Data analytics involves examining raw data to extract insights and make informed decisions. It includes various techniques and processes to clean, transform, and model data to discover patterns, trends, correlations, and other meaningful information. It's used across industries for purposes like optimizing business operations, understanding customer behavior, improving healthcare outcomes, and more. Tools like statistical analysis, machine learning, data mining, and visualization aid in this process, allowing analysts to derive actionable insights from large and complex datasets.
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The Internet of Things (IoT) is a revolutionary technological concept that has transformed the way we interact with the world around us. It refers to a network of interconnected devices, objects, and systems that have the ability to collect, exchange, and process data over the internet without human intervention. These devices, often embedded with sensors and connectivity features, can range from everyday objects like smartphones and wearable devices to specialized equipment in industries, such as sensors in manufacturing plants or smart meters in energy grids. The power of IoT lies in its ability to enable seamless communication and collaboration between these devices, leading to unprecedented levels of automation, efficiency, and convenience in various aspects of our lives. Through IoT, devices can communicate with each other, share information, and perform tasks autonomously, creating a more connected and intelligent environment. This interconnectedness has given rise to a wide array of applications across numerous industries. In healthcare, IoT enables remote patient monitoring and personalized healthcare solutions. In agriculture, it facilitates precision farming techniques. Smart homes and cities utilize IoT to enhance energy efficiency, security, and overall quality of life. Industries like manufacturing and transportation benefit from IoT through predictive maintenance and optimized
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In this time of rapid invention and utilisation of battery-operated products, battery life is a significant problem. Because the traditional Full Adder(FA) uses more energy, we used low power FA circuitry in this study and examined how it functions in lieu of the traditional Full Adder circuitry. Contrary to the latest State of Art, only ten transistors make up the suggested design,which runs on a 0.8 supply voltage. This study compares and contrasts the present design with the FA's suggested work in respect of power and delay. This design consumes low power of only 674.38 nWand is area efficient as it consists of only ten transistors. The presented design of FA consumes less power and offers very less delay of only 2.3 ps than existing designs. TANNER EDA is used to simulate proposed FA and using a 65nm CMOS technology.
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Medical image fusion technology and its collective diagnosis are becoming crucial day by day. This task confers the latest algorithm for image fusion of medical images to many diagnostic complications. Firstly, transform is employed on input source images. The result of the application of transform is the decomposition of source images into various subbands. Eminent features are extracted from these subbands by using resnet50. These features are fused by phase congruency and guided filtering fusion rules. Finally, inverse transform gives the original image. The experiment results of this algorithm are compared with different methods by taking some pairs of medical images. Subjective and objective outcomes prove that the proposed algorithm exceeds the current methods by giving optimal performance measures in the area of medical diagnosis. Thus, it is revealed that the suggested multimodal image fusion model provides elevated performance over existing models via diverse diseases using MRI-SPECT and MRI-PET.