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Access to Justice Through Law Schools Legal AID Activities in India : An Empirical Study with Special Reference to Kerala
The provision of legal services is a fundamental human right and is integral to the maintenance of the rule of law. Ensuring Justice and the rule of law are unique sustainable development goals in the 2030 Agenda. Law school clinics provide a novel way to reach SDG-16. The legal aid system has been influenced by both international and national legislation, which has contributed to the establishment of its framework. The judiciary plays a pivotal role in ensuring the provision of free legal assistance to indigent people. Access to formal and informal justice institutions must be improved so that people can seek and get justice. Law school clinics provide potential and challenges as informal justice nstitutions, yet they are mostly ignored. Under CLE, law schools LACs engage in a variety of legal aid initiatives. Through this, students acquire professional skills while clients get legal services. That is the beauty of law school LACs. In the end, this "laboratory of lawyering" helps individuals find justice. In the Indian context, this thesis answered three research questions. 1) How do the legal aid programmes undertaken by law schools clinics promote SDG-16 and improve access to justice? 2) What are the current practices being undertaken by law schools LACs to guarantee access to justice? 3) What are the shortcomings that law schools LACs face in delivering appropriate legal services in Kerala? Two methodologies were used in answering these three questions: the doctrinal method for the first two research questions and the empirical method for the third. The doctrinal study examines the operation of LACs in general. The purpose of this empirical research on law school clinics in Kerala is to investigate the numerous legal aid activities and barriers to law school clinic operations in Kerala. No meticulous study was conducted in Kerala to evaluate how law schools LACs worked. National and international law school clinics' best practises and case studies were incorporated. The study examined the relationship between BCI, NALSA, SLSAs as well as CLE requirements along with law school performance. The LACs' commitment will be assessed based on their legal aid operations pre- and post-Covid-19, including legal representation, legal awareness, legal advice, paralegal services, PIL and ADR services to beneficiaries, and the effective implementation of BCI and NALSA's CLE requirements. This study explores the relationship between dependent and independent variables, such as how the improper implementation of BCI and NALSA regulations on CLE hindered law school LACs' commitments. The prevailing policy has restricted law school LACs' activity and is not enough to achieve access to justice (ATJ). Due to multiple factors, law school LACs failed to ensure effective service learning and did not reach the needy. This gap in the current CLE and its insufficient attention to promoting access to justice have been addressed. The empirical investigation demonstrates that while the number of law schools increased, legal aid activities decreased during the past decade. Current legal aid practices of law school LACs in Kerala are unsatisfactory and inconsistent in providing access to justice. BCI and LSAs ineffective control over LACs in law schools has contributed to a decline in legal aid activities and services. BCI and NALSA must reform their CLE rules and establish mandatory legal services to foster inclusive and effective LACs that give meaningful justice to the disadvantaged. -
A catechism of pentecostal schisms and the efficacy of management in the stabilization of the church in zimbabwe
The Pentecostal church in Zimbabwe has of late experienced a rude awakening with the mushrooming of these incessant schisms which threaten the unity of purpose that should prevail in a religious set up. The current newlineincrease in schisms is of great concern to the Christian community. Are such schisms embedded in its original design, or are there other factors at play. The problem necessitated the commissioning of this study in order to explore the schism scourge with view to arresting it and bring stability to the splintering Pentecostal church. The conceptualization of the study began by identifying six hypothetical perspectives as the root hypothetical causes of church schisms, i.e., doctrinal, controversial relationship, secularization, institutionalism, leadership and management perspectives. Theoretical frameworks in the newlineexisting literature were reviewed to establish knowledge gaps that informed the newlinestudy approach. Using focus group discussion, document analysis, survey questionnaires, and interviews, the study sought causal and remedial validation on the problem at hand. To unveil the intricacies of the problem, an explorative mixed study framework was preferred. In order to generate a desired rich understanding and interpretation of schisms, a more qualitative catechism inquiry based on a combined ethno-methodology and hermeneutics paradigm was adopted. The study proposition was that church schisms are a result of management challenges in the Pentecostal church. The theoretical frame of the study was therefore modeled to explore newlinehow management protocols could be harnessed to induce real growth and stability. The Pentecostal church is renowned for shunning management, considering it secular and hence worldly. On one hand, the church is the most newlinecomplex institution, multifaceted and with multi-bottom lines, yet on the other hand, management is all about dealing with such complexities. -
