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On the Maximization of Some Graph Coloring Problems
A graph coloring problem involves labeling the vertices or edges in a graph with newlinecolors or numbers subject to some constraints. The most frequently known graph newlinecoloring problems are the ones that usually minimize the number of colors used in newlinecoloring the vertices or edges. The chromatic number of a graph G, denoted by and#967;(G), is the least number of colors used in a proper coloring of G. The chromatic sum of a graph G, denoted as P(G), was introduced in [1], which is to and the smallest possible coloring sum in a proper coloring of the graph G using natural numbers. Lately, a few studies have endured in a distinct area of the literature where the number of colors used in a graph coloring problem is maximized under certain conditions. Some of these works have applications in network sciences. newlineThe concerned study focuses on the maximization of three dierent edge coloring newlineconcepts, viz., the vertex induced kand#8722;edge coloring, vertex incident kand#8722;edge coloring, newlineand edge incident 2and#8722;edge coloring of a simple connected graph G, where k and#8805; 2. The newlinenumber of colors assigned to the edges of the graph G has been maximized under certain conditions. The vertex induced kand#8722;edge coloring and the vertex incident newlinekand#8722;edge coloring concepts are the generalized version of the edge coloring approach newlineintroduced and studied in [2]. Furthermore, the concept of the achromatic sum of a graph G has also been introduced here. This concept is to and the greatest possible coloring sum of the graph G in an improper edge coloring using natural numbers. An extensive study newlineon three achromatic sums, namely the vertex induced 2and#8722;edge coloring sum, the vertex incident 2and#8722;edge coloring sum, and the edge incident 2and#8722;edge coloring sum are carried out. A few bounds for these parameters on a simple connected graph G and the exact values for some elementary graph classes have been investigated. A few comparative results between some of these parameters have also been obtained. -
A STUDY ON THE INFLUENCE OF FAMILY ENVIRONMENT IN THE DEVELOPMENT OF AGGRESSIVE BEHAVIOR IN CHILDREN
This study designates the influence of family environment in the development of aggressive behavior in children. The purpose of the study was to find out how the family environment influences the aggressive behavior in children. The study was conducted in 5 government aided schools run by the diocese of Mananthavady in Wayanad district of Kerala State. The study included fifty, 10 to 12 year old school going children and their mothers. Family environment scale was used to find the family environment of the children and Aggressive Questionnaire was used to find the level of aggression in children. The raw data were subjected to various statistical analyses. The study brings in (1) the structure and systems in the families (2) the types and levels of aggression in children. The study found that 54 % of the children are with high aggression and 36 % of the children are with very high aggression. Over all the result found that the family environment has a significant role in the development of aggressive behavior in children. The more poor structure and systems in family environment creates the more aggressive children. Key words: family environment, physical aggression, verbal aggression, anger, hostility. -
Linear and non-linear analyses of electrothermo convection in a micropolar fluid
The linear and weakly non-linear stability analyses of electrothermo convention in a micropolar fluid layer heated from below are studied. The linear and non-linear analyses are, respectively, based on normal mode technique and truncated representation of Fourier series. The influence of various parameters on the onset of convection has been analyzed in the linear case. The resulting autonomous Lorenz model obtained in non-linear analysis is solved numerically to quantify the heat transfer through Nusselt number. It is observed that the increase in concentration of suspended particles stabilizes the system and decreases the heat transfer and increase in electric Rayleigh number destabilizes the system and increases the heat transfer. 2017 Pushpa Publishing House, Allahabad, India. -
Detection of Various Security Threats in IoT and Cloud Computing using Machine Learning
Due to the growth of internet technology, there is a sharp rise in the growth of IoT enabled devices. IoT (Internet of Things) refers to the connection of various embedded devices with limited processing and memory. With the heavy adoption of IoT applications, cloud computing is gaining traction with the ever-increasing demand to process and compute a massive amount of data coming from various devices. Hence, cloud computing and IoT are often related to each other. However, there are two challenges in deploying the IoT and cloud computing frameworks: security and Privacy. This article discusses various types of security threats affecting IoT and cloud computing, and threats are classified using machine learning (ML). ML has gained much momentum in recent years and is applied in various domains. One of the main subdomains of machine learning is used in IoT and cloud security. A machine learning model can be trained with data based on which the model can predict the impending security threats. Popular security techniques to protect IoT devices from hackers are IoT authentication, access control, malware detection, and secure overloading. Supervised learning algorithms can be used to detect malware in the runtime behavior of applications. The malware is detected from network traffic and is labeled based on its suspicious behavior. Post identification of malware, the application data is stored in a database trained via an ML classifier algorithm (KNN or Random Forest). With increased training, the model can identify malware applications with higher accuracy. 2022 IEEE. -
Analysis of Multinomial Classification for Legal Document Categorization
