A Secured Joint Encrypted Watermarking In Medical Image Using Block Cipher Algorithm

ABSTRACT At present year, most of the hospitals and diagnostic centre have exchanging the biomedical information through wireless media. reliability of the information can be verified by adding ownership data as the watermarking and encryption in the original information. In our proposed work, a joint encryption/watermarking system for the purpose of protecting medical image. This system based on approach which combines a substitutive watermarking algorithm with an encryption algorithm, advanced encryption standard (AES) in counter mode. If the watermarking and encryption are conducted jointly at the protection stage, watermark extraction and decryption can be applied independently. The capability of our system to securely make available security attributes in encrypted domains while minimizing the elapsed time. Furthermore, by making use of the AES algorithm in counter (CTR) mode make our compliant with the DICOM (Digital Imaging and Communications in Medicine) standard

A Hybrid Pre-Processing Techniques for Artifacts Removal to Improve the Performance of Electroencephalogram (EEG) Features Extraction

ABSTRACT-Electroencephalogram (EEG) blend reflects the summation of the synchronous activity of thousands or millions of neurons that have parallel spatial direction. EEG Signals are extracted from Human Brain. While Extracting an EEG Signals, large amount of data with diverse categories will be collected from the human skull. To investigate and categorize the valuable information from the EEG recordings, computerized methods are required, because removing any of the components would remove too much of useful EEG signal in sequence. EEG Recordings generally not just contains electrical signals from mind, which is polluted with various artifacts. It is the combinations of unwanted mechanisms like Power Line Noise, Electrocardiogram (ECG), Electrooculogram (EOG) and Electromyogram (EMG). Signals in the EEG that are of non-cerebral origin are called artifacts. So, before analyzing the brain signals they need to be preprocessed. The focus of this paper is proposing the development of an integrated artifacts removal technique that can automatically discover and remove the artifacts in order to smooth the progress of EEG Assessment, and the hybrid pre-processing techniques is based on the joint venture of Adaptive Filtering, Wavelet Denoising and Independent Component Analysis (ICA) in order to improve the feature extraction performance of the EEG Signals. This paper converse the comparison with existing techniques, and discuss the advantages of the proposed hybrid pre-processing Technique

A Welfare Facility for Elders Based On Sensor Network

Abstract---Recent days in this world the population growth is rapidly increasing, so the world has number of aged people. These aged people are living lonely in home or old people home or retirement home and so on. The aged person have many diseases like memory loss, fits and etc., so that they cannot live independently in their home, if they need long life and precious independence they must stay in monitored environment. In this paper, we present the design and development of welfare facility for elders system which is based on wireless sensor network. Here we use sensors for monitoring aged people. If the sensor detecting any abnormality pattern in aged people, the system customary activity will automatically generate and send the text message or E-mail or both to the care giver and family members. Here we use Hidden Markov Model [HMM] for reducing data transmission time to care giver and family members. Also we design the database security which would provide more security to database in controller system. Here we use message digest algorithm [MD5] for providing security to database in controller side. Also display the monitoring status in web page that could take appropriate action by the person who notices it

A Hysteresis Band Based Vector Control of DFIG for Wind Energy Conversion Applications

ABSTRACT-In the recent days DFIG has been the most favorite option for wind power harnessing. Most research in the area of wind power generation system is based upon the control and performance improvement of the DFIG as a generator in variable speed wind energy systems. The slow and complex dynamics of the DFIG makes it a challenging task for high performance control structures. In this paper a DFIG based variable speed wind energy system is considered. A hysteresis current controller based stator flux oriented vector control scheme is implemented for the high performance control of the system. The control scheme relies upon two conventional PI controllers and three hysteresis band current controllers for the control purpose. The system is evaluated under different types of disturbances and the results are produced in this paper. KEYWORDS-Doubly-fed induction generator, Rotorside vector control, P-I controller. I. NOMENCLATURE II. INTRODUCTION Induction machines have served well as generators in wind energy conversion system for a long period of time. Initially for fixed speed wind energy conversion systems squirrel cage induction machines were employed as power generator for their rugged design, maintenance free performance and greater efficiency. But with the development of variable speed wind energy conversion systems the choice of generator has shifted towards doubly fed induction machines. Doubly fed induction machines inherit all the advantages of a cage induction generator but the fact due to which they are more popular are that the stator of the DFIG is connected directly to the grid and it supplies power from the stator side at grid voltage and frequency[1

Experimental investigation on corrosion resistant properties of copper based nanocomposite coatings

ABSTRACT-The corrosion resistant coatings used conventionally are having some limitations like degradation of the coatings and improper coatings which may lead to pitting corrosion. The nanocomposite corrosion resistant coating can overcome this problem. The SiO 2 nanoparticles are synthesized by ball milling process. The nanoparticles are mixed micron sized copper powder and converted into a composite. The composite materials are made into pellets using UTM. The pellets are used as targets to coat the mild steel substrate using sputtering process. SEM analysis indicated that the elements in the copper based nanocomposites are homogeneously distributed and agglomeration was observed. The SiO 2 and copper based nanocomposites are characterized using AFM, XRD and SEM. The corrosion resistance of nanocomposite coatings is tested using weight loss method and electrochemical method