The Internet of Things (IoT) represents a transformative advancement in internet technology, and its influence is particularly notable in the realm of healthcare research. The utilization of wearable sensors and Smartphones has notably expedited the progress of remote healthcare monitoring. This innovative IoT-enabled health monitoring not only aids in curtailing the spread of diseases but also facilitates accurate health diagnoses, bridging geographical gaps between patients and doctors. This article delves into the escalating demand for healthcare solutions, especially within the elderly demographic. These solutions stem from the aspiration to empower patients and seniors to sustain an autonomous lifestyle within their residences, alleviating the need for excessive dependence on family or caregivers. The primary focal point of this investigation is to conduct an exhaustive appraisal of contemporary remote health monitoring systems. Furthermore, we have identified noteworthy pre-existing RHMS systems, accentuating their potential in revolutionizing healthcare. Lastly, we have meticulously examined and discussed prevailing challenges associated with the evolution of RHMS.

The rapid growth of light electric vehicles (LEVs) as eco-friendly urban transportation solutions has triggered a surge in research on efficient and compact charging systems. This paper presents a comprehensive review of single-stage isolated bridgeless chargers designed for light electric vehicles. These chargers address the need for high-power density, reduced size, and enhanced efficiency in the charging process. The review covers the fundamental operational principles, topologies, control strategies, and key design considerations of single-stage isolated bridgeless chargers. Furthermore, a comparison of various charger configurations is presented, highlighting their advantages and limitations in terms of efficiency, cost, and power factor correction. The review concludes by identifying current research trends and potential areas for further advancement in single-stage isolated bridgeless chargers for LEVs, emphasizing the importance of innovation in power electronics and control techniques to meet the evolving demands of sustainable urban mobility.

Cooling towers are used in a variety of applications; from the 400-foot-tall towers at nuclear power plants to small 4 foot cooling boxes used by neighborhood dry cleaners. The most common use is in large building central cooling systems, but also used for refrigeration, cold storage facilities, dry cleaning, medical equipment, manufacturing and industry. Cooling towers are generally the most efficient means to remove large amounts of heat from air and equipment. Unfortunately, cooling towers use large amounts of water when properly maintained, and can waste greater amounts of water when not maintained properly through wasteful practices, inefficient equipment and leaks. Industrial cooling towers are used to remove surplus heat from water. In this study, a review study is carried out to investigate different types of cooling towers, their application, performance, usage and working principles, which can be useful in the field of nuclear plants as well as other energy stations. A number of investigations have been considered to reveal differences between the used cooling towers and finally a Fluent simulation has been carried out to examine major contours and flow field around the cooling tower.

With the increasing rise of Information Computing technology globally energy demand is also escalating which is leading to fast-rising of financial and environmental costs. Global warming is continuously increasing in the planet there is need of an hour to cut down the extreme carbon emissions particularly to save the planet earth. Data centers also play an important role they are considered to be the second most significant contributor in carbon emissions. To minimize this carbon emissions and the impact of climate Change, The new green policies need to be initiated and implemented by designing the proper road map to overcome this issue by all the high energy usage industries. To contribute environment the responsibility should be shared by all stakeholders’ governments, private organizations and community at large. This paper highlights the issues that contribute in the accomplishment of the objective of zero carbon emission, by using renewable energy, innovative technologies, creating awareness for the organization and by easing green policy implementation.

In modern times, email has emerged as the most common way of communication that is also the quickest and most cost-effective. For many inhabitants, the data sharing process has evolved into a routine part of their day-to-day lives. Email, on account of its user-friendliness, is vulnerable to a significant deal of potential threats. The sending of unsolicited commercial email, also known as spam, is one of the most fundamental risks associated with electronic communication. The expansion of the spam movement is an issue that should be of concern since it wastes system data transfer capacity, the time of customers, and memory space, and it also results in monetary loss for both customers and businesses. In this research, we make a recommendation for a model that does characteristic choice for ruthless spam recognition in email. Our goal is to streamline the grouping parameter, the figure precision, and the computation time for later on characterization calculations. In order to accomplish this, we offer a model that can perform characteristic choice. The method of determining features will make use of the work of ling spam dataset, and after that, the arrangement of chosen features will be validated with four different classifiers, namely Support Vector Machine (SVM), Naive Bayes (NB), Logistic Regression, and Random Forest.

Humans have evolved to communicate with one another primarily through speech since it is the most natural, effective, and favored way of communication. As a result, it is reasonable to presume that individuals are more at ease utilizing speech as a means of input for a variety of computers as opposed to other more archaic modes of communication such as keypads and keyboards. A system that uses Automatic Speech Recognition (ASR) assists us in accomplishing this objective. A method like this enables a computer to accept an audio file or direct voice from a microphone as an input and convert it into text, ideally, the text will be in the script of the language that was said. The ability to accommodate variety in speech presents the greatest difficulty for automatic speech recognition. The idea of automatic speech recognition (also known as ASR) is broken down and analyzed in this study from the perspective of pattern recognition. In this paper, several various research gaps are investigated, as well as state-of-the-art architecture models of ASR, and their classification is explained from a comprehensive perspective. The development of a speech recognizer that works in real time may encounter obstacles ranging from challenging environments to the anatomy of the human body. In addition to that, it incorporates linguistic considerations. In this study, we investigate a variety of obstacles that must be overcome while creating a reliable ASR system.

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Face Recognition wrapping Curvelet Transform based. The Wrapping Curvelet Transform is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidian Distance (ED) to compute Equal Error Rate (EER) and True Success Rate (TSR). The proposed algorithm with WCT performs better than Curvelet Transform algorithms used in [1], [10] and [11].