Self-Discrepancy as a Moderator Between Romantic Attachment and Body Image Satisfaction
Body image; Intimacy; Romantic attachment; Self-discrepancy; Trust
Body image satisfaction is about appreciating our body the way it is. One's romantic attachment style with their partner may impact their body image which this study wants to assess. The present study looks at romantic attachment and its effect on body image satisfaction, with self-discrepancy playing the moderator's role. Romantic attachment was measured through avoidance and anxiety dimensions along with trust, commitment, intimacy, physical proximity, support, and partner's suggestions on dressing and looks. Individuals in the age group of 18-25 in a romantic relationship (N=170) were sent an online questionnaire. The questionnaire included scales on body image satisfaction, self-discrepancy and romantic attachment. Correlations results revealed that attachment styles and specifiers of romantic relationships correlate highly with body satisfaction. Regression results indicated a high impact with attachment-related emerging as the single most impactful predictor for the model. The findings from the study can be used by individual and couple therapists dealing with romantic and body image concerns. In a period where romantic relationships are becoming very important in young adults' lives, this study probes into the possibility of romantic relationships affecting body image issues. Studies in the past have given more importance to body image dissatisfaction and parental attachment but this study looks at body satisfaction along with romantic attachment. In a collectivistic Indian culture where the concept of dating is gradually gaining popularity, the findings of this study are unique. 2021 RESTORATIVE JUSTICE FOR ALL.
Krishnamurthy V., Deemed to be University, NCR, Delhi, India; Chukkali S., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India
ON THE GENERALIZED COMPLEMENT OF SOME GRAPHS
comb graph; complement of graph; partition; twin prime
In this paper we study the generalized complement of the graph Gm,n = (V, E) for some values of m, n. We study the generalized complement of Gm,n graphs with respect to the equal degree partition. The 2?complement of Gm,n graphs are also determined for m = 2, n is even or odd. In particular, for some values of m, n ? N, we studied the complement of Gm,n graphs with respect to the equal degree partition and the 2?complement of Gm,n graphs. We determine the partitions Pk, k ? N of the vertex set V such that the generalized complement of Gm,n graph is a path graph and a comb graph. 2021, Asia Pacific Academic. All rights reserved.
Chakrabarty I.; Acharya M.; Kureethara J.V.
Asia Pacific Journal of Mathematics, Vol-8
https://doi.org/10.28924/APJM/8-22 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127783608&doi=10.28924%2fAPJM%2f8-22&partnerID=40&md5=7950d3b274fcd502d0dee821c75323eb
Chakrabarty I., Department of Mathematics, Christ University, India; Acharya M., Department of Mathematics, Christ University, India; Kureethara J.V., Department of Mathematics, Christ University, India
Functional response, host stage preference and development of Rhynocoris fuscipes (Fab.) (Heteroptera: Reduviidae) for two cotton pests
Biocontrol; Comparative biology, life table; Cotton pests; Rhynocoris fuscipes, Runctional response
Considering the indispensable role of reduviid predators in ecofriendly pest management programme, the relationship between a predatory reduviid, Rhynocoris fuscipes, and three prey species viz., red cotton bug Dysdercus koenigii Fab. (Heteroptera: Pyrrhocoridae), cotton mealybug Phenacoccus solenopsis (Tinsley) (Hemiptera: Pseudococcidae) and rice flour moth Corcyra cephalonica Stainton (Lepidoptera: Pyralidae), were scrutinized and studied to determine the influence of host species on biology, host stage preference and biological control efficiency under laboratory conditions. Rhynocoris fuscipes completed nymphal stage in 41 days when feeding on C. cephalonica, 45 on D. koenigii, and 50 days on P. solenopsis. Adult longevity, fecundity and egg viability were higher in C. cephalonica fed category and the lowest on P. solenopsis. Life table parameters were in favor of C. cephalonica. Third instars of D. koenigii were favored by third and fourth instars of the predator. Fifth instars and adults of the predator had chosen fourth and fifth instars of D. koenigii, respectively. All instars of predator preyed on adults of P. solenopsis. It is observed that the reduviid responded to increased D. koenigii and P. solenopsis density with type II functional response. Positive interactions distinctly imply that there is a salutary effect on the pest as well. 2021, Crop Protection Research Centre. All rights reserved.
