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The Internet of things (IoT) is the network of different devices like sensors, actuators, and other different objects which have the capability to communicate without the need for human involvement. IoT mainly includes the devices which has low power and lossy networks (LLNs). These devices have limited resources like memory, energy, processing power, and bandwidth. These features leads the system in challenging environment which may end up in unstable state if proper security measures are not applied. IETF designed a protocol for routing mechanism of these devices known as routing protocol for low power and lossy networks (RPL). RPL is vulnerable to number of routing attacks and does not support mobility of nodes. This paper includes the study of different kind of threats possible on RPL. The proposed method for attack detection by using trust-based intrusion detection system considers trust value of participating nodes.

Information systems and computerization nowadays need very faster, secure & easier data analysis techniques. It is also required to maintain efficiency and accuracy in data analysis. So machine learning & Blockchain techniques have been continuously used in the data analysis & security in various fields from medicine to organization and education to energy applications. This study applies classification of machine learning & Blockchain techniques to process the data and survey of selection methods, query strategies, applications and security. In highly secure data, Security issues are solved by using Blockchain Technology.Blockchain technology is rapidly gaining attention towards the Security of confidential data. The healthcare industry is one of the fields of organization where high risk involves & its attracted attention of many technological organizations so this field required the security for securing their data. The Blockchain is generally used for providing the security to secure the high sensitive data. By using the Blockchain technology there are numerous opportunities for healthcare industry to achieve & gain. Such as reduced transaction costs, increased transparency for regulatory reporting, efficient healthcare data management and healthcare records universality as well as able to access data from any location. In the context of smart healthcare system blockchain may provide distinct benefits, particularly from a context-aware perspective where efficient and personalized solutions may be provided to citizens and the society. This paper provides a comprehensive survey of relationship between Machine learning and blockchain techniques related to smart healthcare system. In addition, we are going to discussed several challenges can comes for actually implementing machine learning secure healthcare system using blockchain based Technology.

This paper proposed closed loop control of nonlinear system connected inverter based on the optimal neural controller (ONC). The novelty of the proposed method rests on the hybrid technique which is the combined performance of both, particle swarm optimization (PSO) technique and Radial basis function neural network (RBFNN). It effectively optimizes the feasible solutions by updating the generations, by taking lesser time with greater reliability. In the proposed method, the PSO generates the dataset according to different loading conditions. The RBFNN is trained by using the target control signals along with the corresponding input load voltage error and change in error. Depending on the load variations, the RBFNN predicts the exact control signals of the inverter during the testing time. Since experimentation and comparison of such inverter models on hardware being relatively expensive, the proposed method is implemented in the MATLAB/Simulink platform and the performance has been validated through the comparison analysis with the conventional techniques. The comparison results have proved the superiority of the proposed method.

Standalone photovoltaic (PV) systems are implemented to perform independently from the utility grid. Such system are beneficial for certain AC as well as DC loads; that too especially where conventional energy cannot reach. To make such system more efficient and independent, a closed loop control could be employed. This research paper presents a novel approach to model and simulate a closed loop maximum peak power tracking (MPPT) based single phase stand alone system using particle swarm optimization (PSO) technique. Based on the simulation results, an experimental investigation has been successfully carried out.

Camera calibration is to identify a model that infers 3-D space measurements from 2-D image observations. In this paper, the nonlinear mapping model of the camera is approximated by a series of linear input–output models defined on a set of local regions called receptive fields. Camera calibration is thus a learning procedure to evolve the size and shape of every receptive field as well as parameters of the associated linear model. Since the learning procedure can also provide an approximation extent measurement for the linear model on each of the receptive fields, calibration model is consequently obtained from a fusion framework integrated with all linear models weighted by their corresponding approximation measurements. Since each camera model is composed of several receptive fields, it is feasible to unitedly calibrate multiple cameras simultaneously. The 3-D measurements of a multicamera vision system are produced from a weighted regression fusion on all receptive fields of cameras. Thanks to the fusion strategy, the resultant calibration model of a multi-camera system is expected to have higher accuracy than either of them. Moreover, the calibration model is very efficient to be updated whenever one or more cameras in the multi-camera vision system need to be activated or deactivated to adapt to variable sensing requirements at different stages of task fulfillment. We studied the Simulation proposed by Jianbo Su in this paper and we are trying to implement his proposed model. Sachin Agrawal Student Prof. Ram Meghe Institute of Tech & Research Badnera S.A.Bhura Student Prof. Ram Meghe Institute of Tech & Research Badnera The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org