A comparison of distressed and non distressed married couples on marital quality emotional intelligence and conflict resolution styles
Aim: To compare and study the marital quality, emotional intelligence newlineand conflict resolution styles of distressed and non-distressed married couples; and to examine the interrelationships between these variables. Method: The study utilized a cross sectional, between group, mixed method research design. The sample consisted of 43 heterosexual married couples (N=86) in non-clinical settings, in the age range of 20-60 years, living in Bangalore, who met the inclusion and exclusion criteria, were newlinerecruited through purposive/ snowball sampling. The participants were administered a demographic data sheet, the Marital Quality Scale (Shah, 1995), the Emotional Intelligence Scale (Schutte, Malouff, Hall, newlineHaggerty, Cooper, and Golden, 1998), the Conflict Resolution Scale (Kurdek, 1994) and a Semi-structured Interview Schedule for qualitative data (prepared by the researcher). Quantitative and Qualitative analysis was carried out. The MQS cutoff score of 80 was used to divide the sample into distressed and nondistressed couples. newlineResults: The two groups significantly differed on the conflict resolution styles. A significant relationship was found between marital quality and conflict resolution styles of distressed as well as non distressed group. There was a significant positive relationship between withdrawal as a newlineconflict resolution style and marital quality among distressed wives. Correlations between marital quality and conflict resolution styles among non-distressed couples showed that withdrawal had a significant positive newlinerelationship with the marital quality of the husband. From the correlation between the emotional intelligence and conflict resolution styles of distressed couples, compliance had a significant positive relationship with the wife s emotional intelligence. Among non-distressed wives conflict engagement was negatively correlated and positive problem solving was positively correlated with their emotional intelligence. -
A Comprehensive Model for Forecasting the Nifty50 Index Using MAchine and Deep Learning Methodologgy with Reference to National Stock Exchange
The volatility and uncertainty make stock and stock price index predictions challenging. Many financial professionals and academics are interested in stock price/index prediction studies. This study presents computational ML and DL intelligence techniques for estimating the NIFTY50 index closing value on the Indian NSE using Fundamental Analysis and Technical Analysis. To forecast the NIFTY50 index, we first employed Fundamental Analysis and max voting, bagging, boosting, and stacking ensemble learning techniques. An embedded feature selection algorithm is utilized to determine the model's best fundamental indicators, and a grid search is performed to tweak hyperparameters for each base regressor. Our results demonstrate that the bagging and stacking regressor model 2 beat all other models, with the lowest RMSE of 0.0084 and 0.0085, respectively, indicating an improved fit of ensemble regressors. Subsequently, TA research was done to exhibit the influence of deep learning on the NIFTY50. This method employs a data augmentation mechanism and three GRU model variations. It is examined using two datasets, TA1 and TA2, which include technical indicators from the NIFTY50 index. The GRU model enhanced the NIFTY50 index prediction using the TA1 technical indicator dataset. Finally, the study examines a hybrid model to estimate equity market trends, combining PCA with ML methods such as ANN, SVM, NB, and RF. The proposed approach uses the trend deterministic data preparation layer to convert the continuous data to a discrete form denoted by +1 or -1. The empirical findings of this hybrid model demonstrate that the RF model with the first three principal components obtains precision of 0.9969, F1-score 0.9968 and AUC score of 1. Overall, the suggested research design outperforms baseline models in our experiments and shows promising results using fundamental and technical analysis indicators. Thus, this study provides an ideal tool for stock market prediction and financial decision-makers. -
A critical analysis of the complexity of leadership in zimbabwean anglican churches