A major area of research today is the application of Machine Learning Techniques for Document or Text Classification. Document Classification is an important aspect of Electronic Discovery in the Legal domain. The need for the process to be automated has been realized over the past few years. Multinomial Classification is a well-known Supervised Machine Learning Technique that helps us classify if there are more than two classes used for the purpose of Classification. Evaluation metrics such as Precision, Recall, and F1 Score have been used to measure the efficiency of Classification. Logistic Regression and Gradient Boosting Algorithms have outperformed other Multiclass Classification techniques. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Supreme court dialogue classification using machine learning models
Legal classification models help lawyers identify the relevant documents required for a study. In this study, the focus is on sentence level classification. To be more precise, the work undertaken focuses on a conversation in the supreme court between the justice and other correspondents. In the study, both the nae Bayes classifier and logistic regression are used to classify conversations at the sentence level. The performance is measured with the help of the area under the curve score. The study found that the model that was trained on a specific case yielded better results than a model that was trained on a larger number of conversations. Case specificity is found to be more crucial in gaining better results from the classifier. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
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India as a climate leader in the indo-pacific: challenges and opportunities
The non-traditional security threats in the form of incessant floods, cyclones, and all-time rising sea levels in the Indo-Pacific region call for an integrated and constructive response led by a climate leader. Climate change is seen way beyond the lens of a mere environmental catastrophe having the potential to destabilize a nations economy and polity. The global state and non-state actors have acknowledged climate change to be an alarming global security threat. However, the failure of collective management of the climate crisis has mandated a responsible climate leader to monitor the mitigation efforts. In the context of initiatives like the National Solar Mission that envisages India to be a global leader in solar energy, the paper intends to weigh the possibilities for Indias role as a cogent climate leader in the Indo-Pacific region. It seeks to evaluate Indias climate leadership based on its green policies and assistance to Indo-Pacific countries. 2024 Indian Ocean Research Group. -
COOPERATIVE FEDERALISM IN A MULTINATIONAL COUNTRY: Examining the Case of Pakistan
Pakistan, as a multilingual and multiethnic country, has had to deal with issues of ethnic conflict and separatism. Cooperative federalism is used as a device by countries across the world to accommodate and manage the immense diversities they possess. This chapter examines the need for cooperative federalism in a multinational country like Pakistan to strengthen its federal model, ensuring that ethnic groups in the country do not feel insecure and alienated from the union, demanding secession. Beyond national security concerns, cooperative federalism in Pakistan will ensure economic security, human rights, social security, effective policymaking and much more, which form the basis of a welfare state. 2024 selection and editorial matter, M.J. Vinod, Stefy V Joseph, Joseph Chacko Chennatuserry and Dimitris N. Chryssochoou; individual chapters, the contributors. -
Knowledge society and the era of post-truth: Challenges to democracy
The future of any country in the contemporary era lies in its ability to harness the knowledge potential. The fruits of knowledge society have transformed the terrain of social and political scenario of countries around the world. Democracy as a form of government, to be successful, requires a critically-engaged and politically literate population. Democracy, therefore, requires not only political literacy but also media and digital literacies given the influence of media in our lives. If democracy is viewed as a relationship between knowledge and power, there needs to be a strong distinction between the ideas, the truth of power and the power of truth. The term, 'Post-truth', signifies that objective facts have become less influential in shaping public opinion than appeals to emotion and personal beliefs. The political processes in various democracies seem to have become more managerial and technologically fixated. There has been significant erosion in the ideas of transparency of information and political leadership has become nothing but a propaganda exercise. The paper analyses how the information technology revolution and the surge of new media has impacted the political processes in democracies, and presents the phenomenon of post-truth as a threat to the modern democratic systems. 2019 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Social Work Intervention Research in Child Sponsorship Programs: Enhancing Psychological Well-being of Marginalized Adolescents
The Child Sponsorship Program (CSP) is critical to enhancing the objective and subjective well-being of enrollees. Meanwhile, social work interventions emphasize scientific approaches aimed at empowering marginalized populations. This intervention research (IR) was focused on raising the psychological well-being (PWB) of adolescents in a prominent CSP located in Kochi, Kerala. Preliminary findings from a pilot study underscored the need for intervention, and subsequent Delphi survey results guided the formulation of an intervention strategy. Capitalizing on the transformative power of peer groups, IR implemented a social group work intervention to enhance adolescent PWB in CSP. Using a nonequivalent comparison group interrupted time-series design, the PWB of participants in the intervention group (IG, N = 20) and comparison group (CG, N = 20) was measured and compared. Ryffs PWB scale with 42 items served as the assessment instrument. Descriptive statistics confirmed the normal distribution of baseline data for all participants (N = 40), while repeated measures ANOVA in SPSS 25 validated the alternative hypothesis, indicating significant differences in PWB measures over time within IG and between IG and CG. Additionally, along with statistical evidence of intervention effectiveness, this study used a qualitative design for ongoing evaluation of the intervention process, providing insights for program refinement and demonstrating intervention outcomes. By defining a model for group work intervention among CSP adolescents to improve PWB, this study underscores the important role of social work interventions in empowering marginalized populations. The Author(s) 2024. -
