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Cognitive marketing and purchase decision with reference to pop up and banner advertisements
The aim of this research paper is to employ a mixed research approach and to check how the past data differs from the present and hence it uses an argument mapping to find the reality using focus group. Since genders have different opinion on pop-up and banner advertisements, two focus groups, one group consisting the female gender and the other focus group consisting the male respondents have been taken for the data collection. Small sample has been used for the argument mapping (N=45/Male) and (N=47/Female). A series of steps has been conducted in the argument mapping and relevant maps have been developed for drawing inference. It is found that, male have no patience to deal with the pop-up and banner advertisements but women are keener and patient enough to make the best use of these advertisements. On the other hand a questionnaire was framed from the variables found from the literature review and the same was distributed to both the genders and it was found collectively that though pop-up advertisements and banner advertisements are useful in some way, it is always considered to be a negative aspect. Misleading advertisements, data security scam are a few negative aspects of such advertisements and hence, there are a lot of ugly truth behind pop up and banner advertisements. The mixed research approach (triangulation) between the quantitative and qualitative is a new initiative taken by the researchers in this research and holds originality of the study. 2018 Academic Research Publishing Group. -
Cognitive outcomes prediction in children using machine learning and big data analytics
This study explores the potential of machine learning (ML) and big data analytics in predicting cognitive outcomes in children, aiming to enhance early identification and intervention strategies. Leveraging a diverse dataset comprising neurocognitive assessments, genetic markers, socio-economic factors, and environmental variables, our research employs advanced ML algorithms to develop predictive models. The interdisciplinary approach integrates neuroscience, psychology, and data science to discern patterns and correlations within the expansive dataset. The study emphasizes the importance of early cognitive assessment for optimal child development and academic success. By harnessing the power of big data, our models seek to uncover nuanced relationships that traditional methodologies may overlook. Preliminary results indicate promising accuracy in predicting cognitive outcomes, offering a valuable tool for educators, healthcare professionals, and policymakers. Additionally, the model's interpretability allows for a deeper understanding of the factors influencing cognitive development. Ethical considerations, privacy safeguards, and data governance are integral components of this research, ensuring responsible use of sensitive information. The implications of this study extend beyond academia, with the potential to inform educational policies, personalized learning strategies, and targeted interventions for at-risk populations. As technological advancements continue, the integration of ML and big data analytics in predicting cognitive outcomes heralds a new era in pediatric research, promoting proactive approaches to support children's cognitive well-being. 2024 IEEE. -
Cognitive Style and Academic Achievement among School Students
The aim of the present study was to explore cognitive style and academic achievement among school students using a quantitative approach. The study involved a total of 423 students from grade VIth and VIIth. Students from both private and government schools participated in the study. The study used group embedded figures test by Witkin et al. (1971) and classroom achievement test by Singh & Gupta (2007) to determine the participants field independent and dependent cognitive styles and academic achievement. T test was used to compare the academic achievement of field independent ?? field dependent cognitive style students. Whereas, two-way Anova test was done to analysis the interaction effect of grades, gender, and type of school along with cognitive style on academic achievement of students. The findings of the present research showed that there was a significant difference between field independent and dependent students' on academic achievement. It also revealed that students with field independent cognitive style performed significantly better than field dependent students. However grades had a significant main effect on academic achievement of students. There was no interaction effect found between grades and cognitive style on academic achievement of students. In addition, it was also found that there was no interaction effect of type of school and cognitive style on academic achievement of students. The findings of the study benefits teachers by indicating significant classroom implications which will help them to develop effective learning materials and strategies which are suitable for their student in order to utilize their cognitive style strength effectively. It helps students in making effective decisions regarding ones enrolment in higher education courses and career choices. Key Words: Field Independent-Dependent Cognitive Style, Academic Achievement, Grades, Gender and Type of School. -
