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Animal-Assisted Therapy for the Promotion of Social Competence: a Conceptual Framework
Developmental disorders have a substantial effect on the social competence of children affecting their overall psychosocial functioning. Social competence entails the process of being socially mature by establishing stable and adaptive patterns of social behavior. Animal-assisted therapy, as an alternative treatment modality, has offered some new prospects for improving social cognition. This conceptual paper, thus, attempts to throw light on how animal-assisted therapy can help improve social competence. The paper draws its knowledge from the existing theories and empirical work done to propose a conceptual framework that can enhance social competence by incorporating therapy animals. It can be concluded that animal-assisted therapy has found to improve different dimensions crucial for development of social competence. This further suggests the dire need to explore the effectiveness of human-animal interactions by utilizing it for improving social competence. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
ANN Based MPPT Using Boost Converter for Solar Water Pumping Using DC Motor
The solar DC pump system is simple to set up and run completely on its own without the need for human intervention. Solar DC pumps require fewer solar panels to operate than AC pumps. Solar PV Arrays, a solar DC regulator, and a DC pump make up the Solar DC Pump system. The nonlinear I-V characteristics of solar cells, PV modules have average efficiency compare to other forms of energy, and output power is affected by solar isolation and ambient temperature. The prominent factor to remember is that there will be a significant power loss owing to a failure to correspond between the source and the load. In order to get the most power to load from the PV panel, MPPT is implemented in the converter circuit using PWM and a microcontroller. In order to give the most power to load from the source, the solar power system should be designed to its full potential. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
ANN based pattern generation, design and simulation of broadband fractal antenna for wireless applications
The synthesis of microstrip antenna(MSA) remains complex and time consuming from convenient design point of view. The Artificial Neural Network (ANN) on the other hand provides quicker and accurate solutions while multiple parameters controlling MSA designs. This paper proposes a new type of square fractal antenna (SFA) structure iterated and optimized by ANN developed using Advanced C and simulated using HFSS for optimum resonance characteristics covering 1.6-6.6 GHz frequency range. The motivation behind this work is size reduction of MSAs through FA concept with broadband resonance. It is suggested that the proposed antenna can be a right choice for various wireless applications because of its broadband functionality. 2016 IEEE. -
Announcement effect of tender offer share buyback around turmoil period evidence from India
The announcement of a buyback informs the market about the companys decision to repurchase its own shares. This announcement highlights the companys price valuation and the inefficiencies that exist in the market. This study examines the share buyback announcement effect during the COVID-19 period. The study considered the stocks listed in the National Stock Exchange (NSE) that offered share buyback under tender offer mode during the pre-pandemic period between April 2016 and February 2020 and the post-pandemic period between March 2020 and March 2022. 75 firms in the pre-pandemic period and 43 in the post-pandemic period that announced share buyback under the tender offer method were analyzed. The event study methodology using a market model was employed to determine the presence of abnormal returns during the event period, which consisted of 21 days and +21 days. The findings of the study revealed the existence of abnormal returns in and around the announcement date. Besides, statistically significant cumulative abnormal average returns (CAAR) were also found on the event day, i.e., on Day 0. The study found that the impact of buyback announcements on stock returns significantly differed before and after COVID-19 for 10 and 21-day periods, with no significant differences for shorter periods. These insights can help traders and fund managers make informed portfolio adjustments during turbulent market periods surrounding buyback announcements. The author(s) 2024. -
Anomalous indirect carrier relaxation in direct band gap atomically thin gallium telluride
We report ultrafast studies on atomically thin Gallium telluride, a 2D metal monochalcogenide that has appeared to display superior photodetection properties in visible frequencies. Pump photon energy-dependent spectroscopic studies reveal that photoinduced carriers in this direct band-gap material undergo indirect relaxation within ?30 ps of photoexcitation, which is at least an order slower than that of most 2D materials. Despite the direct band-gap nature, slow and indirect carrier relaxation places this layered material as a prime candidate in the multitude of atomically thin semiconductor-based photodetectors and highlights the potential for prospective optoelectronic applications. 2023 American Physical Society. -
Anomaly detection in online social media
