Bøger af A. Sai Suneel

Recently a lot of study has been done on improving the visual quality of underwater and undersea imaging in submarine and military operations to find the hidden structure designs and sea excursions. This project proposed an underwater image enhancement method based on colour constancy theory. When we compare with much of the existing research, the time and complexity of the proposed method are low, and it achieves excellent performance. Firstly, we analyse the underwater imaging model and distortion. Then, by compensating the red channel and applying local white balance, a linear transformation is performed. Finally, results are obtained by applying the histogram equalization to the RGB images. We also measure the image quality by taking the parameters PSNR, UIQM, UCIQE and Entropy. These parameters are compared to proposed and existing approaches; however, our method produces higher image quality.

No rádio cognitivo de 5G, o sinal primário do utilizador é mais activo graças à ampla banda de frequência. A detecção normal do espectro cooperativo só detecta uma característica do PU utilizando um tipo de detector. A rádio cognitiva (CR) surgiu como uma técnica promissora para o problema de escassez de espectro enfrentado por todas as administrações sem fios propostas tão recentemente. Na rede de rádio cognitiva (CRN) a detecção de espectro assume a parte principal e é considerada como uma parte básica da CR. O nó CR individual pode não dar resultados de detecção válidos devido à sombra e a problemas terminais secretos do canal de comunicação sem fios. Por conseguinte, para afectar estes problemas, é proposta a implementação durante este artigo de rádio cognitivo cooperativo baseado na detecção do espectro para comunicação 5G. No esquema de detecção cooperativa do espectro (CSS), cada CR sentirá individualmente o espectro e depois transferirá a sua decisão para um nó central também referido como centro de fusão (CF). Usando a probabilidade de detecção falhada (Pmd) e a probabilidade de falso alarme (Pfa) para reconhecer se a detecção do espectro é suficiente ou não, melhorar o desempenho usando Pfa. O resultado da simulação mostra o desempenho superior.

In India and in the world pollution is increasing day to day, which severely affects all living beings and damages our earth. Because of rise in vehicles, there is a rise in air, sound pollution. On the other hand, factories also release waste gases into the air. Because of pollution there is a rise in harmful ultraviolet rays. Because of light intensity during night times, accidents occur because of light reflections from either side vehicles may cause blurred sensation in eyes. In this project we are proposing an embedded device which is a combination of embedded system and PHP web server and measure the parameters like CO gases, sound intensity, UV and light intensities. If any of these parameters crosses it¿s limit then it will send data to PHP server from the server message will be sent to the authorities to take action in that area to control pollution.

The need for the spectrum access is increasing day by day as the users are developing more interest for the utilization of the spectrum technique. But as a design issue the range of the spectrum cannot be enhanced with the need of the users and area. Hence the researchers have found the path of direction in the ideal strategy of the usage of secondary users for the spectrum in the absence of the primary users. Hence in this process, a new technique has been raised termed as the spectrum sensing for the identity of primary users with plenty of techniques and technologies, one of device used for the process of identification is the Cognitive Radio. The sensing of the spectrum criteria also involves the gathering of the signal features from the spectrum with its threshold optimized depending on the received values. Upon the detection of the threshold values the spectrum can sense the presence of the user as primary or not. The techniques that are involved in spectrum sensing are energy detection, matched filtering, correlation, etc.