Cognitive synergy: Enhancing late career engagement with ergonomic solutions
The chapter explores the intricate relationship between cognitive ergonomics and late career employees, emphasizing the challenges and opportunities of an aging workforce. It combines research findings and case studies to understand how cognitive aging affects job performance and satisfaction. A central theme is the importance of technology training and support for older workers. As technology advances, organizations must ensure their older employees have the skills to navigate these changes. This includes training in new software and tools, and ongoing support. Flexible work arrangements are also crucial, reducing stress and fatigue from long commutes and rigid schedules. Health screenings and age-friendly workplaces are key. Regular health screenings and access to healthcare can address physical and cognitive challenges. Designing workspaces and processes for older workers fosters inclusivity and diversity. In conclusion, the chapter offers recommendations for organizations to leverage the late career workforce. 2024 by IGI Global. All rights reserved. -
Cognitive technology for the Indian higher education: A Language teaching and Learning application
Past decade witnessed a technological boom in the world. Regardless of the age every person in the world owns a mobile device which can be connected to internet. The technologies and applications for these mobile devices are one of the inevitable part people's day to day lives. The past decade also evidenced the development of Artificial Intelligence, Machine Learning (ML), Natural Language Processing (NLP), Image Processing (IP), Speech Recognition (SR) and Big DataAnalytics (BDA), etc. which lead to the development of Intelligent applications for the fields like business, health care, weather, media, etc. The field which uses the technology in a slow pace is education system. This paper is majorly focused on the Indian higher education system and the technologies used in their teaching and learning. One of the major drawbacks of Indian higher education system is the traditional teacher centric teaching and learning process. The usage of technology in their education system limited to chock and board to power point presentation. Some of the elite Universities in India uses Massive Online Open Courses (MOOC) but majority of the education institution still follows the old method of teaching and learning. This paper profiles cognitive technology based applications which can be used for the betterment of current system. The proposed model in this paper is for the language course learning. The application is centered on ML and NLP. Copyright 2019 American Scientific Publishers All rights reserved. -
Cognitive technology in human capital management: a decision analysis model in the banking sector during COVID-19 scenario
Cognitive technologies are products of the artificial intelligence (AI) domain which execute tasks that only humans used to perform. The impact of cognitive technologies on the management of human capital (HC) has a massive effect in the banking sector. This paper studies the transformation of cognitive technology to human capital management (HCM) in the banking sector during the COVID-19 pandemic. The study draws data from 201 bank employees working in private, public, and foreign banks using a multi-stage sampling method in India. A number of hypotheses were framed and tested using multivariate and regression analyses. The results from the study indicate a significant change in the performances of bank employees statistically during the transformation of cognitive technologies. Cognitive technologies such as payment, product customisation, self-services, workload alleviation, automated back-office function, and a personalised experience significantly contribute to the HCM. 2024 Inderscience Enterprises Ltd. -
CoInMPro: Confidential Inference and Model Protection Using Secure Multi-Party Computation
In the twenty-first century, machine learning has revolutionized insight generation by using historical data across domains like health care, finance, and pharma. The effectiveness of machine learning solutions depends largely on the collaboration between data owners, model owners, and ML clients, without privacy concerns. The existing privacy-preserving solutions lack efficient and confidential ML inference. This paper addresses this inefficiency by presenting the Confidential Inference and Model Protection, also known as the CoInMPro, to solve the privacy issue faced by model owners and ML clients. The CoInMPro technique is suggested with an aim to boost the privacy of model parameters and client input during ML inference, without affecting the accuracy and by paying a marginal performance cost. Secure multi-party computation (SMPC) techniques were used to calculate inference results confidentially after sharing client input and model parameters privately from different model owners. The technique was implemented in Python language using the open-source SyMPC library to support the SMPC function. The Boston Housing Dataset was used, and the experiments were run on Azure data science VM using Ubuntu OS. The result suggests CoInMPros effectiveness in addressing privacy concerns of model owners and inference clients, with no sizable impact on accuracy and trade-off. A linear impact on performance was noted with an increase of secure nodes in the SMPC cluster. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Cold spray deposition of hydroxyapatite powder onto magnesium substrates for biomaterial applications