Social groupwork for promoting psychological well-being of adolescents enrolled in sponsorship programs
Background: The dearth of data on adolescents highlighted in the UN's data disaggregation against the agenda 'no one left behind' calls for research on 'the second decade'. Moreover, India is a country with the world's largest adolescent population, and as such, studies and policies for developing competencies of adolescents are crucial to the country's development; interventions instilling confidence to aspire to a better future in underprivileged adolescents are vital to mitigate inequity. Methods: This intervention study adopted a quasi-experimental design to measure the effectiveness of social groupwork in raising the psychological well-being of adolescents in child sponsorship programs in Kerala. Forty adolescents from a Child Sponsorship Program (CSP) center in Kochi were recruited for the study. Those suggested by the CSP center considering their poor academic performance and behavior problems were allocated to the intervention group and the rest to the comparison group. The intervention was designed in response to the information garnered through a preliminary study and administered to the intervention group (n=20). We conducted pre-test and post-test for both the intervention group and comparison group (n=20). Results: Comparison between pre- and post-measurements carried out using paired sample t-test for the intervention group and comparison group separately gave a p-value of <0.05 for the intervention group and >0.05 for the comparison group. Thus, it was proved that psychological well-being of participants in the intervention group was raised significantly due to the social group work intervention. Conclusions: Applying refined granularity, this research adds data specifically on adolescents enrolled in child sponsorship programs and sets a blueprint for social groupwork to improve their psychological well-being. Proposing a conceptual framework for child sponsorship programs, this study recommends further research in all aspects of its functioning, and interventions at group, family, and community levels, for the well-being and empowerment of marginalized adolescents. 2021 Joseph S and Karalam DSRB. -
Addiction treatment in India: Legal, ethical and professional concerns reported in the media
As per the Magnitude of Substance Use in India 2019 survey report, over 57 million of the Indian population is in need of professional help for alcohol use disorders and around 7.7 million for opioid use disorders. The increasing demand for addiction treatment services in India calls for professionalising every aspect of the field. Frequent human rights violations and various unethical practices in Indian addiction treatment facilities have been reported in the mass media. This study is a content analysis of newspaper reports from January 1, 2016 to December 31, 2019 looking into legal, ethical and professional concerns regarding the treatment of substance use disorders in India. The content analysis revealed various human rights violations, the use of improper treatment modalities, the lack of basic facilities at treatment settings, and the presence of unqualified professionals in practice. Indian Journal of Medical Ethics 2021. -
Problematic Gaming Among Adolescents within a Non-Clinical Population: A Scoping Review
Gaming is a pastime activity that has been enjoyed by millions of individuals worldwide for the past few years. The adolescent is in a developmental period that involves significant bio- psychosocial changes, including rapid changes in physical and mental states that make them more vulnerable to addiction. Online Gaming could have a higher risk of developing problematic gaming. Many studies have documented video gaming addiction and not problematic video gaming. Problematic gaming is a condition different from video game addiction. Further research remains needed to synthesise the factors behind problematic video game usage. The purpose of the scoping review is to synthesise the findings related to problematic video by identifying using a search through the following database: JSTOR, ProQuest, APA Psycnet, Ebsco. The research will help detect the early symptoms of addiction and understand the mechanism behind the addictive nature. Through the study, we can provide psychological care for adolescents by educating them and preventing and being aware of problematic gaming usage and experiences. The Electrochemical Society -
The Efficacy of Multi-Component Intervention for Adolescents with Problematic Video Gaming in a Community-Based Setting
Video gaming is a popular leisure activity enjoyed by millions globally, helping with socialisation, interaction, and relieving stress. It may also become a maladaptive coping mechanism to evade distress and negative emotions, leading to problematic usage. Research evidence shows that problematic gaming is associated with different psychosocial issues. Video games can be a way of negative coping and escaping reality, and problematic usage can hide other problems of players in real life. Adolescents are vulnerable to problematic use due to their developmental stages, and those with specific vulnerabilities and disabilities are at greater risk. No one psychotherapy has all the answers, and the multi-component intervention technique might have better treatment utility than a solitary behaviour intervention. The research aims to show the effectiveness of the intervention for problematic video game usage in a community-based setting. The study focuses on adolescents in seventh through ninth grade who were identified as problematic video gamers (not addictive users) from a selected group of schools in Kerala. The study employed an experimental design, encompassing both intervention and control groups, to systematically assess the effects of the experimental manipulation and establish a baseline measurement. The paired t-test results showed no significant decrease in the intervention groups Gaming Addiction Scale at the post-test, but it did lower the addiction scores. By conducting the research, we provide psychological care for adolescents and help them identify and prevent problematic gaming experiences. The research underscores the significance of early identification and prevention of problematic video game usage among adolescents, advocating for a holistic approach incorporating diverse components. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Character Recognition of MODI Script Using Distance Classifier Algorithms
