A Study on Role of A.I. and Robotics in Health Care Sector: Its Impact and Contribution

Health Care is one of the major domain sectors of our country. As this domain has many different aspect of implementation, as per the current scenario of Diseases and health complications. This paper will discuss about how, the Artificial Intelligence (A.I.) and robotics can be beneficial and plays a major role on, health care domain with respect to the Efficiently Diagnose, Developing New Medicines, Earlier Detection of Diseases, Advance Treatment Care, A.I-Deep learning For the Critical Decision’s. As this Information will help to give more clarity on what, A.I. & Robotics contributes for the major Diseases Treatment by the advancement of Technology. This can be beneficial for not only Doctors, Patients, or Firm but can also be helpful for citizen people as well. The objective of this paper is to study the role of AI and Robotics in Healthcare Sector and its impact.

Introduction

This book focuses on the evolution of object clitics in the Romance languages (from now on, simply clitics). Cliticization is a major domain of research in the field of Romance linguistics. Furthermore, clitics raise many research questions that are of interest to general linguists working in any field of the discipline: phonology, morphology, syntax, pragmatics, acquisition, pathology, etc. In fact, clitics offer clues or raise problems regarding a wealth of linguistic issues, including phonological domains, information structure, syntactic movement, and language impairments. Yet scholars are seldom aware of the many empirical facets of cliticization or have not fully considered the theoretical ramifications of the topic....

Leaf Disease Classification Using Convolutional Neural Network

Agriculture is a major domain that contributes a lot for building up the country’s Economy; contributing to the GDP area synthesis of 17.9%. India stands second in production of agricultural products. Promising technologies such as Internet of Things, Machine Learning, Deep learning, Artificial neural networks contributes towards the most effective and reliable solutions by providing the most feasible solutions in making of different domain modernization through automation in monitoring and maintenance of agricultural fields with minimum human intervention. This paper presents a convolutional neural network based customized VGG framework and a lightweight architecture for the classification of tomato leaves affected with various diseases. Experimental analysis is performed on publically available PlantVillage dataset. After rigorous experiment we fined tuned the CNN model to obtain mAP of 83.33%.

Interactions between nascent proteins translated by adjacent ribosomes drive homomer assembly

Accurate assembly of newly synthesized proteins into functional oligomers is crucial for cell activity. In this study, we investigated whether direct interaction of two nascent proteins, emerging from nearby ribosomes (co-co assembly), constitutes a general mechanism for oligomer formation. We used proteome-wide screening to detect nascent chain–connected ribosome pairs and identified hundreds of homomer subunits that co-co assemble in human cells. Interactions are mediated by five major domain classes, among which N-terminal coiled coils are the most prevalent. We were able to reconstitute co-co assembly of nuclear lamin in Escherichia coli, demonstrating that dimer formation is independent of dedicated assembly machineries. Co-co assembly may thus represent an efficient way to limit protein aggregation risks posed by diffusion-driven assembly routes and ensure isoform-specific homomer formation.

PERSON-CENTERED INTEGRATIVE DIAGNOSIS: CONCEPTS AND PROCEDURES

The person-centered integrative diagnosis (PID) is a model that aims at putting into practice the vision of person-centered medicine affirming the whole person of the patient in context as the center of clinical care and health promotion at the individual and community levels. The PID is a novel model of conceptualizing the process and formulation of clinical diagnosis. The PID presents a paradigm shift with a broader and deeper notion of diagnosis, beyond the restricted concept of nosological diagnoses. It involves a multilevel formulation of health status (both ill and positive aspects of health) through interactive participation and engagement of clinicians, patients, and families using all relevant descriptive tools (categorization, dimensions, and narratives). The current organizational schema of the PID comprises a multilevel standardized component model integrating three main domains. Each level or major domain addresses both ill health and positive aspects of health. The first level is the assessment of health status (ill health and positive aspects of health or well-being). The second level includes contributors to health, both risk factors and protective factors. The third major level includes health experience and values. Experience with the PID through a practical guide in Latin America supported the usefulness and adequacy of the PID model.

Introduction

This introductory chapter traces some of the major strands of social change thought to have had an impact on different areas of children's daily time use. The past several decades have witnessed rapid social, economic, and technological change, widely thought to have affected many aspects of children's daily lives. Technological change potentially has had the most direct impact on children's lives, and certainly has garnered the most attention, through changes affecting screen-based activities. Education is a further major domain in children's lives where there has been persistent change over many decades. The chapter then examines the relationship between children's time use and outcomes relating to their health, development, and well-being, drawing together strands of thought from the sociology of childhood and research on child well-being. It sets out the data, measures, and methods of the empirical analysis, followed by a first outline of change in a child's day over four decades between 1975 and 2015.

Recommender System for Nutrient Management Based on Precision Agriculture

Agriculture is the heart of our nation and society. It is influenced by several factors and parameters such as uneven monsoon, changing climate as well as weather circumstances, rainfall and nutrient facts during the harvest. Agriculture is primarily crucial and also the main source of our livelihood. But, owed to the scarceness of nutrients in plants, the human is strained to handle many dare in everyday life. The restoration of the nutrient is essential, in this view there is need to adopt precision agriculture system which change crop related plans and regulations, whereas nutrient management is a major domain that is needed to be spotlight in the field of farming techniques. The main aim of this research is to create an idea of developing a precision based recommender system for nutrient management and the main scope of this paper to describe the initial phase of the research. The experimental study of this research work is conducted using a terrace garden. The nutrient management with respect to the horticulture crop tomato is considered as the objective. The samples are grouped as two sets namely A and B representing samples without using natural fertilizers/manures and with natural fertilizers/manures. The growth parameters are analyzed and the results are presented. The data collection phase using sensors and Arduino kit is described here. The impact of pests and the remedy taken during the period of growth is recorded. The advices from the experts given in the soil tests are considered for preparing this nutrient management system.

Issues and Considerations for Effective Text Data Retrieval

Text data retrieval is one of the major domain for extracting knowledge from the stored data sets. Within the text information, the text meaningful numerical codes extracted unstructured process information is to make the free text associated with the unstructured nature of data mining in a different stream. Number of procedure is constructed to Performing this operations most effectively. This paper focuses one of the text retrieval process, experimental results verified proposed methods works well with most of the documents.