A simple, modified, cold spray process was developed in which hydroxyapatite powder was coated onto pure magnesium substrates preheated to 350 or 550C and ground to either 240 or 2000 grit surface roughness, with stand-off distances of 20 or 40 mm. The procedure was repeated five and 10 times. The hydroxyapatite coatings did not show any phase changes. Atomic force microscopy revealed a uniform coating topography, and scanning electron microscopy revealed good bonding between the coated layers and the substrates. As the p values were < 0.05, all factors except the number of sprays were considered to be significant. The response optimiser indicated that a 22.7 mm stand-off distance, a 649.2 grit surface roughness and a 496C substrate heating temperature produced good hydroxyapatite coatings of 46.3 ?m thickness, 436.5 MPa nanohardness and 43.9 GPa elastic modulus. The modified cold spray technique with substrate heating showed promising results in terms of product coating thickness and mechanical properties. 2015 Institute of Materials, Minerals and Mining. -
Collaboration between gram panchayat and women self-help groups on rural development in karnataka
Mahatma Gandhi said, Indiaand#8223;s development relays on development in rural India. To see a developed India, we must develop villages in India. India is trying to improve the living standard of rural people since Independence. Government, Non-Government Organizations, Voluntary Groups, and many individuals are making continuous efforts for decades to improve rural condition. There is a positive change and growth, but the achieved results are not satisfactory in relation to need, the available resources, opportunities, and the efforts made. What are the root causes of failures? Are there necessary coordination and collaboration among the development efforts to optimize the fruits and minimize the loss of human and material resources? Gram Panchayat Institutions and Self-Help Groups by women are two of major efforts which became very powerful means to empower and develop rural people. The Constitution (73rd Amendment) Act, 1992 became a land-mark by establishing Panchayat Raj Institutions (PRI) in Indiaand#8223;s effort for rural development and reaching out the democracy to grass-root level by newlineforming Panchayat Raj Institutions with three tier system. The Reservation policy of 72nd newlineAmendment Act was another turning point in empowering effort. NGOs initiated Self-Help newlineGroups in India in early 1990s and later Government also supported and promoted the newlineinitiative. Will the Collaboration between the Gram Panchayat Institutions and Women SelfHelp Groups enhance development of rural area through higher level of Community newlineParticipation is the research question here. newlineThere are many writings, studies and evaluations on Gram Panchayat Institutions and SelfHelp Groups by women to assess the existing condition, and to make the efforts more efficient and effective towards rural empowerment and development. Still, studies on impact of collaboration between Gram Panchayat and Women Self-Help Groups on rural newlinedevelopment are missing. -
Collaborative intrusion detection system in cognitive smart city network (CSC-Net)
Smart environment is about incorporating smart thinking in the environment and implementing the technical intervention that improvise the city's environment. Artificial intelligence (AI) provides solutions in huge technological issues in various aspects of day-to-day life such as autonomous transportation, governance, healthcare, agriculture, maintenance, logistics, and education that are automated, managed, controlled, and accessed remotely with the aid of smart devices. Cognitive computing is denoted as a next-generation AI-dependent method that gives human-computer interactions with personalized services that replicate manual behavior. Simultaneously, massive data is generated from the applications of the smart city like smart transportation, retail industry, healthcare, and governance. It is necessary to obtain a reliable, sustainable, continuous, and secure framework in the cloud centralized infrastructure. In this research article, the authors proposed the architecture of cognitive smart city network (CSC-Net) that defines how data are collected from applications of smart city and scrutinized by cognitive computing. This research article predicts the mobile edge computing solution (MEC) that permits node collaboration between internet of things (IoT) devices for providing secure and reliable communication among smart devices and fog layer, conversely fog layer and cloud layer. This proposed work helps to reduce the excessive traffic flow in smart environment with the support of node to node communication protocols. Collaborative-dependent intrusion detection system (C-IDS) is proposed to solve the data security issues in fog and cloud layers. Copyright 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