This study examines the leadership controversy in the Anglican Churches of newlineZimbabwe and evaluates the extent to which the exigencies of power impacted upon this newlineconflict. This study is necessitated by the fact that the Anglican Church Province of Central Africa has been affected by an unprecedented conflict hinged on leadership wrangle and a crisis of legitimacy. This has resulted in the excommunication of Bishop of the diocese of Harare who had deliberately withdrawn from the Anglican international communion to form the province of Zimbabwe. Key to this dispute was the allegation of gay marriages presumably blessed by the Church of the Province of Central Africa (CPCA) although it appears that there were other multifarious factors behind the controversy. Given this background, this study seeks to present a critical exploration of the cardinal factors at play within the context of the Episcopalian polity and try to link church governance and ecclesiology to the context of the Anglican conflict in Zimbabwe. It should be appreciated that, as the world is setting into the 21st Century and Globalization becomes inescapable, a new breed of leaders and leadership paradigm is needed in Christian organizations. There is newlinea general consensus among scholars that the term leadership can be defined from various newlinevantage points. But for the purposes of this study, the term leadership designates the art of inducing competence, an instrument of goal achievement, a form of persuasion. Leadership newlineis the most important factor determining the future of any organization. The style of newlineleadership in a religious organization is a critical determinant in enhancing the stability and growth of the church. To this end, leadership has to do with the manner and approach of providing direction, implementing plans for institutional development, staff development progress in pursuit of organizational excellence. -
A Critical analysis of the law relationg to elementary education in india Viz-A-Viz Minimum level of learning
The demand for free and compulsory education started in the British period. newlineThe framers directed that the object of Article 45 must be achieved within ten years newlineof the commencement of the constitution. After several judicial strictures the newlineConstitutional (Eighty Sixth) Amendment Act 2002 (Amendment Act, 2002) declared education as a fundamental right. To execute this mandate the Children Right to Free and Compulsory Education Act 2009 (RTE Act, 2009) was passed. However, the government has failed to fulfil the mandate of giving quality education in terms of minimum level of learning under the RTE Act. One of the newlineparameters of the Quality Monitoring Tool under Sarva Shiksha Abhiyan (SSA) is newlineto give quality education in terms of minimum level of learning. But, when it was newlinerealized that the children from Government schools are completing their primary newlineeducation without minimum level of learning, three amendments had been made to the RTE Act 2009, i.e., during 2012, 2015 and 2019. Yet, the latest Annual Survey on Education Report shows that there is poor minimum level of learning among children who have completed their primary education in government primary newlineschools. Thus, the purpose of this research is to critically analyse the RTE Act 2009 newlineand the subsequent amendments to the Act of 2009 and to study various policies and schemes under SSA, to explore the reasons for low level of learning in government primary school and to make suggestion to improve the minimum level of learning. -
A critical analysis of the zimbabwean political leadership in the practice of justice
Political leadership is a fundamental philosophical issue influencing governance newlineof states and the success of every state is directly or indirectly linked to the newlineleadership ideology of its political leaders. This study investigated the nature and newlinecharacter of political leaders in Zimbabwe by assessing their political philosophy in the context of the major historical events since 1890 masked by three eras namely the pre-colonial era, (characterised by little political activities) followed by the colonial era (dominated by socio-political system that weakened the African culture and governance) and lastly, the post-independence era (characterised by failure to uphold the constitution by the ruling party leadership). newlineThe scope of this study is based on benchmarking the concepts of the Zimbabwean political philosophy with political ideas from renown philosophers such as Plato, Aristotle and Gandhi. More specifically, the Gandhian philosophy was selected and conceptually applied to the Zimbabwean political situation in an attempt to develop an ideal political philosophy because of its illustrious wisdom with regards to good governance principles. A hermeneutics and newlinephilosophical analytic models were used to interpret relevant literature and leadership responsibilities as provided for in the Zimbabwe Constitution. Study findings revealed challenges in the current political leadership that calls for developing a new Zimbabwean political leadership philosophy. These include but not limited to partisan politics, political violence, unbridled favouritism and nepotism, ethnicity in leadership, state capture of key institutions, negative use of power by the state, political violence, poor electoral systems flouted with impunity and rampant corruption. These political challenges militate against democratic principles of common good that fight human oppression, repression and suppression. -
