Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhance Fair Routing with Resources Flexible Node Allocation for WSN

: Wireless sensor network is a network composed of a large number of sensor nodes with limited radio capabilities and one or a few sinks that collect data from sensor nodes. Sensor nodes are powered by small batteries, hence, the energy consumption in operating a WSN should be as low as possible. In this project existing system analysis the heterogeneity of networks and a fair cooperative routing method, to avoid unfair improvement only on certain networks. In this project introduce one or a few shared nodes that can use multiple channels to relay data packets. The sinks and shared nodes can communicate with any WSNs node, different WSNs can use cooperative routing with each other since shared nodes allow sensor nodes to forward data from another WSN as the function of interchange points among respective WSN planes. When receiving a packet, a shared node selects the route to send the packet, according to proposed route selection methods. This cooperation prolongs the lifetime of each network equally as possible.
A System for Large-Scale Graph Processing on the Concept of Map-Reduce and MRBG

A time-line based framework for topic MapReduce programming model is widely used for large scale and one-time data intensive distributed computing, but lacks flexibility and efficiency of processing small incremental data. Incremental Mapreduce framework is proposed for incrementally processing new data of a large data set, which takes state as implicit input and combines it with new data. Map tasks are created according to new splits instead of entire splits while reduce tasks fetch their inputs including the state and the intermediate results of new map tasks from Preserved and latest generated result. The preserved states really producing the promising result and significantly reduce the run time for refreshing big data mining results compared to re-calculating on both simple and multi stage MapReduce. The intermediate states are saved in the form of kv-pair level data and data dependence in a MapReduce computation as a bipartite graph, called MRBGraph. A MRBG-Store is designed to preserve the fine-grain states in the MRBGraph and support efficient queries to retrieve fine-grain states for incremental processing.
An Efficient Approach for 3D Face Recognition Using ANN Based Classifiers

: The area of Face recognition is largely being encompassed by the application of soft computing tools. In this paper, neural network based three different classification algorithms have been used for a comparative evaluation purpose of randomly taken 3D facial images as a local dataset. The recognition rates have been calculated using LDA technique and compared using SOM, SVM, and Backpropagation algorithm. All the three classification methods differ based on their learning paradigms, as the first one is an unsupervised learning approach and the latter two are supervised learning based classifiers. Through this paper, results have been calculated to serve the purpose of determining a most prominent of the ANN based main classifiers used for efficient 3D Face recognition system.
AN EFFICIENT ANTI PHISHING FRAMEWORK BASED ON DYNAMIC CAPTCHA

Web security has become a serious and challenging issue due to the growth of Internet, due to this drastic growth Cyber-attacks has been increasing day by day. Phishing (attempt to obtain sensitive information such as user names, passwords, and credit card details from unsuspecting victims for identity theft, financial gain and other fraudulent activities) is one of the most popular attack. Hackers design fake websites which appear very identical to the original ones are being hosted to achieve this. In this paper a new approach called “Anti-phishing framework based on visual cryptography “is introduced to solve phishing problems. Using Visual Cryptography, we will be able to use image for authentication. Visual cryptography (VC) schemes hide the secret image into two or more images called shares. Here the shares are shared with the user and database. The secret image will be recovered simply by stacking the shares together without any complex computation. The original image captcha can be revealed without any complex computation only when both shares are simultaneously available; the individual sheet images do not reveal the original image captcha. Once the original image captcha is revealed to the user that can be used as the password. Using this method the website cross verifies its identity and proves that it is a genuine website before the end users.
Authentication Aura to Secure Graphical Password: The Case of Android Unlock Pattern

: Multi-Level Lock Application: Privacy Manager using Android Techniques is a concept of Android Application development using which device’s security is provided to all the Android users. The term Multi-level means multiple level of security (Type of lock) out of which any one can be activated according to user’s choice. Android is a forefront adaptable stage that was planned to be extremely open. Android applications make use of bleeding edge gear and programming, and also adjacent and served data, revealed through the phase to pass on progression and motivating force to buyers. Also there is default inbuilt security system that is provided by Android itself such as Pin password, Pattern password, picture password, etc. These all types of security passwords are very good in their work that is to protect the valuable data of customer. The First level is Touch Pattern, in this level user will select one or several points in some particular manner as a password. In Second level there is Pin password which is also derived from existing application but the algorithm behind this is way more different than that. In this password we use some digits as a password and certain indexes for all those digits given by the user.
Implementation and Performance Analysis of Convolutional Encoder and Viterbi Decoder Using Matlab