Online Social Media (OSM) is a platform where users post opinions, discussions, product reviews, random thoughts, advertisements, comment exchanges and status updates.These platforms help in text mining applications such as prediction of election results, newlinestudying global mood trends, public perception of a national concern or an issue, mining of public health knowledge, detecting epidemics and business analytics. These newlineapplications also present some research challenges like personal data stealing, community phishing, hate speeches, spreading misconceptions, cyber bullying and terror attack planning. Some of these challenges are anomalies or outliers which don t conform with the majority ones. The anomalies focused in this research work are behavioral and content anomalies. Data preprocessing for textual data from OSM plays an important role for creation of the Vector Space Model (VSM) which is used as an input for behavioral and content anomaly models. The contents posted by the public in OSM is written using natural language and sometimes may not follow the formal communication mode. It has lexical, newlinesemantic and syntactic ambiguities and becomes a challenging task to extract accurate information and discover logical patterns during the text mining process. Some of the commonly used methods for text mining are, Bag of Words (BoW), N-grams and Term newlineFrequency-Inverse Document Frequency (TF-IDF). Few limitations of these techniques newlineare, high dimensional sparse feature vectors, missing contextual meaning, presence of newlineweak features and Part of Speech ambiguity. In this research study, an improvised Feature Engineering model is proposed which is a combination of Forward Scan Trigrams and weighted TF-IDF to address the creation of an efficient Vector Space Model (VSM). This proposed model is used with an improvised Feature Hashing technique to address the removal of weak features. -
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Anonymization Based Deep Privacy Preserving Convolutional Autoencoder Learning Technique for High Dimensional Data Clustering in Big Data Cloud
Data Clustering is a primary research focus in large data-driven application domains in the big data cloud as performance of the clustering dynamic data with high dimensionality is highly challenging due to major concern in the effectiveness and efficiency on data representation. Machine learning is a conventional approach to distribute the data into soft partition still it leads to increasing sparsity of data and increasing difficulties in distinguishing distance between data points. In addition, securing the personnel and confidential information of the user is also becoming vital. In order to tackle those issues, a new anonymization based deep privacy preserving learning paradigm has been presented in this paper. The proposed model is represented as deep privacy preserving convolutional auto encoder learning architecture for secure high dimensional data clustering on inferring the distribution of the data over time. Initially dimensionality reduction and feature extraction is carried out and those extracted feature has been taken for clustering on generation of objective function to produce maximum margin cluster. Those clusters are further fine tuned to feature refinement on the hyper parameter of various layers of deep learning model network to establish the minimum reconstruction error by feature refinement. Softmax layer minimizes the intra cluster similarity and inter cluster variation in the feature space for cluster assignment. Hyper parameter tuning using stochastic gradient descent has been enabled in the output layer to make the data instance in the cluster to be close to each other by determining the affinity of the data on new representation. It results significant increase in the clustering performance on the discriminative informations. Detailed experimental analysis has been performed on benchmarks datasets to compute the proposed model performance with conventional approaches. The performance outcome represents that anonymization based deep privacy preserving clustering learning architecture can produce good scalability and effectiveness on high dimensional data. 2023 American Institute of Physics Inc.. All rights reserved. -
Ant colony based mechanism for increasing life time of critical nodes
MANET nodes act as a host as well as a router which increases the significance of every node for their participation in communication. Loss of any node in the network results in failure of links connected to the node which brings the importance of increased lifespan of a node. Some nodes during frequent transaction at critical network scenario consume more energy and become ill with critical energy level. Special attention towards these nodes can improve the lifespan of the node. In this paper an ant colony-based pheromone deposition mechanism was proposed to extend the lifetime of ill nodes. Pheromone deposited for the neighbor in the pheromone table helps in identifying frequently communicated neighbor. The proposed algorithm identifies the ill node and requests its frequently communicated neighbor for a tie up. The neighbor shares the workload of the ill node with mutual agreement. This method also improves the performance of a network by limiting pheromone deposition practice for low weighted nodes with low energy and high density (packet in queue). The proposed method increases lifespan of ill nodes and thereby increases the lifetime of entire network. The proposed work was also compared with existing protocol and the results have proved that the proposed mechanism has increased lifetime and reduced energy consumption of the entire network. 2019 School of Science, IHU. All rights reserved. -
Ant colony optimization based algorithm for detection of down syndrome /
Patent Number: 202141013924, Applicant: Vincydevi V K.