Journal of Biopesticides, Vol-14, No. 1, pp. 12-21.
https://doi.org/10.57182/jbiopestic.14.1.12-21 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123265811&doi=10.57182%2fjbiopestic.14.1.12-21&partnerID=40&md5=dbdcc01046a42bba4479f9046b2e598d
Tomson M., Department of Life Sciences, CHRIST University, Hosur Road, Karnataka, Bangalore, 560029, India
Early Identification and Detection of Driver Drowsiness by Hybrid Machine Learning
accidents; Driver drowsiness; facial expression; machine learning
Drunkenness or exhaustion is a leading cause of car accidents, with severe implications for road safety. More fatal accidents could be avoided if fatigued drivers were warned ahead of time. Several drowsiness detection technologies to monitor for signs of inattention while driving and notifying the driver can be adopted. Sensors in self-driving cars must detect if a driver is sleepy, angry, or experiencing extreme changes in their emotions, such as anger. These sensors must constantly monitor the driver's facial expressions and detect facial landmarks in order to extract the driver's state of expression presentation and determine whether they are driving safely. As soon as the system detects such changes, it takes control of the vehicle, immediately slows it down, and alerts the driver by sounding an alarm to make them aware of the situation. The proposed system will be integrated with the vehicle's electronics, tracking the vehicle's statistics and providing more accurate results. In this paper, we have implemented real-time image segmentation and drowsiness using machine learning methodologies. In the proposed work, an emotion detection method based on Support Vector Machines (SVM) has been implemented using facial expressions. The algorithm was tested under variable luminance conditions and outperformed current research in terms of accuracy. We have achieved 83.25 % to detect the facial expression change. 2013 IEEE.
Altameem A.; Kumar A.; Poonia R.C.; Kumar S.; Saudagar A.K.J.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ACCESS.2021.3131601 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120584518&doi=10.1109%2fACCESS.2021.3131601&partnerID=40&md5=d3db07c29350cac4cecb25a868493db6
Altameem A., Department of Computer Science, College of Applied Studies, King Saud University, Riyadh, 11495, Saudi Arabia; Kumar A., Department of Computer Science and Engineering, Swami Keshvanand Institute of Technology Management and Gramothan, Rajasthan, Jaipur, 302017, India; Poonia R.C., Department of Computer Science, Christ (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Kumar S., Department of Computer Science and Engineering, Christ (Deemed to Be University), Karnataka, Bengaluru, 560074, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
In silico Analysis of Stigmasterol from Saraca asoca as a Potential Therapeutic Drug Against Alzheimers Disease
Acetylcholinesterase; Alzheimers Disease; Molecular Docking; Quantitative Structure Activity Relationship
Improvements and advances in health care over the past few decades have increased life expectancy and quality of life. However, this has resulted in an increase in non-communicable diseases like dementia, Alzheimers Disease (AD), etc. AD most commonly affects the older population, but recent studies reveal that it can also affect people of any age group. As of now, there are no accessible treatments or therapies that reverse the progression of the disease. The few existing medications to treat AD include Donepezil (Aricept), Galantamine (Razadyne) and Rivastigmine (Exelon) provide only temporary relief and come with several side effects like diarrhoea, vomiting, nausea, fatigue, insomnia, loss of appetite, and weight loss. An effective and augmenting therapy with Cholinesterase inhibitors from natural products is gaining popularity among researchers. Plant sterols have been known to play roles in inhibiting proteins implicated in the development of AD. The present study highlights the significance and scope of Stigmasterol, a phytochemical in Saraca asoca in the alleviation of AD. Our study involving the use of QSAR, ADME, molecular interaction, and molecular docking has shown that Stigmasterol has the potential to be developed as a therapeutic drug to curb the progression of AD after thorough validation procedures. 2021 Har Krishan Bhalla & Sons.
Rajeev R.; Marathe S.D.; Niranjan V.; Sharma B.; Sarojini S.