— During the transmission of data over channel, the data gets affected by the noise, which leads in reducing the effectiveness of system. To obtain the effective output, error detection and correction technique is achieved using error control codes providing Forward Error Correction technique which plays an important role in wireless networking facilitating the effective communication, thereby limiting the noise. The paper illustrates the convolution encoding with the decoding based on Viterbi algorithm. The performance of the code is analysed in terms of Bit Error Rate in comparison with the un-coded data. The complexity of the decoder increases with the increase in constraint length. The simulation was performed using BPSK modulation scheme in symmetric Additive White Gaussian Noise channel in MATLAB.
H.P. Acthar® Gel in Dermatomyositis and Polymyositis Treatment Registry: An Interim Analysis

Introduction: Therapies for dermatomyositis and polymyositis (DM/PM) include corticosteroids, immunosuppressants, and intravenous immunoglobulin (IVIg). A high proportion of patients with DM/PM are refractory to therapy. H.P. Acthar® Gel, repository corticotropin injection (RCI) is a potential anti-inflammatory treatment. Methods: Patients enrolled in the Acthar in Dermatomyositis and Polymyositis Treatment registry were monitored for changes in the clinical parameters of DM/PM after initiation of RCI twice weekly in doses up to 80 IU per subcutaneous injection. Results: RCI treatment effectively altered the clinical course of DM/PM in 14 of 24 patients. Positive responses to treatment were associated with disease activity at baseline and duration of treatment. Mild to moderate adverse events were reported. Conclusions: This is the largest observational study of RCI in treatment of DM/PM to date and results indicate that RCI may be an effective, tolerable treatment for refractory patients. Controlled studies are necessary to identify any additional associations between disease state and response to RCI treatment.
Diagnostic Status of Stool for Occult Blood in Predicting the Development of Necrotising Enterocolitis

Stool for occult blood is a frequently ordered test and a common finding in neonatal intensive care unit (NICU). To determine the incidence of occult hematochezia and its diagnostic status in predicting the development of necrotising enterocolitis (NEC) a prospective study was conducted at a tertiary level referral nursery.
Relationship between Statins Adverse Events and Pharmacokinetic Variables

There are no doubts that statins together with steroids, antibiotics and diuretics are among the most important drugs of the last two centuries. Despite the improvement of the life expectancy, statins have to be used carefully to avoid any misuse that could bring the patients from the benefit to the risk of damaging side effects [1,2]. Statins (hydroxymethyl-glutaryl coenzyme A reductase inhibitors or HMG-CoA reductase inhibitors) are characterized by different potency [3] which is reflected by the daily dosage, ranging between 2mg (pitavastatin) and 80mg (fluvastatin), with intermediate dosages of 10, 20 and 40mg respectively for atorvastatin, simvastatin, and lovastatin. Abstract
Moving Vehicle Segmentation Based on EM Algorithm And Fast Motion Estimation Algorithms

Moving vehicles segmentation is an interesting yet difficult problem in intelligent transportation system. Ordinary segmentation method is obstructed by some problems: the moving objects in dynamic scenes are the examples. Bayesian framework is utilized to classify the motion in the scenes to improve the robustness of the model and EM algorithm is used to estimate the parameters of the model. The direction and magnitude of the motion vectors are the inputs to the Bayesian rule and EM algorithm. In existing methods traditional Exhaustive search method is used for finding the motion vector. Computational cost of the Exhaustive search method is high. In this paper we are using some fast algorithms like Three Step Search and Four Step Search algorithms for reducing the computational cost. Experimental results on the scene,’ waving trees’, shows that the proposed model can segment the moving vehicles correctly with less computational cost. Quantitative evaluations demonstrate that the proposed method outperform the existing methods.
The Role of Web Content Mining and Web Usage Mining in Improving Search Result Delivery

- In today’s e-world search engines play a vital role in retrieving and organizing relevant data for various purposes. However, in the real ground relevance of results produced by search engines are still debatable because it returns enormous amount of irrelevant and redundant results. Providing relevant information to user is the primary goal of the website owner. Web mining is ample and powerful research area in which retrieval of relevant information from the web resources in a faster and better manner. Web content mining improves the searching process and provides relevant information by eliminating the redundant and irrelevant contents. However for a broad-topic and ambiguous query, different users may have different search goals when they submit it to a search engine. Web usage mining plays an important role in inferring user search goals as they can be very useful in improving search engine relevance and user experience. The paper focuses on combine approach of web usage mining and web content mining.
Int. J. Biosci