Nowadays, the systems related to healthcare are restructured with innovative skills like machine learning and artificial intelligence to offer humans more intellectual and proficient healthcare facilities. Various intelligent healthcare systems are exhibited with the help of big data and mobile computing devices to offer intellectual and expert services. Also, the increase in medical data leads to different issues for managing, storing, and processing data. -
Ant Colony Systems- Enabled Wireless Network Communication
[No abstract available] -
Antecedent Factors in Adolescents Consumer Socialization Process Through Social Media
The research paper attempts to find the antecedent factors that influence in adolescents consumer socialization process through social media and its impact on family purchase. Consumer socialization of adolescents through social media has become a key indicator in the area of marketing because of predominant online interaction of consumer. Socialization process framework is adopted to investigate among 254 respondents. The results show there is positive influence of antecedent variables like age, social media and peer identification on Purchase Intention and the variable social media also influences Product Involvement in family decision making. The outcome of this research benefits the academicians and marketers to explore the impact of social media on adolescent in their family decision making. Springer Nature Switzerland AG 2020. -
Antecedents and Consequences of Green Marketing Orientation in Automobile Industry : A Customer-Based Corporate Reputation Mediation Model
This dissertation presents a study that explores the influence of social cost and green innovation on environmental justice and their impact on green marketing. It also examines the role of customer-based corporate reputation as a mediator between customer cost-benefit (CCB) and customer loyalty. The research was conducted using a sample of 382 hybrid and electric vehicle owners in three major cities in India. The findings indicate that green innovation, social cost, and environmental justice significantly contribute to green marketing orientation. Moreover, green marketing orientation positively affects corporate reputation, which subsequently enhances customer loyalty and purchase intention. The study underscores the significance of implementing newlinesustainable and responsible business practices and developing effective green marketing strategies to gain a competitive edge in environmentally conscious markets. newlineThe outcomes of this study have practical implications for automobile companies, newlineoffering insights on how to enhance corporate reputation and customer loyalty through green newlinemarketing strategies. Additionally, future research may explore the moderating effects of cultural and contextual factors on the relationship between antecedents, green marketing orientation, and desired outcomes. newlineOverall, this research contributes to the existing body of knowledge on green newlinemarketing and corporate reputation. It emphasizes the need for automobile companies to adopt a more sustainable and responsible approach in their business practices, aligning with the growing environmental concerns and expectations of consumers. -
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Antecedents and consequences of overconfidence bias of stock market investors in Kerala
Keeping in mind the dynamic changes that have been taking place in the Indian stock market, since the emergence of technology, the advancement of the internet even into the remote regions of the country and active involvement of regulators like SEBI, the proposed study is designed to determine the antecedents of overconfidence bias of stock market investors and its consequences on their investment activities. -
Antecedents and Outcomes of Employee Engagement : A Study on Employees in Travel Organizations
Employee engagement is becoming very vital in the recent years because organizations with engaged employees tend to out-perform than employees who are disengaged. The outcomes of engaged employees are higher performance, lower turnover, increased profitability and many more. However there are some industries ignorant and neglect the importance of having engaged employees. Hence it is necessary to conduct more research on employee engagement which create more awareness to the organizations about the prominence of focusing on employee engagement and also augment to the existing literature. The study was conducted on a sample size of 433 employees working in travel organizations set up in Bengaluru and tested the relationship of psychological climate and psychological capital (antecedent variables) has on employee engagement and in turn its newlinerelationship with organizational citizenship behavior and intent to stay (outcome newlinevariables). The study also tested the mediating relationship of employee engagement newlinebetween the antecedent and outcome variables. Results indicated that psychological newlineclimate and psychological capital has a significant and positive relationship on employee engagement and with respect to outcome variables it was determined that higher the engagement level it leads to higher level of organizational citizenship behavior and intent to stay. Results of the study also indicated that employee engagement mediates the relationship between the antecedent and outcome variables. -