Journal of Biologically Active Products from Nature, Vol-11, No. 45813, pp. 516-529.
Rajeev R., Department of Chemistry, CHRIST (Deemed to be University), Bangalore-29, India; Marathe S.D., Department of Biotechnology, RVCE, Mysuru Road, Bengaluru, 560059, India; Niranjan V., Department of Biotechnology, RVCE, Mysuru Road, Bengaluru, 560059, India; Sharma B., Department of Chemistry, CHRIST (Deemed to be University), Bangalore-29, India; Sarojini S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 29, India
Software Systems Security Vulnerabilities Management by Exploring the Capabilities of Language Models Using NLP
Security of the software system is a prime focus area for software development teams. This paper explores some data science methods to build a knowledge management system that can assist the software development team to ensure a secure software system is being developed. Various approaches in this context are explored using data of insurance domain-based software development. These approaches will facilitate an easy understanding of the practical challenges associated with actual-world implementation. This paper also discusses the capabilities of language modeling and its role in the knowledge system. The source code is modeled to build a deep software security analysis model. The proposed model can help software engineers build secure software by assessing the software security during software development time. Extensive experiments show that the proposed models can efficiently explore the software language modeling capabilities to classify software systems' security vulnerabilities. 2021 Raghavendra Rao Althar et al.
Althar R.R.; Samanta D.; Kaur M.; Alnuaim A.A.; Aljaffan N.; Aman Ullah M.
Computational Intelligence and Neuroscience, Vol-2021
All Open Access; Green Open Access; Hybrid Gold Open Access
https://doi.org/10.1155/2021/8522839 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122898212&doi=10.1155%2f2021%2f8522839&partnerID=40&md5=f0bb3c564264a93cba7fbfbf11b611d0
Althar R.R., Data Science Department, CHRIST Deemed to Be University, Karnataka, Bangalore, India, QMS, First American India Private Ltd., Karnataka, Bangalore, India; Samanta D., Department of Computer Science, CHRIST Deemed to Be University, Karnataka, Bangalore, India; Kaur M., School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea; Alnuaim A.A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, P.O. Box 22459, Riyadh, 11495, Saudi Arabia; Aljaffan N., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, P.O. Box 22459, Riyadh, 11495, Saudi Arabia; Aman Ullah M., Department of Computer Science and Engineering, International Islamic University Chittagong, Chittagong, Bangladesh
AI Diagnosis: Rise of AI-Powered Assessments in Modern Education Systems
Artificial Intelligence; Assessments; Learning; Machine Learning; Students
The literature on the limitations on the current archaic education system is limitless, the consequences of which have only been exacerbated in the current lockdown scenario. The timed evaluations have not only failed as an assessment tool during these times but research has shown there are increased rates of using unfair means and proctoring as a result. Not only was the system faulty to begin with, it is failing miserably under current lockdown situations. Simultaneously the current literature keeps positing that since technology has become an integral part of our life already, it would not be long before technology integrates with education and assessments. Taking into consideration the need and potential of an integrative system, this paper aims to explore how artificial intelligence can be effectively introduced into education and improve learning outcomes. The paper performs a Comprehensive Literature Review (CLR), and analyses data based on the framework developed by Onwuegbuzie and Frels (2015). The paper thus reviews literature with the aim to explore current models of AIEd and relevant psychological concepts relating to learning and career outcomes. The evidence is consistence with the rationale for research problem: current AI methodologies in education focus only on delivering learning material, using AI as a means, instead of taking into other factors improving learning and education outcomes. The subsequent literature review on the factors influencing learning outcomes establish that there are two main thematic influences on students learning and behavioral outcomes: inside-school and out of school factors, which have been further implored in context of technological advancements. 2021. Transnational Press London. All Rights Reserved.