A Critical Study in ADR Mechanism in India with Reference to Court Annexed Mediation in Family Disputes
Mediation has been in vogue in India since time immemorial. Sadly, it is yet to evolve into a major dispute resolution mechanism. Alternative dispute resolution (ADR) mechanisms like arbitration, mediation, conciliation, courtannexed ADR, and summary jury trial would help in resolving all types of disputes, including those of a civil, commercial, industrial and family nature. newlineGenerally, ADR mechanisms would use a neutral third party that help the parties to communicate, discuss their differences and resolve the dispute. With matrimonial dispute numbers rising and the significance attaching to matrimonial bond in our country, the researcher set out to examine the country s court-annexed mediation mechanism to ascertain how the flaws, if any, that obtain in the mechanism can be addressed. It should lead the researcher to recommend a strategy for a seamless and hassle-free implementation of the relevant regulatory provisions. The researcher embarked on descriptive research, employing the survey method, in the newlinecircumstances. She collected data from primary and secondary sources for the newlinepurpose. The ensure bias minimisation and accuracy of findings, she interviewed two categories of respondents, namely, litigants numbering 100 and mediators numbering 100. She used a 4-point Likert scale to elicit the newlinerespondents replies to the queries raised in the Interview Schedule. Since the two variables used in the study were categorical and nonordinal, she used the Chi-square test to examine the relationship. The researcher s analysis of the data led her to conclude that there obtains a certain degree of lack of clarity in terms of the enforceability of the outcomes of mediation. For example, in court-annexed mediation, a settlement reached newlineby the parties is not enforceable automatically. It is unfortunately assumed in newlineour country that mediation is resorted to by litigants who do not have a strong newlinecase. It is also assumed that the litigant that chooses mediation is the one that newlineblinks first. -
A Feminist study of food in select culinary narratives
This research studies Indian immigrant women s relationship with food in the twenty-first century globalised, capitalist, multicultural, American society. It adds to the limited scholarship on the genre of diasporic culinary narratives by looking at the works of Shoba Narayan s Monsoon Diary: A Memoir with Recipes (2003),Amulya Malladi s Serving Crazy with Curry (2007), Bharti Kirchner s Pastries: A Novel of Desserts and Discoveries (2009) and Sandeepa Mukherjee Datta s Bong Mom s Cookbook (2013). The research thus views food as a means for immigrant women to articulate their sense of self and critique the standardization of women s relationship with food by the capitalist food industry. Moreover, critiques of capitalist notions of women s relationship with food further enables the select texts to re-envision women s relationship with the kitchen and domestic work. Finally, the study analyses select culinary narratives as paradoxical texts for its simultaneous critique of the commodification of ethnic culture and performance of cultural self-commodification -
A Frame Work For Continous Indian Sign Language Recognition Using Computer Vision
Sign language is a non-vocal, visually oriented natural language used by the hearing newlineimpaired and the hard-for-hearing part of society. It combines multiple modalities newlinelike hand movements, facial expressions and body poses. Static gestures involve basic finger movements such as numbers and alphabets, dynamic signs include words, and a sign sentence consists of grammatically connected and meaningful dynamic words. Sign Language Translation (SLT) models have been an actively evolving research topic under computer vision. One of the most challenging aspects in earlier iterations of SLTs was accurately capturing the intricate and constantly changing hand movements and facial expressions characteristic of sign language. newlineHowever, the advent of deep learning models has facilitated significant advancements in the field, particularly in the realm of continuous sign language translation. newlineThe research endeavours to develop a lightweight deep-learning framework newlinespecifically tailored for the translation of Indian Sign Language (ISL) into text and newlineaudio. The proposed framework introduces two collaborative deep-learning components that extract and classify features synergistically. The ISL video sequence serves as the input, which undergoes feature extraction utilizing the Inception V3 architecture, enabling the extraction of features from each frame. Classification models tend to be bulky and intricate, consuming substantial memory space and requiring extended training periods. This challenge has been addressed by introducing a lightweight LSTM model, which effectively utilizes the feature map generated by the Inception model for accurate classification. It is important to note that each sign possesses unique characteristics yet exhibits similar feature maps. The performance of the framework is assessed based on the speed and accuracy achieved in converting the input video into text and audio formats. -
