The aim of the Criminal Justice System is to punish the guilty and protect the innocent. Although the broad contours of the Criminal justice system are seldom codified, these can be inferred from different statutes, including the Constitution and judicial pronouncements. In a democratic civilized society, the Criminal Justice System is expected to provide the maximum sense of security to the people at large by dealing with crimes and criminals effectively, quickly and legally. More specifically,

(सांस्कृतिक संक्रमण काल में महिला लेखन का उत्तरदायित्व) आज जिस युग में हम साँस ले रहे हैं वह विभिन्न संस्कृतियों का ‘संक्रमण काल’ है। विशेषतया भारतीय एवं पाश्चात्य संस्कृति के समागम का। इस संक्रमण के दौर में भारतीय संस्कृति का अस्तित्व खतरे में नजर आ रहा है। क्योंकि भारतीय मानव को यदि गौर से देखा जाए तो वह भी बेमेल संगम या अवांछित मिश्रण सा नजर आता है। यह संगम फूल में सुगंध का नहीं है, अपितु दूध में नींबू का है। नींबू जिस प्रकार दूध के अस्तित्व को समाप्त कर उसे नया रूप देता है, उसी प्रकार भारती

Radiation is the emission or transmission of energy as waves or particles through space or through a material medium which is able to penetrate various materials and is often categorized as either ionizing or non-ionizing depending on the energy of the radiated particles. Radiation processing can be defined as exposure of materials with high energy radiation to change their physical, chemical, or biological characteristics, to increase their usefulness, and safety purpose, or to reduce their har

Peter Senge's five disciplines—personal mastery, mental models, shared vision, team learning, and systems thinking—constitute the cornerstone of a learning organization. This paper reviews these disciplines in the context of the service industry in India. The service sector, a major contributor to India's GDP, faces unique challenges and opportunities in implementing these disciplines. This review examines how each discipline can be applied, the benefits they bring, and the challenges faced by o

With the rise of collaborative robots, the need for safe, reliable, and efficient physical human–robot interaction (pHRI) has grown. High-performance pHRI requires robust and stable controllers suitable for multiple degrees of freedom (DoF) and highly nonlinear robots. In this article, we describe a cascade-loop pHRI controller, which relies on human force and pose measurements and can adapt to varying robot dynamics online. It can also adapt to different users and simplifies the interaction by

Feature extraction is essential in bioinformatics because it transforms genome sequences into the feature vectors required for data mining activities such as classification and clustering. The data mining activities enable us to classify or cluster the newly sequenced genome to the known families. Nowadays, a variety of feature extraction strategies are available for genome data. Nevertheless, several existing algorithms do not extract context-sensitive key properties, also some approaches extra

Cloud computing is the upcoming environment in the use of computer technology. Numerous users are keen to put their information in cloud; since balancing load in cloud a risky. Load balancing resource allocation plays a vital role. This chapter deals with the research motivation, the objectives and the thesis organization.

Efficiently executing image categorization with high spatial quality imagery from remote sensing can bring great benefits to scene classification. Effective feature representation is critical in the development of high-performance scene categorization techniques because sensor data processing is tough. Remote sensing as well as deep learning abilities have made it easier to extract spatiotemporal information for classification. Furthermore, other scientific disciplines, together with remote sensing, have made significant advances in image categorization by convolutional neural networks (CNNs), and transfer learning is being combined. Image categorization in this article was performed to enrich the accuracy of Scene classification using Transfer learning utilizing pre-trained Alex Net, and Visual Geometry Group (VGG) networks and compared with feature extraction methods. First, features were retrieved from the pre-trained network's second fully-connected layer and employed in SVM classification. Second, substituting the last layers of pre-trained networks with the notion of transfer learning was used to categorize new datasets. It is executed on the UCM Dataset as well as the SIRI-WHU Dataset. The proposed methodologies produced improved accuracy of 95% for UCM, 93% for SIRI-WHU Datasets. The categorization of scene images into a distinct set of meaningful groups based on the image contents is important in the analysis of imaging sensor, aerial and satellite images because of its importance in an extensive range of applications, significant various approaches for remote sensing data scene classification have been developed throughout the last few decades. The capacity to handle large dimensionality data and perform well with limited training samples, as well as high accuracy, drew a lot of attention with the introduction of SVM machine learning. We can use a pretrained network as a commencement for learning a new deep learning task by replacing the pretrained network's fully connected layer and classification layer.

Autisum Spectrum Disorder (ASD) is characterized by deficits in social communication and interaction, making early intervention critical in improving long-term outcomes. Play-based therapy has emerged as a promising approach to addressing these social challenges, offering a structured yet fiexible therapeutic method for enhancing social skills in autistic pre-schoolers. This review explores the effectiveness of play-based therapy in fostering social development, focusing on various methodologies, including Floor time, Integrated play Group (IPG), and Pivotal Response Training (PRT). By synthesizing existing literature, this paper evaluates the efficacy of these interventions and their implications for clinical practice.

The researchers reviewed the use of statistical models to make forecasts and understand time series data, to check how accurate, easy to understand and strong they were. To evaluate these models, data from the real world and produced using generators was used together. Forecast accuracy, residual checks and the models’ responses to missing or incorrect data were all evaluated when judging the models. It was revealed that conventional models such as ARIMA and Holt-Winters did okay, but were not as useful for analyzing complex patterns and shifts. Similarly, SARIMA and most importantly State Space models delivered the best results across most measures. The research finds that first selecting the proper model, based on the data and the expected use, is important for avoiding errors and getting useful insights in time series analysis.

Similar to Western countries, the early origins of special education in India started with Christian missionaries and nongovernmental agencies which stressed a charity model of serving populations such as the visually, hearing, and cognitively impaired. However after its independence from Great Britain in 1947, the Indian government became more involved in providing educational, rehabilitation, and social services. Thus over the past four decades, India has moved gradually toward an inclusive education model. This chapter discusses the implementation of such a model related to the prevalence and incidence rates of disability in India as well as working within family environments that often involve three to four generations. Also included are challenges that an inclusive education system faces in India, namely, a high level of poverty, appropriate teacher preparation of special education teachers, a lack of binding national laws concerned with inclusive education, a dual governmental administration for special education services, and citizen’s and special education professionals strong concern about whether inclusive education practices can be carried out.