Metal Leachability, Mechanical Properties And Surface Characterisation Of Ti6al4v Dental Implants

Implanted prosthetic devices have become an integral modality in restorative dentistry. Biological risk associated with ionic particles released from metallic implants are critical and very much sought after. This study is divided into in vitro and in vivo. The main objective of the study was to evaluate metal leaching from dental implants Ti6Al4V. Specifically, the in vitro part aimed to analyse metal leaching from dental implants in simulated body fluid (SBF) at different pH (3.0, 5.5, 6.5, 7.3,7.5 and 7.8) using inductively coupled plasma mass spectrometry (ICP-MS) with electrochemical corrosion and mechanical properties evaluation

An innovative simplified method for assessing available bone in mandible for implant

The primary factor that determines the success of implant is the amount of available bone in the edentulous site. Diagnostic imaging and techniques help to develop and implement a cohesive and comprehensive treatment plan according to the available bone. In the following case report an innovative simplified method (poor man CT) is used to fabricate a three dimensional model to assess the available bone for implant placement in mandible

A Prototype for a Multimodal Biometric Security system based on Face and Audio Signatures

Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systemsCochin University of Science and TechnologyInternational Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 143-14

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.Cochin University Of Science And Technolog

IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATOR

Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achievedCochin University of Science and TechnologyComputer Science & Information Technology (CS & IT

IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATOR

Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89 % and rejection rate of 95 % is achieved

Ultrasonic evaluation of influence of hard acrylic resin denture on blood flow of mandibular denture supporting mucosa utilizing duplex color Doppler studies: An in vivo study

Aims: To determine the influence of hard acrylic denture base materials on the blood flow of mandibular denture supporting mucosa over a period of six months time. Materials and Methods: Select fifteen edentulous patients of age 55-75 years. The blood flow of the mandibular denture supporting mucosa was measured bilaterally in the molar region and in the incisor region utilizing Ultrasound colour Doppler (2D and Duplex Imaging). Measurements were performed prior to denture insertion and later after the dentures were worn for 1 month, 2 months, 3 months, 4 months, 5 months and 6 months. Statistical analysis used: Mean blood flow as measured by Ultrasound colour Doppler were tabulated significant changes if any at various time interval in comparison to baseline was assessed by Kruskalwallis ANOVA test followed by Wilkoxan sign rank test for pairwise comparison.( In the present study, P < 0.05 was considered as the level of significance). Results: The denture supporting mucosa exhibited a progressive reduction in the blood flow both with hard denture. The blood flow change with hard denture was a reversible condition as the blood flow improved at the end of six months. Kruskalwallis ANOVA test revealed no significant change in the blood flow at any interval of time in comparison to base value (P = 0.133). Conclusions: Within the limitations of the study denture supporting mucosa exhibited a progressive reduction in the blood flow with hard denture which was reversible

A silicon neuron-based bio-front-end for ultra low power bio-monitoring at the edge

This paper presents the circuits for an edge-based bio-front-end implemented using an integrate-and-fire silicon neuron model in 22nm SOI CMOS Technology. The proposed implementation encodes both positive and negative input signals separately and, like its biological counterpart, provides asynchronous output. This asynchronous output allows for maximum sensitivity to high-information content input signals and low sensitivity for low-information content. In the proposed design, the firing rate can be controlled by an adaptation circuit to achieve maximum power savings. We demonstrate this design with a sinusoidal test signal and pre-recorded ECG signals. The proposed design achieves ultra-low-power consumption; by applying a sinusoidal input and ECG input the power consumption without adaptation (with adaptation) is 4.0698nW (3.999nW) and 5.1529nW (3.3118nW), respectively. In addition, the reconstruction of the ECG signal is demonstrated and the signal to error for the reconstructed ECG signal is 30.2 dB