A framework for information security assurance using DNA cryptography
Molecular biology is a branch of life science which plays a pivot role in improving the quality of life whereas Information security is another aspect for social edification, which human beings will never compromise. Both are subjects of high relevance and inevitable for humanity. Thus, an amalgamation of these subjects turns up as an innovation which is beneficial for Information security and storage. The secure transfer of information was of significant concern from ancient civilizations. Various techniques have been proposed from time immemorial to maintain the security of data so that only intended recipient should be able to receive the message other than the sender. newlineThe Information security aspects became prominent with the introduction of the newlineInternet. Regardless of the type of information which varies from a single newlinecharacter to the much-discussed Big Data , it is necessary to ensure secure storage and protection which is a matter of concern.Cryptography is an art by newlineitself and the science of secrecy which protects information from unauthorized newlineaccess. Various techniques have evolved through years of information protection newlinewhich includes Ciphers, Cryptography, Steganography, Biometrics and the most newlinerecent Nano-Cryptography comprising of Quantum Cryptography and DNA Cryptography. newlineDNA cryptography is an emerging and promising field of Information security. Dr. Leonard Adleman s experiment to solve the Hamiltonian Path Problem, which is an NP-complete problem using computational properties of DNA, has newlineredefined the word computing. The emergence of DNA computing marked the beginning of DNA Cryptography.It was a leap forward in the field of security to use biomolecular concepts and the later research followed on DNA encryption gives us new hope of unbreakable algorithms. DNA based encryption schemes work on the principles of DNA computing techniques.Cryptosystems based on DNA got relevance due to bio-computational properties of DNA. -
A Framework for Integrating Nested Queries in Natural Language Interfaces to Databases
To translate Natural Language (NL) statements into Structured Query Language (SQL) queries, different methods and systems were proposed in the past. This work presents a framework for automating the translation of Data Requirement Specifications (DRS) given by enterprise Business Users in NL into SQL queries, focusing on requirements that result in the generation of nested SQLs. The framework takes the business user s DRS given in English as input and generates an initial query sketch by employing semantic parsing. This initial sketch is further refined and newlinecompleted into a well-formed SQL by consulting the Database Schema. It performs newlinethe translation by combining NL processing techniques with Query Sketch generation newlinemethods and refines it by employing Repair techniques or extends it further. The newlineframework suggests using Lambda expressions for intermediate representation and newlineemploys standard operations of Lambda Calculus for performing the required newlinetransformations needed for translation. Lambda Context Calculus (LCC) provides the newlineoperational semantics and the relevant methods needed in transforming NL statements newlineinto SQL, preserving the integrity and compositionality24 of expressions in every step of the translation. Though Lambda Calculus is found to be effective in representing the intermediate expressions and assists in performing the transformations that are needed for translating specific predicates into SQL, its inflexibility in combining parallel computations is a constraint. To represent clauses that are in parallel or are in pipeline, and to perform the required transformations on the intermediate expressions involving these, more advanced programming constructs are needed. It also adopts functional programming techniques to deal with complex scenarios involving nested queries. -
A Mixed methods study of psyhosocial factors in career decision making in adolescents
