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Now a day every information is stored and shared on the cloud. And so the medical record especially Personal Health Record (PHR) is an important part of health information exchange, that is need to be stored at cloud servers. But there are various privacy problems as personal health information could be discovered to unauthorized people. That need guarantee of the patient control over to their own PHRs, in this method encryption of the PHRs is done before the storage on cloud. But still issues like risks of privacy, efficiency in key administration, flexible access and efficient user administration, have still remained the important challenge toward achieving better, cryptography imposed data access control. In this research development, we develop a mechanism for control of data access to PHRs stored in cloud servers. To achieve this efficient and modular data access control for PHRs, we provide encryption approach for the encryption to each PHR file. For this system method already tried to focus on the multiple data ownership scheme also dividing the users into security domains that highly reduce the key management complication for owners and users. Here the system takes patient privacy as serious issue and guaranteed it by exploiting multi-authority Encryption. Our main aim is not only privacy but also systems scheme try to enable modification of access policies or file attributes, and break-glass access under emergency situations. Our proposed scheme shows Extensive analysis and experimental results are presented for security and efficiency of PHR.

Very basic example of including R code in a LaTeX document.

Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

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Husnul Abid's CV

This template is based on the "Study Guide" (Kompendium) provided by the Institute of Political Science at the University of Bremen

Dissertação de Mestrado - Profmat Universidade Federal do Espírito Santo

Template para TCC, Tese e Dissertação do Instituto de Computação da UFAM.