Transnational Marketing Journal, Vol-9, No. 3, pp. 625-633.
https://doi.org/10.33182/tmj.v9i3.1323 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122444241&doi=10.33182%2ftmj.v9i3.1323&partnerID=40&md5=17a4ab20541bd8bb8aa0493671c5575f
Gupta P., Piyush Gupta, India; Yadav D., Diksha Yadav, Assistant Professor, Christ University, India; Dey R., Rajdeep Dey, India
Optimal order quantity with endogenous discounted partial advance payment and trade-credit for inventory model with linear time varying demand
Advance payment; Credit period; Endogenous discount; Inventory; Linear time dependent demand rate; Supply chain
When buyers seek extended credit periods from relatively less secure suppliers, the supplier requires co-operation from the buyer for purchase of raw materials, etc., in terms of partial advance payment. For a single buyer single supplier supply chain, we develop an inventory model with a hybrid payment policy combining discounted advance payment to supplier with the supplier permitting interest free delay period to the buyer when buyer has the option to make advance payment. For the advance, supplier offers discount and may allow the buyer to set the discount rate and the advance proportion. For a linear demand function in such a scenario, we maximise buyer's net profit rate through optimal choice of payment policy and the buyer's replenishment. We consider two situations with discount: 1) exogenous; 2) endogenous for the buyer. Optimal solution is characterised theoretically. Numerical example reveals that by choosing advance proportion appropriately, the profit rate in the endogenous case can be higher than that in the exogenous case even with lower discount. 2021 Inderscience Enterprises Ltd.. All rights reserved.
International Journal of Mathematics in Operational Research, Vol-20, No. 4, pp. 565-587.
https://doi.org/10.1504/IJMOR.2021.120154 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122854033&doi=10.1504%2fIJMOR.2021.120154&partnerID=40&md5=42265420e97c1c194996aac10065960d
Agrawal S., Department of Science, Christ University, NCR, Ghaziabad, Delhi, India; Banerjee S., School of Statistics, Devi Ahilya University, Indore, India; Gupta R., Prestige Institute of Management, MP, Gwalior, India
An Integrated Reinforcement DQNN Algorithm to Detect Crime Anomaly Objects in Smart Cities
Advanced Encryption Standard (AES); anomaly detection; crime rate prediction; HybridFly; RCNN; reinforcement; security attacks
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.
International Journal of Advanced Computer Science and Applications, Vol-12, No. 12, pp. 348-352.
https://doi.org/10.14569/IJACSA.2021.0121246 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122584024&doi=10.14569%2fIJACSA.2021.0121246&partnerID=40&md5=c45d17b08ac5a7e4eb4158fdee0957d6
Mandala D.J., Department of CSE, School of Engineering & Technology, CHRIST (Deemed to be University), Bengaluru, India; Akhila P., Department of CSE, Gayatri Vidya Parishad College of Engineering (A), Andhra Pradesh, Visakhapatnam, India; Reddy V.S., Department of IT, VBIT Telangana, India
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.
Gowram I.; Beulah M.; Sudhir M.R.; Mohan M.K.; Jain D.
Advances in Materials Science and Engineering, Vol-2021
Gowram I., Department of Civil Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bangalore, 560074, India; Beulah M., Department of Civil Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bangalore, 560074, India; Sudhir M.R., Department of Civil Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bangalore, 560074, India; Mohan M.K., Department of Science and Humanities, Christ (Deemed to Be University), Karnataka, Bangalore, 560074, India; Jain D., Department of Construction Technology and Management, Bule Hora University, POB 144 Oromia, Ethiopia
DROUGHT MITIGATION THROUGH HYDROGEL APPLICATION IN RICE (Oryza sativa L.) CULTIVATION
Agriculture; Drought; Hydrogel; Mitigation; Rice; Soil conditioning; Sustainability
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.
Reddy B.S.P.; Vasudevan S.; Mani S.K.; Uppaluri S.; Sudakar M.
Journal of Experimental Biology and Agricultural Sciences, Vol-9, No. 6, pp. 727-733.
