Antidiabetic and antihyperlipidemic effects of Dillenia indica (L.) leaves extract

The present study was carried out to evaluate antidiabetic and antihyperlipidemic effects of Dillenia indica methanolic leaves extracts in streptozotocin induced diabetic Wistar rats by administering graded oral doses (250 and 500 mg/kg body weight) for 21 days. The extract showed significant antidiabetic activity (pRealizou-se o presente estudo para avaliar os efeitos antidiabético e anti-hiperlipidêmico de extratos metanólicos de folhas de Dillenia indica em ratos wistar com diabetes induzido por estreptozotocina por meio da administração de doses orais (250 e 500 mg/kg de peso corporal) por 21 dias. O extrato mostrou atividade antidiabética significativa (

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Weed flora dynamics and growth response of green gram (Vigna radiata (L.) R. Wilczek) under varied agri-horti system and weed management practices

Horizontal expansion of pulse production can be achieved by introduction of short duration pulse crop like, green gram (Vigna radiata (L.) R. Wilczek) under agri-horti system. Response of green gram under different agri-horti system and weed management practices is lacking. Therefore, an agronomic trial was conducted during monsoon season of 2011 at Agricultural Research Farm, Rajeev Gandhi South Campus, Banaras Hindu University, Barkachha, Mirzapur, Uttar Pradesh, in split plot design, consisting of three agri-horti systems [guava, custard apple and open field] in main plots and six weed management practices [pendimethalin 1000 g/ha (PE), imazethapyr 125 and 200 g/ha (PoE), 1-HW (20 DAS), 2-HW (15 and 30 DAS) and weedy check] were assigned to sub plots and replicated thrice. Green gram variety ‘Samrat’ was sown as per standard agronomic package of practices on August 5, 2011 in open field as well as within the alleys of, 5-year old, guava and custard apple agri-horti system. Agri-horti systems, did not significantly (P<0.05) affect the growth, yield attributes, yield and nutrient content in green gram. The weed management practices significantly affected the CGR, RGR and yield of green gram. Application of imazethapyr 200 g/ha recorded 79.08% reduction in weed biomass and 11.38% lower seed yield as compared to weedy check and 2-HW (15 and 30 DAS), respectively. 2-hand weeding effectively reduced weed biomass (88.07%) and showed highest yield (888.79 kg/ha), and CGR (13.61 g/day) followed by imazethapyr 200g/ha yield (787.66 kg/ha) and CGR (13.14 g/day)

A New Hand Based Biometric Modality & An Automated Authentication System

With increased adoption of smartphones, security has become important like never before. Smartphones store confidential information and carry out sensitive financial transactions. Biometric sensors such as fingerprint scanners are built in to smartphones to cater to security concerns. However, due to limited size of smartphone, miniaturised sensors are used to capture the biometric data from the user. Other hand based biometric modalities like hand veins and finger veins need specialised thermal/IR sensors which add to the overall cost of the system. In this paper, we introduce a new hand based biometric modality called Fistprint.  Fistprints can be captured using digital camera available in any smartphone. In this work, our contributions are: i) we propose a new non-touch and non-invasive hand based biometric modality called fistprint. Fistprint contains many distinctive elements such as fist shape, fist size, fingers shape and size, knuckles, finger nails, palm crease/wrinkle lines etc. ii) Prepare fistprint DB for the first time. We collected fistprint information of twenty individuals - both males and females aged from 23 years to 45 years of age. Four images of each hand fist (total 160 images) were taken for this purpose. iii) Propose Fistprint Automatic Authentication SysTem (FAAST). iv) Implement FAAST system on Samsung Galaxy smartphone running Android and server side on a windows machine and validate the effectiveness of the proposed modality. The experimental results show the effectiveness of fistprint as a biometric with GAR of 97.5 % at 1.0% FAR

Behavioral biometric based personal authentication in feature phones

The usage of mobile phones has increased multifold in the recent decades mostly because of its utility in most of the aspects of daily life, such as communications, entertainment, and financial transactions. Feature phones are generally the keyboard based or lower version of touch based mobile phones, mostly targeted for efficient calling and messaging. In comparison to smart phones, feature phones have no provision of a biometrics system for the user access. The literature, have shown very less attempts in designing a biometrics system which could be most suitable to the low-cost feature phones. A biometric system utilizes the features and attributes based on the physiological or behavioral properties of the individual. In this research, we explore the usefulness of keystroke dynamics for feature phones which offers an efficient and versatile biometric framework. In our research, we have suggested an approach to incorporate the user’s typing patterns to enhance the security in the feature phone. We have applied k-nearest neighbors (k-NN) with fuzzy logic and achieved the equal error rate (EER) 1.88% to get the better accuracy. The experiments are performed with 25 users on Samsung On7 Pro C3590. On comparison, our proposed technique is competitive with almost all the other techniques available in the literature

A SOLUTION TO SELECTIVE FORWARD ATTACK IN WIRELESS SENSOR NETWORK

Purpose of Study: Wireless mesh network represents a solution to provide wireless connectivity. There are some attacks on wireless sensor networks like black hole attack, sinkhole attack, Sybil attack, selective forwarding, etc. In this paper, we will concentrate on a selective forwarding attack. Selective Forwarding Attack is one of the many security threats in wireless sensor networks that can degrade network performance. An adversary on the transmission path selectively drops the packet. The adversary same time transfers the packet, while on a few occasions it drops the packet. It is difficult to detect this type of attack since the packet loss may be due to unreliable wireless communication. The proposed scheme is based on the trust value of each node. During data transmission, a node selects a downstream node that has the highest trust value, which is updated dynamically based on the number of packets a node has forwarded and dropped. Methodology: A comparative methodology is used in all existing schemes. We compared our scheme with the existing scheme and found that the packet loss in the proposed scheme is much less than the existing scheme. Result: We showed that our scheme essentially detects malicious nodes for each possible scenario. Regarding communication overhead, our scheme is more efficient than typical multipath schemes. Also, by utilizing an existing routing protocol which is secure against sinkhole attacks, our scheme also provides security against sinkhole attacks