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Collision avoidance using gazebo simulator
Autonomous cars will make its complete presence on roads in the future. A major feature of autonomous cars currently under research is collision avoidance on roads. Better collision avoidance systems could result in a decrease in number of accidents. Smart collision avoidance systems could handle the increasing amount of vehicles on roads. Collision avoidance system provides alert to the autonomous vehicles if an unavoidable collision is detected. When the collision is definite to happen, collision avoidance system takes action by its own without any driver input (by braking or steering or both). Collision avoidance system does the obstacle avoidance by gathering information about the environment with the help of sensors embedded in the system. The effectiveness of collision avoidance system depends upon the speed at which the system reacts from the gathered inputs. This paper uses the Gazebo simulation to design and implement collision avoidance. This paper also present a simple and effective obstacle avoidance algorithm for a simulated robot. Turtlebots Obstacle Avoider algorithm is attached to the robot in the simulator with the support of ROS(Robotic operating system) to implement collision avoidance. BEIESP. -
Colonialism and Communalism: Religion and Changing Identities in Modern India
Christhu Doss examines how the colonial construct of communalism through the fault lines of the supposed religious neutrality, the hunger for the bread of life, the establishment of exclusive village settlements for the proselytes, the rhetoric of Victorian morality, the booby-traps of modernity, and the subversion of Indian cultural heritage resulted in a radical reorientation of religious allegiance that eventually created a perpetual detachment between proselytes and the others. Exploring the trajectories of communalism, Doss demonstrates how the multicultural Indian society, known widely for its composite culture, and secular convictions were categorized, compartmentalized, and communalized by the racialized religious pretensions. A vital read for historians, political scientists, sociologists, anthropologists, and all those who are interested in religions, cultures, identity politics, and decolonization in modern India. 2024 M. Christhu Doss. -
Colonoscopy contrast-enhanced by intuitionistic fuzzy soft sets for polyp cancer localization
Medical images often suffer from low contrast, irregular gray-level spacing and contain a lot of uncertainties due to constraints of imaging devices and environment (various lighting conditions) when capturing images. In order to achieve any clinical-diagnosis method for medical imaging with better comprehensibility, image contrast enhancement algorithms would be appropriate to improve the visual quality of medical images. In this paper, an automated image enhancement method is presented for colonoscopy images based on the intuitionistic fuzzy soft set. The fuzzy soft set is used to model the intuitionistic fuzzy soft image matrix based on a set of soft features of the colonoscopy images. The technique decomposes the fuzzy image into multiple blocks and estimates a soft-score based on an adaptive soft parametric hesitancy map by using the hesitant entropy for each block to quantify the uncertainties. In the processing stage, an adaptive intensity modification process is done for each block according to its soft-score. These scores are accurately addressed the gray-level ambiguities in colonoscopy images that lead to better results. Finally, the enhanced image achieved by performing a defuzzification together with all unprocessed blocks. Qualitative and quantitative assessments demonstrate that the proposed method improves image contrast and region-of-interest of polyps in colonogram. Experimental results on enhancing a large CVC-Clinic-DB and ASU-Mayo clinic colonoscopy benchmark datasets show that the proposed method outperforms the state-of-the-art medical image enhancement methods. 2020 Elsevier B.V. -
Color image segmentation based on improved sine cosine optimization algorithm
