Multilevel inverters have become popular among high power converters for the past few years due to their high quality output waveform and low total harmonic distortions (THD). In addition, the filter size also reduces significantly to achieve a pure sine wave output. Cascaded H-Bridge topology has been recognized as the most promising among various classical topologies for multi-level inverters on the basis of its modular form and ease of design, troubleshooting, packaging and high power capabilities. However, a large number of switches are required in cascaded H-Bridge multilevel inverter that leads to larger system losses and an increase in cost. In this paper the modified cascaded topology is proposed to reduce the number of controlled switches without affecting the resolution of output waveform or the number of voltage levels. We achieved this by replacing some of the high cost controlled transistor switches with diodes, in the cascaded H-Bridges. Furthermore, equal voltage source sharing is also possible by using the proposed topology. Hence the proposed inverter is a type of cascaded multilevel inverter with reduced switches, better modular structure, low cost and high efficiency. The inverter design is validated using simulations and tested on hardware prototype.

Conversational agents like Alexa from Amazon, Siri from Apple, Assistant from Google, and Cortana from Microsoft demonstrate extraordinary research and potential in conversational agents. A conversational agent, chatter-bot, or chatbot is a piece of computer software supposed to communicate at a level of intelligence comparable to a person's. Chatbots are designed for various purposes, such as task-oriented helpers and creators of open-ended discourse. Numerous approaches have been studied, from primitive types of hard-coded response generators to contemporary ways of constructing artificial intelligence. These are classified as rule-based or neural network-based systems. Unlike the rule-based technique, which is based on pre-defined templates and responses, the neural network approach is based on deep learning models. Rule-based communication is optimal for more straightforward, task-oriented conversations. Open-domain conversational modeling is a more complicated topic that depends heavily on neural network techniques. This article begins with an overview of chatbots before diving into the specifics of a variety of traditional, rule-based, and neural network-based methods. A table summarising previous field research closes the survey. It looks at the most recent and vital research on the subject, the evaluation instruments used areas for improvement, and the applicability of the proposed methods.

The Digital image processing is one of the most widely implemented fields worldwide. The most applied applications of digital image processing are facial recognition, finger print recognition, medical imaging, law enforcement, cyber-crime investigation, identification of various diseases and criminals, etc. The subject to be discussed in this article is skin detection. Skin detection has solved many serious problems related to digital image process. It is one of the main features in making an intelligent image processing system. The proposed methodology conducts an improved and well enhanced skin detection, the skin and non-skin parts are divided from an input image or video, noise is removed, HSV is applied which also acts as a color model that generates more better results in accordance to RGB or YCbCr for skin and face identification. The algorithms, NOGIE (Noise Object Global Image Enhancement) and NOWGIE (Noise Object with Global Image Enhancement) are applied separately on the input and the results can be compared for better perception and understanding of the applied skin detection techniques, the skin parts are highlighted as "White" while the Non-skin parts are highlighted as "Black". The results are different NOWGIE gives better results than the NOGIE due to the image enhancement technique. This methodology is subjected to be implemented in special security drones for the identification of suspects, terrorists and spy's the algorithms provides the ability to detect humans from a non-skin background making an autonomous and excellent security system.