Antecedents and Trajectories of the Child and Adolescent Mental Health Crisis: Assimilating Empirically Guided Pathways for Stakeholders
Importance: Amid and following the COVID-19 pandemic, there has been a growing focus on understanding the underlying etiology of the mental health crisis in children and youth. However, there remains a dearth of empirically driven literature to comprehensively explore these issues. This narrative review delves into current mental health challenges among children and youth, examining perspectives from both pre-pandemic and pandemic periods. Observations: Research highlights reveal concerning statistics, such as 1 in 5 children experience mental health disorders. The pandemic exacerbated these issues, introducing stressors such as job losses and heightened anticipatory anxiety. Race relations have emerged as a significant public health concern, with biases impacting students, particularly affecting Asian, black, and multiracial individuals. Substance use trends indicate a rise in overdose deaths, particularly among adolescents, with cannabis use linked to adverse outcomes. Increased screen time and income disparities further compound mental health challenges. Conclusions and Relevance: Proposed public health mitigation strategies include improving access to evidence-based treatments, implementing legislative measures for early identification and treatment of developmental disorders, and enhancing suicide prevention efforts. School-based interventions and vocational-technical education are crucial, alongside initiatives targeting sleep hygiene, social media usage, nutrition, and physical activity. Educating health care professionals about both physical and mental health is essential to address workforce burnout and effectively manage clinical complexities. 2024 Physicians Postgraduate Press, Inc. -
Antecedents of Adoption of Peer to Peer (P2P) Lending-A Fintech Innovation in India
This study examines the association between adoption variables and behavioural intention (BI) to adopt Peer to Peer (P2P) lending technology platform in India. A critical review of literature on technological and personal adoption factors led to development of the theoretical framework using multiple technology adoption models. Results support the generalizability of technology adoption readiness (AR), a parsimonious higher-order construct for the use and acceptance of technology context In addition, a personal antecedent, personal innovativeness (PIIT) was shown to positively affect behavioural intentions and technology adoption readiness. 2022 IEEE. -
Antecedents of Behavioural Intention : Study of Indian Consumer Perceptions Towards P2P Lending Using Technology Adoption Model
Fintech is a rapidly developing area of the financial services business where tech-focused startups and other new players are upending how the sector has historically operated. One of the emerging fintech areas under digital lending is Peer to Peer lending or (P2P) lending; Consumers and authorities are both showing interest in this alternative lending innovation. Results of a literature review show that India is still in the early stages of P2P lending research. The study examines the association between behavioural intention to use P2P lending in India and technological and personal adoption factors. The study model was developed with the help of a literature review and tested using data from 536 respondents who completed an online survey and was tested using covariance-based structural equation modelling (SEM). The results confirm that personal innovativeness, performance expectancy, hedonic motivation, effort expectancy, social influence, and perceived risk are the antecedents of the adoption of P2P lending, except for facilitating conditions and price value. In addition, gender moderates the relationship between performance expectancy, hedonic motivation, personal innovativeness, and intention to adopt P2P lending. The study also throws light on the perceptions of both users and non users in terms of the antecedents. The study's conclusions significantly impact the P2P lending industry and provide practical insights for developers, platforms and regulators to improve and enhance the service. The study suggests looking at other moderating factors like age, voluntariness, experience, and actual usage behaviour for further research. Overall, the research contributes to the academic literature by confirming the predictive power of the extended unified theory of acceptance and use of technology (UTAUT). It highlights personal innovativeness after performance expectancy and motivation as an important factor in predicting the usage of P2P lending. Finally, the study lists managerial implications in the domains of technological adoption, which will assist in the P2P lending long-term success in India.