Segmentation refers to the process of dividing an image into multiple regions based on some criteria such as intensity and color. In recent years, color image segmentation has received considerable attention from the researchers. However, it is still a highly complicated task due to the presence of more attributes or components as compared to monochrome images. Numerous meta-heuristics algorithms are developed to determine the optimal threshold value for segmenting color images efficiently. This paper presents an enhanced sine cosine algorithm (ESCA) to seek threshold for segmenting color images. Sine cosine algorithm (SCA) is a population-based optimization algorithm which has the ability of preventing local minima problem. First an input image is transformed to CIE L*a*b* color reduced space. ESCA is applied to determine the optimal threshold values for segmentation. The performance of the proposed method is tested on color images from Berkeley database, and segmentation results are compared with two metaheuristic algorithms, namely particle swarm optimization (PSO) and standard SCA. Experimental results are validated by measuring peak signalnoise ratio (PSNR), structural similarity index and computation time for all the images investigated. Results revealed that the proposed method outperforms the other methods like PSO and SCA by achieving PSNR of 23dB and SSIM of 0.93 and also require less time for finding optimal threshold values than PSO and SCA. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Colorimetric and theoretical investigation of coumarin based chemosensor for selective detection of fluoride
Coumarin based Sensor 1 has been designed and synthesized to recognize fluoride ion visually with high selectivity and sensitivity over other anionic analytes through color change from very faint yellow to pink in acetonitrile. The probable binding phenomenon in solution phase has been explained by 1H NMR study of sensor 1 with different concentration of fluoride ions. The binding constant of the sensor 1 with fluoride has been determined as 3.9 104 M?1 and the lower detection limit 6.5 M of the sensor 1 towards fluoride, which has made the sensor 1 as a promising backbone for selective detection of fluoride. For the practical application, test strips based on sensor 1 were fabricated, which could act as a convenient and efficient naked eye F?test kits. The experimentally observed absorption maxima along with its binding nature with fluoride ions also have been supported through theoretical calculations using density functional theory (DFT) calculations. 2022 -
Coloring of n-inordinate invariant intersection graphs
In the literature of algebraic graph theory, an algebraic intersection graph called the invariant intersection graph of a graph has been constructed from the automorphism group of a graph. A specific class of these invariant intersection graphs was identified as the n-inordinate invariant intersection graphs, and its structural properties has been studied. In this article, we study the different types of proper vertex coloring schemes of these n-inordinate invariant intersection graphs and their complements, by obtaining the coloring pattern and the chromatic number associated. 2024 The Author(s) -
Coloring of Non-zero Component Graphs
The non-zero component graph of a finite dimensional vector space V over a finite field F is the graph G(V?) = (V, E), where vertices of G(V?) are the non-zero vectors in V, two of which are adjacent if they share at least one basis vector with non-zero coefficient in their basic representation. In this paper, we study the various types of colorings of non-zero component graph. (2024), (Universidad Catolica del Norte). All rights reserved. -
Colouring of (P3? P2) -free graphs
The class of 2 K2-free graphs and its various subclasses have been studied in a variety of contexts. In this paper, we are concerned with the colouring of (P3? P2) -free graphs, a super class of 2 K2-free graphs. We derive a O(?3) upper bound for the chromatic number of (P3? P2) -free graphs, and sharper bounds for (P3? P2, diamond)-free graphs and for (2 K2, diamond)-free graphs, where ? denotes the clique number. The last two classes are perfect if ?? 5 and ? 4 respectively. 2017, Springer Japan KK, part of Springer Nature. -
COLPOUSIT: A Hybrid Model for Tourist Place Recommendation based on Machine Learning Algorithms
Tourism is an important sector for a country's economic growth. The travel recommendations should be made focused on better growth and attract more travelers. There is a huge amount of travel information and ideas available on the web that allows the users to make poor travel decisions. This paper focuses on building a hybrid travel recommender system by implementing collaborative-based, popularity-based, and nearby place weighted recommender system. The proposed system recommends the travel spots to the users based upon their interests and other criteria specified. In order to implement these methods, we applied a comparative study on different machine learning algorithms for collaborative-based approach and have performed weighted hybridization. These methods provide a personalized and customized list of similar places with respect to places of interest to the users. Thus, a hybrid system built using these methods provides a better recommendation of places with the advantages of these methods. The obtained results confirm that the hybrid method better than other recommender approaches when used separately. 2021 IEEE.