Attacking a smartphone biometric fingerprint system:a novice’s approach

Biometric systems on mobile devices are an increasingly ubiquitous method for identity verification. The majority of contemporary devices have an embedded fingerprint sensor which may be used for a variety of transactions including unlock a device or sanction a payment. In this study we explore how easy it is to successfully attack a fingerprint system using a fake finger manufactured from commonly available materials. Importantly our attackers were novices to producing the fingers and were also constrained by time. Our study shows the relative ease that modern devices can be attacked and the material combinations that lead to these attacks

Tongue Examination in ‘Gunmam’ (Acid Peptic Disease)

In the OPD of NIS, the patients who reported with the condition of Gunmam were included in the study as elucidated by Sage Yugi in his treatise Yugi Vaithiya Chinthamani – 800’. This study was undertaken in order to validate the body constitution, diagnosis and prognosis by using tongue examination among the Gunmam patients. The study results reveal the strong association between the symptoms of organs namely stomach and intestine and the Pitham zone (95%) of the tongue which is affected predominantly than the other zones. By examining the tongue, Pitha Vatham constitution of tongue had higher incidence, all the patients had vitiated Vatham humour. Tongue shows up with unique patterns which are sign to diagnose diseases. It does not vary with age, culture and race. So, screening of the tongue throws light on causes of the illness, hence by using the screening technique practitioner can diagnosis the disease wisely as early as possible. In all Gunmam patients, cracking (100%) in tongue is the most common feature which is seen in Pitham zone that indicate the vitiated Vatham in Pitham zone which infers that the disease is of Vatham nature but manifests itself in the Pitham region of the body. Hence the study reveals, “தொடர் வாத பந்தமலாது குன்மம் வராது” -தேரையர். This study paves a way for proper line of treatment and diagnostic method of simple tongue inspection which can be adopted as a cost - effective tool for finding various systemic and local diseases

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Not AvailableIn e-learning, learning object sequencing is a challenging task. It is difficult to sequence learning objects manually due to their abundant availability and the numerous combinations possible. An adaptive e-learning system that offers a personalized learning path would enhance the academic performance of learners. The main challenge in providing a personalized learning path is finding the right match between individual characteristics and learning content sequences. This paper presents a collaborative optimization algorithm, combining ant colony optimization and a genetic algorithm to provide learners with a personalized learning path. The proposed algorithm utilizes the stochastic nature of ant colony optimization and exploration characteristics of the genetic algorithm to build an optimal solution. Performance of the proposed algorithm has been assessed by conducting qualitative and quantitative experiments. This study establishes that the hybrid approach provides a better solution than the traditional approach. (C) 2019 Elsevier Ltd. All rights reserved.Not Availabl

Automatic Respiratory Disease Detection and Classification from Lung Images : A Detailed Review

The image based automatic detection and classification of respiratory diseases has a large and complex range of solutions that span both computer vision and medical imaging literature. This has been driven by a range of powerful recent developments in deep learning, transformers, and new founding models, and these have significantly improved performances across a range of benchmarks. We provide a comprehensive review of these approaches, comparing and contrasting them in terms of performance, generalization, trading data requirements, and computational costs for both training and inference. Our review maps to the key processes found in the literature namely dataset and benchmark development and curation, data finetuning, segmentation, feature Extraction, localization, object detection masking, and classification of diseases. This will help locate the existing problems in each phase and efficiently find solutions. It will give an overview of recent advancements and potential future directions. This review article could be used as a quick guide by fellow researchers to get a detailed view of the problem domain and plan their contributions

Gastroretentive drug delivery system of levofloxacin hemihydrate: Development and evaluation of mucoadhesive microspheres for the treatment of H. pylori infection

The aim of the studies to formulate and develop mucoadhesive microcapsules of levofloxacin hemihydrates by using the mucoadhesive polymers for the treatment of H. pylori infection. Methods: Microspheres were prepared by Ionotropic gelation technique. To achieve the mucoadhesive and extended release property in this study, sodium alginate, chitosan and calcium chloride for formulating levofloxacin hemihydrate microcapsules. In vitro drug release and in-vitro mucoadhesiveness. Results: To achieve the mucoadhesive and extended release property in this study, mucoadhesive polymer, such as chitosan was used. Sodium dioctyl sulphosuccinate (DOSS) used as surfactant. The percentage yield for levofloxacin hemihydrate loaded microspheres was found to be in the range of 32.11±1.25% to 87.28±1.67%. Drug content of the levofloxacin hemihydrate loaded microspheres varied from 20.21±1.01% to 30.77±1.88%. The encapsulation efficiency of the prepared microspheres varied from 51.77±1.33% to 78.54±1.55%. The mean diameter of levofloxacin hemihydrate loaded microspheres were found to be in the range of 135.5±3.64 μm to 448.59±5.44μm Mucoadhesive property of the prepared microspheres varied from 45.81±1.32% to 82.97±0.82%. A significant decrease in the rate and extent of drug release was observed with the increase in sodium alginate concentration in beads.&nbsp