XML is a widely adopted technology in various domains ranging from web services to messaging systems, databases grid and scientific computing. However the processing of XML documents is an expensive operation that can degrade performance and limits the adoption of XML for specific applications. As different applications incorporating XML have come to the fore it becomes imperative to conduct a comprehensive study of the issues involved in design of parser. Hence optimizing parser performance has become a research hotspot. This paper focuses on a detailed study of the optimization parameters and design and implementation of a novel parser NXParse while optimizing for character streams, in-place parsing, string transformation control-flow, data structures and recurrent structures. Our empirical analysis shows that the NXParse gives a better parsing performance.

Content-based search and retrieval techniques for multimedia content utilize various descriptors for different image features. However, most content-based image retrieval systems use low-level visual features for representation and retrieval of images. The color content, being one of the easily computable features is often used in contentbased search for retrieving images in large image databases. The paper presents a simple and fast technique for image indexing and retrieval based on a description of the spatial distribution of dominant colors. The idea in this study is to empirically evaluate the effect of color features to the query. Furthermore, some similarity measures are defined that allow the definition of effective visual queries for fast interactive image database browsing applications. We use the image histograms to characterize the global and local color properties of an image and to preserve its intrinsic geometric information. The color feature is probably the most visible visual feature for the most humans. This is the new approach in the image organization and retrieval of image, in image databases. Our approach combines the representation of the color as the global image feature and the color as the representation of the spatial information in the images.

Verbal arithmetic's is a class of constraint satisfaction problems which includes making mathematical relations between meaningful words using simple arithmetic operators like '+' in a way that the result is conceptually true, and assigning digits to the letters of these words and generating numbers in order to make correct arithmetic operations as well. In this puzzle, arithmetic operations are simple and of base ten, but are ciphered into letters. A simple way to solve such problems is by depth first search (DFS) algorithm which has a big search space even for quite small problems. DFS is an algorithm for searching a tree, tree structure. Thus going deeper and deeper until a goal node is found. The paper illustrates the design and implementation of parallel genetic algorithm that can find the solution more quickly taking less memory.

During oxidative stress, the reactive oxygen species (ROS) generally produce structural and biochemical alterations in cells and cell organelles. Impairment of lysosomal and mitochondrial function is the key for understanding the degenerative changes due to aging. Nonspecific esterase enzyme is particularly present in lysosomes and microsomes. In order to find the antioxidant property of fenugreek, non-specific esterase activity was measured to study the lysosomal membrane integrity in submandibular and sublingual salivary glands of D-galactose-induced aging male mice without and with supplementation of fenugreek. Adult male albino mice ( Mus musculus ) were divided in to six groups of five each and treated as follows: a) control for D-galactose (Dg) treatment; b) Dgtreated; c) Dg + fenugreek seed extract (FSE) treated concurrently; d) treated with Dg first, followed by treatment of FSE; e) Dg + FSE-loaded PLGA nanoparticle treated concurrently; and f) treated with Dg first followed by treatment of FSE-loaded PLGA nanoparticle. A significant decrease in non-specific esterase activity was observed in D-galactose treated mice, whereas FSE and FSE-PGLA groups of mice indicated protection against Dg-induced aging related oxidative stress in salivary glands. Thus, it is shown that fenugreek seed possesses antioxidant property, whereby non-specific esterase activity in salivary glands is increased but in a manner dependent on the treatment pattern, and the best result is obtained when FSE is administered post-treatment as loaded in PGLA nanoparticles.

We report a two and a half year old child who presented with an acute abdomen two days after a spoon was forcefully inserted per rectum. The child recovered after repair of the rectal tear and a temporary sigmoid colostomy.