Amaranthus spinosus (spiny amaranth) natively live in America, Africa, Australia, Europe and Asia. This plant can be used as medicinal plant and also as food or feed. A. spinosus has phenotypic variation, especially in leave and stem type. It is because of plant adaptation. Plant adaptations impact to variation on morphological and genetic. Chloroplast DNA (cpDNA) is a common molecular marker that used in the genetic variability analyses. Phenotypic variation was analyzed using morphological and molecular data. The trnL intron, matK and rbcL genes were amplified and sequenced. The sequence data analyses using MEGA5, Bioedit and DNAsp software’s. The molecular data shown that A. spinosus from tropical zone was higher genetic variability then temperate zone. Plant in the tropical zone easy to be colonized and there isn’t gene flow barrier. So that, A. spinosus that adapt to different habitat have different morphological character and have higher genetic variability. * Corresponding Author: Arik Arubil Fatinah  arik.arubil@gmail.com International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print) 2222-5234 (Online) http://www.innspub. net Vol. 3, No. 11, p. 205-212, 2013
Makeover of MDA Meta-Models in OWL

stract: Web Ontology Language (OWL) & Model Driven Architectures (MDA) have common issues. In this paper, our main concern is to facilitate MDA standard in ontological engineering. In the approach we are taking, one may understand the relation of ODM and MDA-four layered architecture, which will also define the important concept of OWL. Further, we will describe mapping techniques between MDA and OWL. To introduce OWL in context of MDA, we will define ontology language in terms of MDA standards. In addition the MDA based ontological architecture will be implemented. So we can say, this is a formal approach to bring closer MDA-based ontology languages and the OWL recommendations using the idea of technological spaces.
Secure Communication and Privacy Protection Using VANET

: All drivers have an awareness of finding route to the particular destination within a short period. In present scenario, thiscanbeachieved by using Global positioning system (GPS). It determines the current location and alsohelps in finding the route between the source and the destination. At present the drivers comes to know about the traffic and alsoweather conditions in the form of FM radio data system whichtransmits the information collectedfrom Traffic Message Channel. In recentdays, Vehicular ad hoc Network (VANET) isbecoming more popular in many places. VANET is an important element of Intelligent Transportation Source (ITS). VANET is a network whichallows the vehicles to broadcast the safety messages to nearbyvehicles. For using VANET in vehicles, On-Board unit shouldbeplaced in the vehicle and Road Side Unit (RSU) along the highways. The main source of communication between RSU and OBU isdedicated short range communication (DSRC) protocol. This communication isdone over the wirelesschannel. In thispaper, we propose the real time conditions gathered by the VANET to instruct the drivers to reach the destination in particular time. To prevent hacking and tracing, the source isgiven by the confidentialcredential to provideprivacy of the drivers whichisunlinkableeven by the trustedauthority. Herewe use AODV protocol to improve the efficiency of vehicle to vehicle communication.
Energy Efficient MAC Protocol (D-MAC) for Wireless Sensor Network

Energy efficient protocol outline the design of MAC layer protocols that employ adaptive duty cycle as means of further optimizing the energy conservation. In this paper we concern for Medium Access Control (MAC) protocols the recent technology that is used in the Wireless sensor networks are appealing to researchers to achieve an efficient medium access protocol subject to power constraints. D-MAC protocol design methodology and results projected at self-learning, traffic adaptive algorithm for varying traffic conditions inherent to the WSNs. The design incorporates reliable and scalable energy-aware sensing network, in spite of node failures, minimizing energy consumption at the same time. This is a survey & proposed design work based on adaptive D-MAC protocol dynamic sleep schedules to reduce the control overhead, traffic adaptive wakeup and low latency. This protocol is to be simulated in java for future works.
A Review on the use of Augmented Reality to Generate Safety Awareness and Enhance Emergency Response

Augmented reality applications annotate real world with computer generated graphics. They make the surrounding environment interactive by overlaying digital 3D models or some plain text information over and around the tangible objects in its radius. Augmented reality finds its uses in many diverse fields; one such field is discussed in this paper: Safety. This review paper has conducted a study on various existing augmented reality systems that have been successful in implementing a way to provide the user with the knowledge pertaining to safety practices or parting knowledge to the user when it comes to learning how to react in case of emergencies. The ARLIST project (F. Pretto et al, 2008) focused on enhancing Life Support training by projecting audio and visual content on manikins in an attempt to provide a realistic scenario for the trainees. To generate safety awareness in an earthquake prone country-Japan; an augmented furniture falling simulation was implemented by generating 3D furniture models onto strategically placed markers in real environment. An in-car augmented reality system was designed for averting possible collisions with surrounding environment and pedestrians and A computer-vision based tracking method was used to realise an augmented reality application that could enhance the safety for jobs involving physical danger (like construction jobs) backed by a method of information presentation. The paper concludes with establishing the need for a comprehensive system that incorporates both safety awareness and safety training instead of just one of these pair of features.
A Novel Framework for Authentication in Social Networks Based on Trustees

