Colon Cancer Detection by using Transfer Learning

Cancer detection at early stage will provide the chance of existence of living. Using image processing techniques medical image analysis becoming easier and exact stage of cancer is also detected. In this work transfer learning technique is used to identify the Colon Cancer

Modelling Accessibility based on Urbanization using Artificial Neural Networks (ANN)

The present study involves modelling the accessibility index with respect to the traffic volume, Right of Way width and Population density. It also involves the collection of number of different types of opportunities like schools, hospitals, ATMs, bus-stops and parks to determine the accessibility index. Two different methods are used in the study such as Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) to develop models in order to predict the accessibility index. Based on the R2 value obtained in the models, it is observed that ANN has better prediction capability than MLR model. The study acts as a guide to the urban transportation planners to understand the change in accessibility index when there is a change in urbanization variables

Differential genotypical expression of a NEDD9 in normal and tumor tissues: a possible pharmacological target

Background: Neural precursor cell expressed developmentally down regulated-9 (NEDD9) is a scaffolding metastatic marker protein in multiple cancer types. Generally, the expression occurs during the embryonic development and depletes in adults. Expression of NEDD9 in adults leads to the progression of tumor which is sufficient for the cellular invasion. Elevated behavior of the gene mediates metastatic movement which includes protease dependent neovessel formation, invasion and migration of tumor cells from the site of origin to the distant tissues.Methods: The current study involves the screening and elucidation of differential expression of NEDD9 in normal and tumor subtypes with various tissues of mice by immunohistochemistry.Results: The validating approaches in the study, low expression of NEDD9 was observed in the normal tissues and predominance in the tumor subsets.Conclusions: The experimental analysis proven that NEDD9 expression is merely associated with tumor progression and the molecular mechanism of NEDD9 is restricted in the establishment of metastatic cascade. NEDD9 association in tumor prognosis which helps in the emergence of diagnostic and therapeutic approaches

OVERVIEW ON DEPLETION ATTACKS HINDERING NETWORK EFFICIENCY

Traditional works on secure routing attempts to make sure those adversaries cannot make discovering of path for returning an unacceptable network path. In our work, we define Vampire attacks, which denote a novel class of resource consumption attacks that utilize routing protocols to block ad hoc networks by means of reduction of nodes’ battery power. Vampire attacks are most general attacks of resource depletion where the energy which is consumed by network for composing and transmitting a message is superior when evaluated to that of an ordinary network. Our work considers of attack-resistant minimal-energy routing, where adversary objective includes lessening energy savings. Vampire attacks are not specific to protocol, and do not depend on design properties of routing protocols, however rather make use of general properties of protocol classes. These attacks neither depend on flooding the network with huge amounts of data; however try to transmit as little data as promising to attain major energy drain, avoiding a rate limiting explanation. Vampire attacks interrupts functioning of a network instantly rather than work overtime to completely stop a network. These types of attacks are not dependant on exact protocols but to certain extent expose vulnerabilities in several accepted protocol classes

DESIGNING A PVC FOR DC-COMPONENT

The electricity component is really a special issue in transformer less grid-connected solar (PV) inverter systems and could cause problems regarding system operation and safety. IEEE standard has defined the limit for electricity component within the grid-side ac power. The electricity component can cause line-frequency power ripple, electricity-link current ripple, along with a further second-order harmonic within the ac current. This paper has suggested a highly effective means to fix minimize the electricity component in three-phase ac power and created a software-based approach to imitate the obstructing capacitors employed for the electricity component minimization, the so-known as virtual capacitor. The suggested method continues to be validated on a ten-kVA experimental prototype, in which the electricity current has been effectively attenuated to become within .5% from the ranked current. The entire harmonic distortion and also the second-order harmonic have been reduced along with the electricity-link current ripple. The “virtual capacitor” is accomplished with the addition of an important from the electricity component in the present feedback path. A technique for accurate extraction ofthe electricity component according to no time at all integral, like a answer to achieve the control, continues to be devised and approved effective even under grid-frequency variation and harmonic conditions. A proportional integral-resonant controller is further made to regulate the dc and line-frequency component in the present loop to supply precise control from the electricity current

Statistical relationship between date of sowing and the sorghum shootfly (Atherigona Soccata, Rondani L)