Editorial board of Journal of Experimental Biology and Agricultural Sciences
Reddy B.S.P., Department of Civil Engineering, CHRIST (Deemed to be University), School of Engineering and Technology, Bengaluru, 560074, India; Vasudevan S., Department of Civil Engineering, CHRIST (Deemed to be University), School of Engineering and Technology, Bengaluru, 560074, India; Mani S.K., Department of Civil Engineering, CHRIST (Deemed to be University), School of Engineering and Technology, Bengaluru, 560074, India; Uppaluri S., Department of Civil Engineering, CHRIST (Deemed to be University), School of Engineering and Technology, Bengaluru, 560074, India; Sudakar M., Department of Agronomy, Pendekanti Krishi Vigyan Kendra, Kurnool, 518124, India
Parametric effect on machining characteristics of laser machined Al7075TiB2 in-situ composite
Al7075 alloy; cutting speed; gas pressure; in-situ composite; laser machining; SOD; stand-off distance
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.
Keshavamurthy R.; Manjoth S.; Pradeep Kumar G.S.; Kavya J.T.
International Journal of Computational Materials Science and Surface Engineering, Vol-10, No. 45750, pp. 165-183.
https://doi.org/10.1504/IJCMSSE.2021.121374 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127058142&doi=10.1504%2fIJCMSSE.2021.121374&partnerID=40&md5=34a266bd7873bf6767d8f64526ebb24e
Keshavamurthy R., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, India; Manjoth S., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, India; Pradeep Kumar G.S., Department of Automobile, Engineering, Christ (Deemed to be University), Bengaluru, 560078, India; Kavya J.T., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, India
A computational approach for shallow water forced KortewegDe Vries equation on critical flow over a hole with three fractional operators
Fixed point theorem; Force KdV equation; Fractional derivatives; q-Homotopy analysis transform technique
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.
International Journal of Optimization and Control: Theories and Applications, Vol-11, No. 3, pp. 52-67.
https://doi.org/10.11121/ijocta.2021.1177 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124367682&doi=10.11121%2fijocta.2021.1177&partnerID=40&md5=fb43043d6c97f1d4f4b2d7b78f65c3d9
Veeresha P., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University, Bengaluru, 560029, India; Yavuz M., Department of Mathematics and Computer Sciences, Faculty of Science, Necmettin Erbakan University, Konya, 42090, Turkey, Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Cornwall, TR10, United Kingdom; Baishya C., Department of Studies and Research in Mathematics, Tumkur University, Tumkur, 572103, India
Towards an Epistemology of Reading: Defining the Process of Reading in Modern Terms
Enlightenment; Epistemology; Hermeneutics; Modernism; Ontology; Phenomenology; Reading
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
Rupkatha Journal on Interdisciplinary Studies in Humanities, Vol-13, No. 4
https://doi.org/10.21659/RUPKATHA.V13N4.33 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122626718&doi=10.21659%2fRUPKATHA.V13N4.33&partnerID=40&md5=3634426e7e028376987daad8d61f7509
Arun D.M., Department of English, Pondicherry University, Puducherry, India, Department of English and Cultural Studies, BGR Campus, CHRIST (Deemed to be University), Bangalore, India
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.
Mohd Y.; Kumar P.; Kuchi Bhotla H.; Meyyazhagan A.; Balasubramanian B.; Ramesh Kumar M.K.; Pappusamy M.; Alagamuthu K.K.; Orlacchio A.; Keshavarao S.; Sampathkumar P.; Arumugam V.A.