— Authenticating users with the help of their friends has been shown to be a promising backup authentication mechanism. A user in this system is associated with a few trustees that were selected from the user’s friends. When the user wants to regain access to the account, the service provider sends different verification codes to the user’s trustees. The user must obtain at least k verification codes from the trustees before being directed to reset his or her password. In this paper, we provide the first systematic study about the security of trustee based social authentications. In particular, we first introduce a novel framework of attacks, which we call forest fire attacks. In these attacks, an attacker initially obtains a small number of compromised users, and then the attacker iteratively attacks the rest of users by exploiting trustee-based social authentications. Then, we construct a probabilistic model to formalize the threats of forest fire attacks and their costs for attackers. Moreover, we introduce various defense strategies. Finally, we apply our framework to extensively evaluate various concrete attack and defense strategies using three real-world social network datasets. Our results have strong implications for the design of more secure trustee-based social authentications.
Facing the Challenges of Female Obesity During Midlife: Social Inequality, Weight Control, and Stigma in Clinically Overweight and Obese Women

The increasing burden of chronic disease in ageing populations has shifted focus towards illness prevention and the self-management of health. Middle-aged and menopausal women’s transitioning bodies, specifically with respect to weight gain and changes in body fat composition, have received much attention by public health officials during the alleged obesity epidemic. In addition to these transformations, socioeconomic status has been shown to interact with obesity by decreasing the psychosocial health of vulnerable women. Although public health actions have targeted the health practices of clinically obese women throughout the menopausal transition, their effectiveness is limited because of existing socioeconomic inequalities, narrow focus on body weight interventions, and the psychosocial impact of an obesity stigma. Drawing on Bourdieu’s sociocultural theory of practice, and namely his concepts of body habitus and symbolic violence, this study aims: (a) to identify the norms and values of clinically overweight and obese postmenopausal women from contrasting socioeconomic backgrounds with regard to the ways they treat and care for their body, and (b) to outline the sociocultural processes which incline them (or not) to pursue weight-loss strategies. Forty semi-structured interviews were conducted with clinically overweight and obese postmenopausal women from underprivileged (n=20) and middle class (n=20) milieus in the city of Sherbrooke, Québec. An intersectional (gender, age, socioeconomic status) thematic analysis was employed in order to analyze the data and identify emergent themes within and between both socioeconomic groups.
A Novel Transformer-less Four Phase Buck Converter with Low Voltage Stress and Automatic Current Sharing

An Interleaved high step-down conversion ratio buck converter with closed loop control for low switch voltage stress. In this converter two input capacitors are seriescharged by the input voltage and parallel discharged by a new four phase IBC (Interleaved Buck Converter) for providing a much higher step-down conversion ratio without adopting an extreme short duty cycle. Based on the capacitive voltage division, the main objectives of the new voltage-divider circuit in the converter are both storing energy in the blocking capacitors for increasing the step-down conversion ratio and reducing voltage stresses of active switches. As a result, the converter possesses the low switch voltage stress characteristic. Moreover, due to the charge balance of the blocking capacitor, the converter features automatic uniform current sharing characteristic of the interleaved phases without adding extra circuitry or complex control methods. Closed loop simulation using PI controller of the new IBC converter is done with 400 V DC input and 500 W output power .
COMPARATIVE INVESTIGATION OF INTELLECTUAL SYSTEM OF HOUSES BASED ON ISLAMIC-IRANIAN MODEL AND PASSIVE DEFENSE

Islamic-Iranian architecture with its regional characteristics and scientific components is considered among sustainable architectures of all time. Passive defense as one of the most important solutions is proposed for sustainability and maximum utilization of architecture capacity. In this study, the relationship between IslamicIranian architecture in Iranian houses and passive defense has been taken into consideration. The research method was library research method and descriptive and analytic.
Lung Diseases Using Deep Learning: A Review Paper

- The detection of abnormalities in the early stage is challenging and it aims to play a vital role in automated screening systems. Medical imaging modalities are used to probe the human body. Feature extraction is the most important step in image classification. It helps in extracting the feature of an images ideals possible. Feature extraction techniques are applied to get the feature that will be useful in classifying and recognizing the images. The proposed method have competitive results with comparatively shorter training time and better accuracy. The classifier are combined with the powerful feature extraction tool and principal components analysis and the evaluation of the performance is quite good over all the performance measures. The texture and shape features are estimate from the segmented region of interest