The present study was based on the available data of eleven years for shoot fly from 2000-2010 for kharif season. Different models viz., linear and non linear were tried to fit, Amongst, the linear, quadratic and cubic models produced better coefficient of determination and the models viz., EGG(Shoot fly Egg) =3.760+0.196(DOS) (R2 =0.892) and EGG(Shoot fly Egg) =1.077+1.195(DOS)-0.087(DOS^2), which produced highest R2 (0.896 at p=0.05) with less standard error (0.419) and quadratic model was also the best fit model in determining the oviposition of shoot fly, which explained 89.6 per cent variation in the oviposition of shoot fly for the 7 days after emergence of the sorghum crop. For the dead heart development (14 DAE), the model %DH (% Dead Heart) =3.535+3.104(DOS) found best fit with highest coefficient of determination of 0. 856 and exhibited significant positive relationship with the date of sowing and during 21 DAE the cubic model %DH (% Dead Heart) =10.619+10.115(DOS)-3.466(DOS^2)+0 .321(DOS ^3) had significant coefficient of determination value of 0.988 with least standard error 0.885. The quadratic model during the 28 days after emergence of the crop %DH (% Dead Heart) =-6.234+22.858(DOS) -1.399 (DOS^2) found best fit and produced significant R2 (0.929 at 5 per cent level) and showed better relationship with the date of sowing. It was found that, both linear and non linear relationship exists between dates of sowing and shoot fly of sorghum during kharif season

Prediction of Chronic Kidney Disease using SVM and CNN

Chronic kidney disease is one of the deadliest diseases today and it is vital to have a good diagnosis as soon as possible. In medical treatment, machine learning has been reported to be effective. A doctor can diagnose the disease early by using machine learning classifier algorithms. This study investigated the chronic disease prognosis of this concept. Disease data was taken from the University of California, Irvine. Other measurement algorithms used in this study include C5.0, Chi-square automatic interaction detector, line extraction, SVM line with L1 and L2 flap, and neural network random tree. The database was also submitted to a feature selection program that merited the database. Scores are computer generated for each category segment using the following methods: Full Version, (ii) Link-Based Feature Selection, (iii) Folder Feature Selection, (iv) Minimal Collapse and Selected Optional Retrospective Features, (v) integrated small oversampling method with very small reduction features and selected bias on the selected operator, and (vi) how to do multiple samples combined with full functions. In the full multi-sample processing process, the findings show that L2-loaded LSVM has a very high accuracy of 96.86 percent. The graph shows the results of different methods, as well as precision, precision, recall, F-score, area under the curve, and GINI coefficient. The minimum absolute reduction and selection regression operation selected features using the synthetic minority oversampling approach produced the best results after using the synthetic minority oversampling method with full features. The support vector machine achieved a high accuracy of 96.46 percent in the process of making very large samples with very small turndowns and selected operator features. Machine learning methods used with convolutional neural networks and SVM classifier models on the same database, with 96.7 percent of high-definition support machine models and networks are used

Morphometric differentiation of hermit crabs, superfamily: Paguroidea from Mumbai, North-West coast of India

492-495The present communication deals with an attempt to differentiate species of hermit crabs, collected from Maharashtra region, using morphometric features. A total of 16 morphometric measurements features were recorded from each specimen. The morphometric features like cheliped dactylus length, cheliped propodus length, carapace length, ocular peduncle length, antennular peduncle length and propodal length have been found to be important traits in the separation of the species. Among these first three, cheliped dactylus length, cheliped propodus length and carapace length, are most important in differentiation. The analysis also indicated 99.55 % correct discrimination of the species based on selected traits

Development and validation of new analytical method for the simultaneous estimation of ibuprofen and diphenhydramine in bulk and pharmaceutical dosage form by RP-HPLC

A simple, accurate, rapid and precise method was developed for the simultaneous estimation of Ibuprofen and Diphenhydramine in Pharmaceutical dosage form. Chromatogram was run through Inertsil ODS (250x4.6mm) 5µ. Mobile phase used was Acetonitrile and Phosphate buffer (45:55) at a flow rate of 1.0 ml/min and detection wavelength was found to be 260 nm. The retention time was found to be 2.32 min and 2.93 min for Ibuprofen and Diphenhydramine respectively. The accuracy and reliability of the method was assessed by evaluation of linearity, precision (intra-day and inter-day % RSD >2), accuracy (98-102%), specificity, LOD, LOQ values in accordance with ICH guidelines. The developed method is applicable for routine quality control analysis of selected combined dosage forms

Web Platform for Interconnecting Body Sensors and Improving Health Care

The Internet of Things (IoT) is a paradigm in which smart objects actively collaborate among them and with other physical and virtual objects available in the Web in order to perform high-level tasks for the benefit of end-users. In the e-health scenario, these communicating smart objects can be body sensors that enable a continuous real-time monitoring of vital signs of patients. Data produced by such sensors can be used for several purposes and by different actors, such as doctors, patients, relatives, and health care centers, in order to provide remote assistance to users. However, major challenges arise mainly in terms of the interoperabil- ity among several heterogeneous devices from a variety of manufacturers. In this context, we introduce Eco Health (Ecosystem of Health Care Devices), a Web middleware platform for connecting doctors and patients using attached body sensors, thus aiming to provide improved health monitoring and diagnosis for patients. This platform is able to integrate information obtained from heterogeneous sensors in order to provide mechanisms to monitor, process, visualize, store, and send notifications regarding patients’ conditions and vital signs at real-time by using Internet standards. In this paper, we present blueprints of our proposal to Eco Health and its logical architecture and implementation, as well as an e-health motivational scenario where such a platform would be useful