Career choice is an important developmental task in adolescence and is influenced by many factors. Using a mixed methods research design, this study aimed to understand career decision making and factors influencing the same in adolescents. In the quantitative phase the relationship between career maturity and perceived parenting style, personality traits, metacognition, socio- economic status, gender, college type, stream of study and decision status was studied in students studying in II Year Pre- University in Bangalore, India. Career decisions, personal and family factors in career decision making were explored in the qualitative phase. Informed consent was obtained from the participants and parents of the participants of the study. newlineQuantitative data was collected from 548 students studying in Arts, Science and Commerce stream in second year Pre- University in Bangalore. Students from eight private and seven government colleges were recruited for the study. Quantitative data was collected using a socio- demographic data sheet, Career Maturity Inventory, Parental Authority Questionnaire, Neo Five Factor Inventory and Metacognitive Awareness Inventory. The scales were translated to Kannada and back translated. In the qualitative phase, data was collected through a semi- structured interview schedule designed for this study. 30 students who were a part of the quantitative phase took part in this phase. The interviews were audio-recorded and transcribed for analysis. Statistical analysis was done to analyze quantitative data. Descriptive statistics, correlation, regression analysis, t tests and one-way ANOVA was done. Qualitative data was analyzed by template analysis and themes were derived from the data. The results revealed associations between personality traits neuroticism, openness and conscientiousness and specific aspects of career maturity attitude and competence. -
A mixed methods study on factors associated with relapse of alcohol use disorder
Background: Alcohol use disorder (AUD) is one of the most concerning mental health issues in India. According to the recent survey, Magnitude of Substance Use in India, 2019, 160 million of the countrys population consumes alcohol. About 35.6% are problem drinkers among those who drink, of which 18% are alcohol dependent. Despite the greater understanding of alcohol use disorder (AUD) and the scientific advancements in treatment, relapse remains to be the main challenge in managing AUD. This study aimed at investigating various factors associated with relapse of AUD and presenting an in-depth understanding of it. Methods: A Sequential Explanatory Mixed Methods design was used. In the quantitative phase, 72 relapsed individuals with AUD currently undergoing treatment were compared with 72 individuals previously treated for AUD who maintain total abstinence for a minimum period of one year. Relapsed participants were selected from three private de-addiction centers in Bangalore and abstaining participants were recruited from various Alcoholics Anonymous meetings in Bangalore. The relapsed and sober groups were matched on gender, AUD diagnosis, and previous inpatient alcohol de-addiction treatment. Cloninger's Temperament and Character Inventory-Revised was used to assess the personality profiles of the participants. A sociodemographic and clinical information form was also used to collect data. Six participants were selected purposively from the same sample for in-depth interviews. Data analysis was conducted using SPSS and NVivo for quantitative and qualitative data, respectively. The study protocol was approved by the institutional ethics committee. Results: Bivariate analyses showed a significant difference in Novelty Seeking, Persistence, Self-Directedness, and Self-Transcendence traits between the relapsed and sober participants. Results also suggested that reported use of other substances, post- discharge follow-ups, and living with drinking or drug-using individuals are significantly associated with relapse. Logistic regression displayed incomplete treatment, use of other substances, and no post-discharge follow-up as predictors of relapse. The qualitative thematic analysis revealed preparedness, motivation, personal exceptionalism, meaning and purpose, and social and interpersonal as the main relapse-related themes. Conclusions: The findings highlight the importance of treatment engagement, discharge planning, aftercare, and special attention to those presenting with multiple substance use. It also displays a few culture-specific aspects to be considered during treatment, such as preparing the individuals entering treatment to effectively engage, assessing and working with their motivation, and addressing the relationship dynamics. -
A Model for Churn Prediction Based on Qualitative Support Interaction Features for Hotel Technology Provider
Customer retention is a significant driver of a company s growth. Machine learning has gained immense popularity as a means to predict customers at risk of churn. Churn prediction models are capable of highlighting customers who are at high risk of churn well in advance. A popular approach to improve the performance of churn prediction models is by using input variables that are mainly quantitative and structured in nature. There are limited works in literature that newlineinvestigate smart means to effectively utilize and integrate unstructured data into churn prediction models, and study the impact on model efficacy. One of the roadblocks to effectively utilize unstructured data is the associated cost of annotation which is both time consuming and requires intensive manual effort. To overcome this obstacle, researchers often adopt a semi-supervised newlineapproach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although active learning boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples for manual annotation. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly newlineinformative and representative subsets of samples for manual annotation. Data comprises newlinemessages of a set of customers sent to a service provider. Series of experiments are conducted to analyse the effectiveness of the proposed query strategy, called Entropy-based Min Max Similarity (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy. -
