity counting Micronucleus changes (MN), Chromosome Aberrations (CA) and DNA modifications among COFs exposures and control subjects inherent from South India. Materials and Methods: Present analysis comprised 212 COFs with tobacco users and equivalent number of control subjects. Results: High frequency of CA (Chromatid type: and chromosome type) were identified in group II experimental subjects also high amount of MN and DNA damage frequency were significantly (p < 0.05) in both subjects (experimental smokers and non-smokers). Present analysis was observed absence of consciousnessamong the COFs exposures about the destructive level of health effects of tobacco habits in working environment. Conclusion: COFs exposed workers with tobacco induce the significant alteration in chromosomal level. Furthermore, a high level of rate of genetic diseases (spontaneous abortion) were identified in the experimental subjects. This finding will be helpful for preventive measures of COFs exposed workers and supportive for further molecular analysis 2021,Asian Pacific Journal of Cancer Prevention. All Rights Reserved. -
Factors Affecting Digital Visibility of Small and Medium Enterprises in India
This study sketches the importance of social media, integrated marketing communication, social customer relationship management and its transformation in the small and medium enterprises (SME). These factors can increase interaction and communication of SMEs with its customers. This study incorporates empirical method to elaborate how SMEs can increase visibility and reachability by gaining value through the usage of social media. Findings of the study highlight the challenges faced by SMEs with respect to visibility, examines the usage of different digital platforms by Indian SMEs which can resolve these difficulties and its impact on the business for improved visibility of SMEs when competition is hitting hard on all businesses. 2021 Management Development Institute. -
Optimized Tree Strategy with Principal Component Analysis Using Feature Selection-Based Classification for Newborn Infant's Jaundice Symptoms
One of the most important and difficult research fields is newborn jaundice grading. The mitotic count is an important component in determining the severity of newborn jaundice. The use of principal component analysis (PCA) feature selection and an optimal tree strategy classifier to produce automatic mitotic detection in histopathology images and grading is given. This study makes use of real-time and benchmark datasets, as well as specific approaches for detecting jaundice in newborn newborns. According to research, the quality of the feature may have a negative impact on categorization performance. Additionally, compressing the classification method for exclusive main properties can result in a classification performance bottleneck. As a result, identifying appropriate characteristics for training the classifier is required. By combining a feature selection method with a classification model, this is possible. The major outcomes of this study revealed that image processing techniques are critical for predicting neonatal hyperbilirubinemia. Image processing is a method of translating analogue images to digital formats and manipulating them. The primary goal of medical image processing is to collect information useful for disease detection, diagnosis, monitoring, and therapy. Image datasets can be used to validate the performance of newborn jaundice detection. When compared to conventional approaches, it offers results that are accurate, quick, and time efficient. Accuracy, sensitivity, and specificity, which are common performance indicators, were also predictive. 2021 Debabrata Samanta et al. -
Development of an efficient real-time H.264/AVC advanced video compression encryption scheme
Multimedia is the combination of media such as text, graphics, video clips, and audio files. In todays world, multimedia plays an important role in many applications that we use in our daily lives. It is used in educational software, animation, sound, and text, as well as multi-media software. H.264/AVC video compression is extremely efficient in terms of compression. Despite this, H.264/AVC requires a lot of processing and consumes a lot of power insdespite of the fact that its compression efficiency is lower than that of H.264/AVC. We examine the various methods of Video H.264 Advanced Video Compression Standard Encryption Schemes in this paper. The performance of all types of encryption techniques will be evaluated using parameters such as cost overhead, delay, and encryption quality. This will provide us with a detailed comparative analysis of video encryption schemes, allowing us to determine which one is far more efficient for H.264/AVC. 2021 Taru Publications.