Two Popular Democracies\u27 Energy Independence Initiatives Through the Lenses of Constitutionalism, Environmentalism, and Judicial Activism Oeuvres--A Comparative Study of the Trump and Modi Administrations

The energy independence approaches by two popular democracies, the United States and India, have recently been the center of attention. This Article examines whether two Democratic leaders, the President of the United States, Donald Trump, and Prime Minister of India, Narendra Modi, have maintained constitutionalism in light of executive orders and ordinances that focus on energy independence by way of promoting coal-fired power plants rather than focusing on the environment and human health. Based on constitutional underpinnings, this Article concludes that although both leaders and their administrations may not have violated their respective constitutions, they have certainly violated notions of environmentalism. This Article then broadly defines what environmentalism is through different discussions and concludes that the Trump administration and Modi administration have violated environmentalism because both ignored many norms of global and national pollution control mandates and environmental justice concerns related to coal mining. This Article then explains and concludes with whether the judiciary will be able to save the day

Data interoperability and privacy schemes in healthcare data using Blockchain technology

Abstract. Electronic Health/Medical Records (EHR/EMR) lay the foundation for securely maintaining medical records. The traditional EHR systems are not effectively managed data manipulation, delayed communication, trustless data storage, data cooperation, and distribution. Blockchain technology can play a major role in healthcare cases. This is because it uses decentralized distributed ledgers to securely manage all parties within the network. It also handles individual data through smart contracts, which can be pre-programmed by the patient for access and maintenance of healthcare data. This thesis focuses on exploring the blockchain in digital healthcare services such as Electronic Health/Medical Records (EHR/EMR). Blockchain-based implementations of Ethereum allow patients to store their medical data with smart contracts that can perform activities such as Registration, Data Append, and Data Retrieve. The challenges faced during the implementation of blockchain protocols are discussed and analyzed in the scope of finding sustainable solutions to develop secure and reliable operation

FACTORS AFFECTING THE PERCEPTIONS OF PILGRIM TOURISTS IN SELECTION OF ACCOMMODATION AND TRANSPORTATION: A CASE STUDY OF GOLDEN TEMPLE, VELLORE CITY, TAMIL NADU, INDIA

Purpose of the study: This empirical study aims to identify the perceptions of pilgrim tourists’ regarding their accommodation and transport facilities in the Golden Temple, Vellore city, Tamil Nadu, India. Methodology: This study used both primary and secondary data for data collection among pilgrim tourists. Data were later on analyzed using SPSS statistical tools like percentage, Chi-square, ANOVA using Statistical Package for Social Sciences were applied. Results: The findings of the study indicate that the income of the family doesn’t relate to accommodation facilities and the age of the respondents was affected by the transport facilities in Vellore City. Applications of this study: The study brings to highlights the basics of accommodation and transportation and the factors affecting the perception of pilgrim’s tourists. It concludes that the age of the respondents affects the transport facilities in Vellore City. The transportation facilities should be improved for the tourists to attract and improve pilgrim tourism. Novelty/Originality of this study: The study has found that the tourists had sufficient maturity, education and good exposure about their destination. The study found that accommodation facilities such as comfort, peace, safety and security, attitude and behavior of staff, and sanitation and hygiene are not more satisfied. Transport facilities such as Signboard, street lights, traffic rules have to be improved

Particle swarm optimized extreme learning machine for feature classification in power quality data mining

This paper proposes enhanced particle swarm optimization (PSO) with craziness factor based extreme learning machine (ELM) for feature classification of single and combined power quality disturbances. In the proposed method, an S-transform technique is applied for feature extraction. PSO with craziness factor is applied to adjust the input weight and hidden biases of ELM. To test the effectiveness of the proposed approach, eight possible combinations of single and combined power quality disturbances are assumed in the sampled form and the performance of the proposed approach is investigated. In addition white gaussian noise of different signal-tonoise ratio is added to the signals and the performance of the algorithm is analysed. The results indicate that the proposed approach can be effectively applied for classification of power quality disturbances

Continuous glucose monitoring system - useful but expensive tool in management of diabetes

Until recently, self monitoring of blood glucose (SMBG) was the only tool used for monitoring blood glucose levels. The limitation of SMBG is that it cannot continuously monitor blood glucose levels. In this paper, we present our initial experience with the continuous glucose monitoring system (CGMS) in three different clinical situations. With reduction in cost and further refinement in technology, CGMS could become a valuable tool for clinical practice and research studies in diabetes

