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The demand for electrical energy is steadily increasing, and the buildings sector represents one of the largest energy end use. The larger amounts of that energy are wasted due to unnecessary heating and cooling. Several studies have shown that the major reason for this behaviour lies in poor controls and the lack of feedback information. In this paper we develop a device that controls home appliances from distance with integrated acknowledgement feature. Unlike the conventional system present in houses, where one has to manually switch on and off the appliances. The proposed system allows the owner of the house to control the appliances wirelessly through a centred location. This is extremely convenient for users as they can control their house loads at any time and from any place (depends on range of the RF module). This system consists of an Arduino microcontroller with various sensors such as a temperature sensor, simple RF modules as well as actuators to control the air conditions. The simple measures show that using the suggested system can save the electricity cost for every test case.

Solar photovoltaic (PV) energy stands as a predominant source of renewable power. The efficiency of energy conversion from sunlight via photovoltaic panels is subject to fluctuation due to varying solar intensity and radiation levels. To optimize the power output, the Maximum Power Point Tracking (MPPT) technique is pivotal. Among the various methods available, high- performance soft computing techniques serve as robust MPPT strategies. This paper introduces a Fuzzy Logic Controller (FLC)-based MPPT system for grid-connected PV systems operating under both steady and variable climatic conditions. The FLC-based MPPT system adeptly adjusts the PV system’s voltage, current, and power settings to harness the maximum feasible power output from the photovoltaic panels. Simulation outcomes demonstrate that the FLC- based MPPT system outperforms the conventional Perturb and Observe (P&O) MPPT method. The employment of a fuzzy logic-controlled grid connection for PV systems heralds significant enhancements in the efficiency, stability, and reliability of integrating renewable energy into the electrical grid. Leveraging fuzzy logic algorithms, this technique allows for dynamic power management, precise voltage regulation, and enhanced frequency stability, effectively mitigating the issues inherent to intermittent solar power. A notable strength of this approach is its inherent flexibility, adapting in real-time to fluctuating environmental and grid conditions, thereby optimizing system performance across diverse scenarios. Furthermore, the implementation of a fuzzy logic- controlled grid connection ensures smooth integration of PV systems into the grid, reducing risks associated with grid disturbances, voltage fluctuations, and frequency anomalies. This strategy not only bolsters the reliability of renewable energy sources but also enhances grid resilience against variable demand and generation dynamics. In summary, the integration of fuzzy logic-controlled connections presents a forward-thinking solution that significantly advances PV system integration into the grid, yielding marked improvements in efficiency, reliability, and overall grid stability. Fuzzy logic-based MPPT offers a robust and adaptable approach to tracking the maximum power point in grid-connected PV systems, overcoming some of the limitations of traditional methods like P&O.

The research delves into the topic of power quality event extraction and compares two parameters—voltage sag/swell and harmonics—using data supplied by SVG and waveforms created by Matlab. When it comes to power quality analysis, the SVG method shines through in the qualitative comparison of findings.

Analogue electronics devices are losing ground to digital electronics components in today’s technologically evolved society. Another aspect of our increasingly digital society is the home device control system. A lot of people are chatting it up over the cellular phone network. These phone networks rely on WIFI modules as their foundation. A shorthand way to say “global system of mobile communication” is WIFI. In addition to being widely employed in industry, it is also used in several electronics projects undertaken by engineering students. It is possible to operate equipment from afar using WIFI-based projects. For instance, what if you wanted to be able to operate any equipment from afar using only your cell phone? Would it be possible? Sure, I can help you with that. Wi-Fi modules and cell phones make it easy to power on and off various gadgets. The home devices control system was developed to enable the control of home equipment from a mobile phone by using the aforementioned ideas. This document makes use of a regulated 5V, 1A power source. When controlling voltage, a 7805 three-terminal regulator is ideal. When a 230/12V step-down transformer’s secondary AC output needs rectifying, a bridge-type full wave rectifier is the way to go.

