bluuebunny/crossref_metadata_2025 huggingface dataset:
A survey on energy efficiency in mobile ad hoc networks
Authors: Shirly Geofrin , Kumar N
Published: May 2018

A mobile ad-hoc network is a collection of wireless mobile nodes which temporarily forms a network without any type of centralized administration which is already in use. In adhoc network, the battery lifetime of the mobile nodes is less. If suppose any nodes battery power is drained it leads to spreading of many divisions in the networks. Hence these spreader nodes are the very important spot in this network. For the purpose of data forwarding some very important nodes can drain their battery power in advance because of increase in load and processing for forwarding the data. Because of the variance in loads developed, the network of nodes will be collapsed very badly, the route lifetime will be reduced, network will be partitioned and route reliability is reduced in MANETs. Because of this, the most important criteria which have to be improved is the consumption of energy in mobile ad-hoc networks. The very important technique is power aware routing technique in MANETs. Hence minimization of energy in the network of mobile nodes individually can be done by using some of the routing techniques. The most important thing is to study the power aware protocol in order to help the new research doers and application developers to find a new idea for designing more efficient routing protocols.
Classification performance assessment in side scan sonar image while underwater target object recognition using random forest classifier and support vector machine
Authors: Kumudham R , Rajendran V , . .
Published: May 2018

Ocean mine have been a major threat to the safety of vessels and human lives for many years. Identification of mine-like objects is a pressing need for military, and other ocean meets. In mine, countermeasures operations, sonar equipment are utilised to detect and classify mine- like objects if their sonar signatures are similar to known signatures of mines. The classification of underwater mines is an important  task,  for  the  safety of  ports,  harbors  and  the  open  sea.  Mine detection is needed in military applications because it has been a threat to many lives and vessels. Although the task of finding mine like objects has received recent attention, very little has been published on the problem of discriminating mine-like (target) objects (MLO) and non-mine like (target) objects of similar size and shape. This paper deals with the recognition of mine like and non mine like objects. The recognition is done through robust Random Forest technique.
IOT connected predictive vehicle systems
Authors: . Murugadass , Sheela Gowr P , Latha M , V. Anbazhagu U
Published: May 2018

Predictive maintenance is to identify vehicle maintenance issues before they occur. By leveraging data from navigation locator and motion of vehicle, status and parts of the vehicle, requirement of service, warranty repairs with current vehicle sensor data would be difficult for a human to discover. Predictive data analytics can find meaningful correlations via Connected Vehicle which is a technological advancement in Automobile industry. Using Internet of Things IOT, various information like health information of a driving person and navigation of vehicle can be easily monitored. Connected vehicle deals with cars and other vehicles where we the data will be shared with the backed applications like micro services.
A genetic algorithm approach for global routing of VLSI circuits
Authors: Ravikumar D , Raaza Arun , Devi V , Gopinathan E
Published: May 2018

Very Large Scale Integrating (VLSI) design has the objectives of producing the layout for integrating circuits. The currently prevalent submicron regions require innovative, new physical design algorithms. Performance requirements have not seen before, become the significant features of such regions. The last ten years have been witnessing the feature of swelling success of Genetic Algorithms in their application to VLSI physical design. These algorithms are in spot light and the subject matter of study and examination. Routing problem is posed to a cost function which takes care of the total net length, the channel capacity exceedance and crosstalk. The Genetic algorithm is used for optimizing the cost function.
Correlation analysis of community detection in social network of big data methodical using set theorem
Authors: M. Monica K , Parvathi R
Published: May 2018