A Model for storage optimization of brain MRI images for tumor detection using image processing technique
Magnetic Resonance Imaging (MRI) is a major non-invasive method for Brain tumor detection. The anatomical assessment of brain newlinetumor can be carried out using brain MRI image analysis. MRI is widely used in brain tumor identification and classification. Images generated during the diagnosis purpose are unattended after the specified diagnosis. newlineBrain MRI images in Digital Imaging and Communications in Medicine (DICOM) format require large amount of storage space. newlineAccumulation of the MRI images put forward the requirement of more storage space. To store large number of images, existing storage models has to be handled wisely. Research associated with storage, process and newlinemanipulation of medical image data using modern technologies with a minimal human intervention is the need of the time. Image processing deals with the study and development of innovative technologies for newlineanalysis,representation and interpretation of the image data. In this research, the need of an efficient storage model that can help in storing the brain MRI images is studied with the help of image processing technique. To store the brain MRI images with a reduced storage space, a matrix-based method is proposed. In this model brain MRI images in newlineDICOM format are converted into matrix format. In the DICOM images, the image data and header information together hold the details of the patient and image data. These data are converted and stored in the matrix. newlineThe stored matrix is accessed as the input to the proposed model. The proposed model follows different image processing steps.The process starts with pre-processing of brain MRI images followed by clustering of newlinewhite matter (WM), gray matter (GM) and cerebrospinal fluid (CSF), segmentation of tumor and classification of tumor and finally it handles the storage of the MRI images. In the pre-processing step, filtering algorithms are applied on MRI to remove the noise and text artifacts. The newlinewhite matter, gray matter and CSF are separated using the K-means newlineclustering method. -
A Novel Approach for Sensitive Crop Disease Prediction Based on Computer Vision Techniques
Agriculture is a vital sector that plays an essential role in ensuring global food security, supporting economic development, and promoting environmental sustainability. Sustainable agriculture is an essential approach that aims to address the diffculties posed by conventional farming practices and ensure the long-term viability of our food production systems. Worldwide, crop leaf diseases seriously threaten food security and agricultural production. Early and accurate detection of crop leaf diseases is essential for effective crop productivity management and food prevention. Computer vision approaches offer promising solutions for automating the identifcation and prediction of crop leaf diseases. Analyzing digital images of plant leaves enables the identifcation of disease characteristics, such as discoloration, lesions, and patterns, which are often imperceptible to the naked eye. Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNN), have been widely employed in this domain to learn from large datasets of annotated images and accurately classify leaf diseases. The process of crop leaf disease classifcation using computer vision involves several stages. Initially, highresolution images of plant leaves are acquired using cameras or mobile devices. Preprocessing techniques, including image enhancement and noise reduction, are applied to improve image quality. Subsequently, feature extraction approaches extract pertinent data from the images, including texture, shape, and color. Deep Learning (DL) models are then trained and fne-tuned using these extracted features. newlineAlthough computer vision techniques have shown effective results in the classifcation of plant diseases, however, several challenges remain. Tomatoes and Potatoes newlineare widely cultivated and consumed vegetables worldwide and are a primary economic newlinesource for many countries. These sensitive plants are prone to various diseases during newlinegrowth, leading to signifcant losses in productivity and fnancial impact on farmers. -
A novel framework for cloud-based analytic of massive and multi-structured healthcare images for real-time insights