Introduction: Receiver Operating Characteristic (ROC) curve is one of the widely used supervised classification techniques to allocate/classify the individuals and also instrumental in comparing diagnostic tests. Generally to deal with classification problems we need to have knowledge of class labels. In most of the scenarios, data exhibit multi-model patterns in class labels which leads to multi-class classification problems. Objective: The main aim of this study is to address the issue of constructing ROC models when there exist multi-models patterns in the class labels further, to classify the individuals for better diagnosis, and also to reduce the complexity of graphical representation of ROC curves in such classification problems. Methods: A new version of univariate and multivariate ROC models are proposed in the framework of Finite Mixtures, due to the flexibility of identifying and modeling the subcomponents in the heterogeneous populations. Results: Oral Glucose Tolerance Test and Disk Hernia datasets are used and simulation studies are also performed. Results show that the proposed models possess better accuracy when compared with Bi-Normal and MROC models with reasonable low 1-Specificity and higher Sensitivity. The ROC curves are depicted in a 2D space rather than a higher dimension for multi-class classification problems. Conclusions: It is suggested that before one proceeds to model ROC curves, it is better to take a look at the density patterns of the study variable(s), which in turn help in explaining the true information between the classes and also provides a good amount of “true” accuracy.

The development of Artificial Intelligence over many decades had beeninconceivable, where it converts every member of the global frugality, including husbandry. The traditional approach of the agrarian assiduity is passing a vital revolution. With requirements of better crop yield, Al has been developed as a important tool to permit growers in monitoring and detecting the crop conditions. In addition, growers can fluently identify the crop conditions in early stage by using AI. As traditional factory complaint identification includes moxie and high processing time, Al is integrated with image processing with an ideal of furnishing accurate, presto, effective and affordable result for complaint discover To overcome this problem early complaint identification, bracket and discovery is needed. lately, deep literacy is veritably popular object recognition and discovery. complication Neural Network id part of deep literacy which is extensively used in object discovery part. In these different infrastructures of complication Neural Network areused. by applying convolutional neural networks(CNNs) familiar with some of the notorious infrastructures, specially the" ResNet" armature, using an stoked dataset containing images of healthy and diseased leaves (each splint is manually cut and placed on a invariant background) with respectable delicacy rates in the exploration terrain. This Deep literacy fashion has shown veritably good performance for colourful object discovery problems. The model fulfills its part by classifying images into two orders(complaint-free) and diseased). According to the results attained, the developed system achieves better discovery performances than those proposed in the state of the art. [ABSTRACT FROM AUTHOR]

Nanocomposites of diphenylalanine (FF) and carbon based materials provide an opportunity to overcome drawbacks associated with using FF micro- and nanostructures in nanobiotechnology applications, in particular their poor structural stability in liquid solutions. In this study, FF/graphene oxide (GO) composites were found to self-assemble into layered micro- and nanostructures, which exhibited improved thermal and aqueous stability. Dependent on the FF/GO ratio, the solubility of these structures was reduced to 35.65% after 30 min as compared to 92.4% for pure FF samples. Such functional nanocomposites may extend the use of FF structures to e.g. biosensing, electrochemical, electromechanical or electronic applications.

In India, the gross enrolment ratio has increased from 13.1 per cent in 2007-2008 to 15 per cent in 2011-2012 which moves the country from elite to a mass higher education system. This article seeks to examine the enrolment of scheduled caste (SC) students across various states in the country and the expenditure by each state and its effect on SC enrolment. The secondary data is the main source for analysis and data envelopment analysis (DEA) is used to explain the expenditure and enrolment pattern. The data pertain to public expenditure and SC enrolment for the period 2004-2010. The study has revealed that out of 25 states, the smaller state Sikkim is performing relatively better than the larger states which suggests the need for state-specific strategies in addressing the issues of expansion of higher education.

The "Cyber Watch" initiative addresses the escalating need for comprehensive online security in our interconnected society. This paper is dedicated to safeguarding digital assets and ensuring a secure digital environment for users of all technical backgrounds. By employing cutting-edge tools and vigilant monitoring, "Cyber Watch" proactively identifies and thwarts cyber threats, maintaining a step ahead of cybercriminals to provide a worry-free online experience. Beyond technological measures, the project places a strong emphasis on user empowerment through educational initiatives on potential risks and protective measures. Adopting a multifaceted cybersecurity approach, it integrates threat detection, prevention, and mitigation strategies. Through the incorporation of machine learning and threat intelligence, "Cyber Watch" strives to establish resilient digital ecosystems capable of withstanding sophisticated cyberattacks.