Machine simulation of human reading is an active research area since the introduction of digital computers. Optical character recognition aims at the recognition of printed or handwritten text from document images and converting the same into a machine-readable form. The focus of this work is handwritten character recognition of MODI Script. A proper recognition system for handwritten documents enables it to be conveniently viewed, edited, and shared via electronic means. The development of a character recognition system for some of the ancient script is still a challenging task due to the complex nature of the script. MODI script is one such script which is the shorthand form of the Devanagari script in which Marathi was written. Though at present MODI script is not an official script, there exists a huge collection of MODI documents in various libraries. In addition, it is observed that scholars and historians are taking serious effort to revive the script. The purposed study based on the implementation of two algorithms for the classification of handwritten MODI script. The algorithms use distance classifier method. The first experiment is done using Euclidean distance classifiers and the second one is with Manhattan distance classifier and the accuracy achieved is 99.28% & 94% respectively. Springer Nature Singapore Pte Ltd 2020. -
Offline Character Recognition of Handwritten MODI Script Using Wavelet Transform and Decision Tree Classifier
MODI script is derived from the N?gari family of scripts, and it was used for writing Marathi until twentieth century. Though currently not used as an official script, it has historical importance, as a large volume of manuscripts are preserved at various libraries across India. With the use of an appropriate recognition system, the handwritten documents can be transferred into digital media, so that it can be conveniently viewed, edited, or transliterated to other scripts. The research on MODI script is still in the initial stages, and there is a considerable demand for more research in this field. An implementation of wavelet transform-based feature extraction for MODI scripts character recognition is discussed in this paper. The experiment is performed using Daubechies, Haar, and Symlet wavelets, and performance comparison between these different mother wavelets is carried out. Decision tree classifier is used for the classification process, and the results indicate that the feature extraction using Daubechies wavelet yielded better character recognition result. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Feature extraction and classification techniques of modi script character recognition
Machine simulation of human reading has caught the attention of computer science researchers since the introduction of digital computers. Character recognition is the process of recognizing either printed or handwritten text from document images and converting it into machine-readable form. Character recognition is successfully implemented for various foreign language scripts like English, Chinese and Latin. In the case of Indian language scripts, the character recognition process is comparatively difficult due to the complex nature of scripts. MODI script-an ancient Indian script, is the shorthand form for the Devanagari script in which Marathi was written. Though at present, the script is not used officially, it has historical importance. MODI character recognition is a very complex task due to its variations in the writing style of individuals, shape similarity of characters and the absence of word stopping symbol in documents. The advances in various machine learning techniques have greatly contributed to the success of various character recognition processes. The proposed work provides an overview of various feature extraction and classification techniques used in the recognition of MODI script till date and also provides evaluation and comparison of these techniques. 2019, Universiti Putra Malaysia Press. All rights reserved. -
Handwritten Character Recognition of MODI Script using Convolutional Neural Network Based Feature Extraction Method and Support Vector Machine Classifier
Deep learning based algorithms are used in various pattern recognition tasks, including character recognition. Convolutional Neural Network (CNN) is effectively implemented for character recognition and is one of the best performing deep learning models. CNN can be used for character recognition directly or it can be used for extracting features in the character recognition process. Implementation of a feature extraction method using CNN autoencoder for MODI script character recognition is discussed in the paper. The extracted features are then subjected to Support Vector Machine (SVM) for the purpose of classification. The On-the-fly data augmentation method is used to add variability and generalization of the data set. MODI Script is an ancient Indian script and was used for writing Marathi until 1950. Various libraries and temples in India and abroad have a large collection of MODI documents. Character recognition related research of MODI script is still in infancy and research and development is necessary to extract the information from MODI manuscripts stored in various libraries. The performance of the proposed method, which uses CNN autoencoder as a feature extractor and an SVM based classifier gives very high accuracy and is better compared to the most accurate MODI character recognition method reported so far. 2020 IEEE.