JRAAS - Journal of the Renin-Angiotensin-Aldosterone System, Vol-2021
ISSN: 14703203; PubMed ID: 34956401; CODEN: JRAAA
https://doi.org/10.1155/2021/7010706 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122908369&doi=10.1155%2f2021%2f7010706&partnerID=40&md5=696a3d2f03c2ebb41f6dccb206d01780
Mohd Y., Medical Genetics and Epigenetics Laboratory, Department of Human Genetics and Molecular Biology, School of Life Sciences, Bharathiar University, Tamil Nadu, 641046, India; Kumar P., Department of Zoology, Jammu University, Jammu and Kashmir, Jammu, 180006, India, Institution of Human Genetics, Jammu University, Jammu and Kashmir, Jammu, 180006, India; Kuchi Bhotla H., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Tamil Nadu, Coimbatore, 461046, India; Meyyazhagan A., Department of Life Sciences CHRIST (Deemed to be University), Bangalore, 560029, India; Balasubramanian B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Ramesh Kumar M.K., Department of General Surgery, Mahatma Gandhi Medical College and Research Institute, Pillaiyarkuppam, Pondicherry, 607403, India; Pappusamy M., Department of Life Sciences CHRIST (Deemed to be University), Bangalore, 560029, India; Alagamuthu K.K., Department of Biotechnology, Selvamm Arts and Science College (Autonomous), Tamil Nadu, Namakkal, 637003, India; Orlacchio A., Laboratorio di Neurogenetica, Centro Europeo di Ricerca sul Cervello (CERC), Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Fondazione Santa Lucia, Rome, Italy, Dipartimento di Medicina e Chirurgia, Universitdi Perugia, Perugia, Italy; Keshavarao S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, Tamil Nadu, Coimbatore, 461046, India; Sampathkumar P., Department of Chemistry and Biosciences, SASTRA Deemed to be University, Tamil Nadu, Kumbakonam, 612001, India; Arumugam V.A., Medical Genetics and Epigenetics Laboratory, Department of Human Genetics and Molecular Biology, School of Life Sciences, Bharathiar University, Tamil Nadu, 641046, India
Corpus based sentimenal movie review analysis using auto encoder convolutional neural network
1500; 1501; 1511; 4500; 4501; Corpus; Dimensionality reduction; Feature extraction; Feature selection; Sentiment analysis; Word disambiguation
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.
Journal of Discrete Mathematical Sciences and Cryptography, Vol-24, No. 8, pp. 2323-2339.
Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Sivakumar R., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Ramamurthy B., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India
Indian government bonds sensitivity to macroeconomic and non-macroeconomic factors: A quantile regression approach
Broad total return index; Government bonds; India; Liquid total return index; Macroeconomic factors; Non-macroeconomic factors; Quantile regression
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.
Afro-Asian Journal of Finance and Accounting, Vol-11, No. 5, pp. 772-786.
https://doi.org/10.1504/AAJFA.2021.119480 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121151483&doi=10.1504%2fAAJFA.2021.119480&partnerID=40&md5=b9c214c6dd2d18ee6d087cea171550a9
Faniband M., Department of Commerce, CHRIST (Deemed to be University), Bengaluru, 560029, India
Market Reaction to Dividend Announcements During Pandemic: An Event Study
Abnormal Return (AR); Cumulative Abnormal Return (CAR); Dividend; Event Study; Insider Trading; Pandemic; Stock Market
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.
Prakash N., School of Business and Management, Christ University, Karnataka, Bangalore, India; Yogesh L., School of Business and Management, Christ University, Karnataka, Bangalore, India
Selfie Segmentation in Video Using N-Frames Ensemble
Deep learning; ensemble; image segmentation; multi-frames; neural network; selfie; soft voting; video
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.
Kim Y.-W.; Byun Y.-C.; Krishna A.V.N.; Krishnan B.
https://doi.org/10.1109/ACCESS.2021.3133276 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121400954&doi=10.1109%2fACCESS.2021.3133276&partnerID=40&md5=3ef452a8f79bf4315b38f18ef3dcf3ab
Kim Y.-W., Centre for Digital Innovation, CHRIST University (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Byun Y.-C., Department of Computer Engineering, Jeju National University, Jeju-si, 63243, South Korea; Krishna A.V.N., Department of Computer Science and Engineering, CHRIST University (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Krishnan B., Department of Computer Science and Engineering, CHRIST University (Deemed to Be University), Karnataka, Bengaluru, 560029, India
Multi-class SVM based network intrusion detection with attribute selection using infinite feature selection technique
15A06; 15A09; 17B10; 17B15; 18A10; 18C05; 18C10; 18D35; Anomaly detection; Infinity feature selection; Intrusion detection system; Machine learning; Multiclass support vector machine; Support vector machine
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.
Journal of Discrete Mathematical Sciences and Cryptography, Vol-24, No. 8, pp. 2137-2153.
Kaushik R., Amity Institute of Information Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Singh V., Department of Computer Science Engineering, Manipal University Jaipur, Rajasthan, Jaipur, 302002, India; Kumari R., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India