The dependency of healthcare industry on the information and communication technology newline(ICT) domain is consistently on the rise in order to conceptualize and provide1537608 newlinesophisticated services to various newlinestakeholders including patients, newlinecaregivers, support service providers, medical practitioners, and experts. There are a variety of decisive advancements in the diagnosis, medication and surgical processes, medical electronics, instruments and equipment, healthcare-centric robots, a bevy of cloud-based healthcare software solutions, medical data hubs, etc. One direct offshoot of all these developments is that the amount of multi-structured data is exponentially growing. There is a litany of support and expert systems in order to lessen the doctors workloads. However the brewing challenges and new-generation requirements include the real-time processing of medical data to extract real-time insights and decision-enablement, the substantial enhancements in appropriate and accurate processing and understanding of various and overlapped symptoms towards correct and strategically sound decisions, the real-time analytics of medical data, the empowerment of medical devices to assist surgeons and specialists in performing their tasks in an assured manner, etc. newlineThe Problem Description - Medical imaging is one of the fundamental and most important areas of the healthcare system. This needs accuracy in processing and producing best results for further diagnosis and action. There are various factors impelling medical imaging like patient preparation, different scanning modalities, the scanner used to capture the image and various algorithms adopted for processing the captured images. -
A Posthuman Analysis of Human - Machine Relationship in Select American Science Fiction Films
The research A Posthuman Analysis of Human Machine Relationship in Select American Science Fiction Films attempts to foreground the emerging posthuman scenario brought about by the explosion of Artificial Intelligence (AI) in contemporary life by analysing the posthuman representations achieved by depicting AI characters and their relationship with humans in the select American science fiction films. The primary texts for the study are Stephen Spielberg s AI: Artificial Intelligence (2001), Spike Jonze s Her (2013), Mathew Leutwyler s Uncanny (2015), and Drake Doremus Zoe (2018). The research analyses the posthuman newlinerepresentations in the select films using the methodological framework of philosophical posthumanism of Francesca Ferrando with its constituent elements of post-humanism, post-anthropocentrism, and post-dualism. The term posthuman in philosophical posthumanism refers to the critique of the notion of human preserved by the Western humanistic traditions. The three constitutive elements of philosophical posthumanism, namely, post-humanism, postanthropocentrism, and post-dualism, offer a revisit of the notion of human propagated by Western humanistic traditions and offer a renewed worldview of being human in the contemporary technocentric society where nonhuman agency is being widely newlinerecognized. From an epistemological perspective, this research adds to the evolving posthuman discussions, providing a new dimension to what it means to be a human and challenging the age-old assumptions about the human condition. -
A refined mechanism for human face recongnition from video footages
Undoubtedly homeland security is a noteworthy concern in today's increasingly connected world and there is a bevy of IT-based security solutions and services emerging and evolving to guarantee the safety and security of people and properties. Security and surveillance cameras are the prominent security solutions. People movements, gestures, and activities are being minutely monitored, captured as images and videos, and subjected to a variety of investigations in order to extract anything uncommon. As videos capture the movement, there is no requirement for the user to coordinate with the camera; video arrangements need not contain face images alone despite the fact that human appearances are vital articles in video sequences. Henceforth recognising a face from the sequence of a video turns into an essential undertaking in PC vision applications. As the user is not totally coordinating with the camera, it is not necessary that the face captured in the video sequence is the frontal face. At times, it need not be a human face. Hence, it is necessary to detect the human face region in a frame. If a human face is detected in a video sequence, there are chances that the detected face can be masked. It is also possible that the faces can be captured in various poses. There is also a difficulty in identifying a face subjected to various illuminations. The above natural possibility of not capturing the frontal face of a human in a frame makes the identification task difficult. This problem prompts researchers working under face recognition technology to design an improved framework that increases the recognition rate in the above situations. From the above-mentioned possibilities that deteriorate the recognition rate of a face, in this thesis work, two major problems namely face with varying pose and partially occluded faces are considered for recognition from a captured video.