Growth and mortality parameters of the three spot crab, Portunus sanguinolentus (Herbst, 1783) from Gulf of Mannar, South East Coast of India

1534-1539The stock characteristics of growth and mortality parameters of portunus sanguinolentus were studied from Gulf of Mannar. The carapace width of male and female P. sanguinolentus was ranged from 3.9 cm to 19.10 cm, carapace length 1.9 cm to 10.3 cm and the weight ranged from 15 to 328 g. The growth parameters of P. sanguinolentus (Male- L∞ = 19.31 cm, K = 1.08 yr-1, t0 = -0.165: Female - L∞ = 20.49 cm , K = 1.43yr-1, t0 = -0.121). The mortality parameters like natural mortality (M), fishing mortality, total instantaneous mortality (Z) and exploitation ratio (E) of P. sanguinolentus (Male- M = 2.00; F = 1.97; Z = 3.97 & E=0.4962: Female -M =2.3; F = 2.39; Z= 4.69 and E = 0.5095) were observed. The results showed that P. sanguinolentus population is marginally over exploited at Gulf of Mannar

UNSUPERVISED CHANGE DETECTION FOR MULTISPECTRAL IMAGES

This paper presents a novel approach to unsupervised change detection in multispectral remote-sensing images. The proposed approach aims at extracting the change information by jointly analyzing the spectral channels of multitemporal images without any training data. This is accomplished by using a selective Bayesian thresholding for deriving a pseudo training set that is necessary for initializing an adequately defined binary semisupervised support vector machine (S3VM) classifier. Starting from these initial seeds, the S3VM performs change detection in the original multitemporal feature space by gradually considering unlabeled patterns in the definition of the decision boundary between changed and unchanged pixels according to a semisupervised learning algorithm. The values of the classifier parameters are then defined according to a novel unsupervised model-selection technique based on a similarity measure between change-detection maps obtained with different settings

Design of a Partial Resonant Inverter for solar photovoltaic applications

This paper presents a solar-powered Partial Resonant Inverter (PRI) interfaced with an asymmetrical cascaded nine-level inverter. The DC input of the proposed system is obtained using Solar Photovoltaic (SPV) panel. The input DC sources fed to the asymmetrical cascaded nine-level inverter are in the ratio of 1:3. The step modulated nine-level inverter works with a precalculated switching angle for a fixed modulation of 0.7. Compared to the conventional 50 Hz inverter and the multi-output transformer design, the proposed system is more compact because of the high-frequency AC link. The PRI ensures Zero Voltage Switching (ZVS) and reduces the switching losses. The proposed scheme has been validated in the MATLAB/ SIMULINK environment and an experimental prototype is built in the laboratory. Based on the investigations the Selective Harmonic Elimination (SHE) method gives superior performance when compared to the Optimal Harmonic Stepped Modulation (OHSM) method. From the results and comparative analysis, the proposed system uses fewer switches to obtain the nine-level output, uses the PRI setup with the multioutput transformer to make the design compact and improves the power quality of the system

Optimal Denoising System for Medical Images Using Recurrent Neural Network and SVM

Image denoising serves as a crucial preprocessing step in the realm of medical image analysis, with the primary objective of faithfully reconstructing the original image from its noisy counterpart. This process is essential for maintaining the integrity of vital details, such as edges and textures, within the denoised image. Innovatively addressing this challenge, our proposed system introduces a novel approach that seamlessly integrates Recurrent Neural Network (RNN) and Support Vector Machine (SVM). This powerful combination is adept at efficiently eliminating various types of noise, including gaussian, white noise, salt and pepper noise, and speckle noise, from intricate lung CT images. To enhance both learning accuracy and training efficiency, we have incorporated batch normalization in conjunction with residual learning. Notably, batch normalization is executed with the support of Long Short-Term Memory (LSTM). This strategic integration aids in the gradual separation of image structure from the noisy observations, a pivotal aspect in achieving optimal denoising outcomes. This approach not only enhances the accuracy of denoising but also contributes to reducing the overall training time, making it a valuable advancement in medical image preprocessing

ANDROID - ARM BASED SWITCH CONTROL USING SMART PHONE

The main idea behind this proposal is to provide an ease off access to the user by providing full control over his/her entire home. Due to modern city life we never find time to check any of our electric appliances, switches, thermostats, air conditioners and so on, whether they are regularly switched off when not in use. This results in Energy wastage, security risk, and eventually leads to stress. In our method we suggest an ease off method by using an Android phone with minimal power specifications