A trending issue in the network system that aids in learning and understanding the overall network structure is the community detection in the social network. Actually, they are the dividing wall which divides the node of the network into several subgroups. While dividing, the nodes within the subgroups will get connected densely but, their connections will be sparser between the subgroups. The ultimate objective of the community detection method is to divide the network into dense regions of the graph. But, in general, those regions will correlate with close related entities which can be then said that it is belonging to a community. It is defined based on the principle that the pair of nodes will be connected only if they belong to the same community and if they don’t share the communities, they are less likely to be connected. The vital problems across various research fields like the detection of minute and scattered communities have been necessitated with the ever growing variety of the social networks. The problem of community detection over the time has been recognized with the literature survey and the proposal methodology of set theorem to find the communities detection where the group belongs to activities. In addition to this, several basic concepts are stated in an exhaustive way where the research fields arise from social networks.
A study on reliability of Manets using trust management system
Authors: Bindu G , Karthika R.A. , Sridevi S
Published: May 2018

Mobile Adhoc Networks is a network where nodes keep moving geographically and doesn’t have an infrastructure. This network is a challenging when interactions are critical to attain system goals like reliability, configurability, capability to increase the size of networks, rapid changes in topology of network, this effects the new nodes entering the network easily to attack. This makes difficult to maintain Trust management in the MANET. To overcome this, few algorithms are developed for Trust management. In this paper we discussed the different types of MANET, Applications, protocols and Trust management schemes. We tried to derive the trust management from different fields.
Comparison and detail study of attacks and detection methods for wireless sensor network
Authors: Karthik Krishnan T , Sridevi S , Bindu G , Anandan R
Published: May 2018

Wireless sensor network is emanating technology in the field of telecommunications. WSNs can be applied in many fields like machine surveillance, precision agriculture, home automation and intelligent building environments. However the major aspect of WSN is the security as the sensor nodes are limited because of these facing several security threats such as black hole attack, worm hole attack, flooding etc. which is finally affecting the functioning of the whole network. These attacks are maximizing the consumption of power in the node and also it decreases life of the battery. In this paper, we discuss several types of security attacks in wireless sensor networks and also it introduces various intrusion detection systems to detect these attacks and prevent the compromised nodes in the WSN. And also we discuss about the different intrusion detection methods with the help of machine learning algorithms. In future these techniques can be helpful to create a safe and sophisticated network.
Side scan sonar image data mapping with geographic reference system
Authors: Kumudham R , Rajendran V
Published: May 2018

Many researchers have been done in classifying the surface of the sea floor. Only few concentrated in classifying the sediment layers of the sea floor and the target objects buried. Side Scan Sonar is one such tool, which is used in collecting the images of the seafloor. Sonar equipment transmits a low frequency signal, towards the surface of the seabed for target recognition. It is necessary to locate the area and positioning where the target is located whether it is a ship wreckage or plane crash, mine recognition etc. This paper is proposed to determine the location and position in user friendly matlab software environment, where the sonar image data is collected and is mapped with Global Reference System.
Modified classic apriori algorithm for association rule mining
Authors: Anitha G , A. Karthika R , Bindu G , V. Sriramakrishnan G
Published: May 2018

In today’s real world environment, information is the most critical element in all aspects of the life. It can be used to perform analysis and it helps to make decision making. But due to large collection of information the analysis and extraction of such useful information is tedious process which will create a major problem. In data mining, Association rules states about associations among the entities of known and unknown group and extracting hidden patterns in the data. Apriori algorithm is used for association rule mining. In this paper, due to limitations in rule condition, the algorithm was extended as new modified classic apriori algorithm which fulfills user stated minimum support and confidence constraints.
Effective processing of unstructured data using python in Hadoop map reduce
Authors: Kousalya K , Javed Parvez Shaik
Published: May 2018

In present scenario, the growing data are naturally unstructured. In this case to handle the wide range of data, is difficult. The proposed paper is to process the unstructured text data effectively in Hadoop map reduce using Python. Apache Hadoop is an open source platform and it widely uses Map Reduce framework. Map Reduce is popular and effective for processing the unstructured data in parallel manner.  There are two stages in map reduce, namely transform and repository. Here the input splits into small blocks and worker node process individual blocks in parallel. This map reduce generally is based on java. While Hadoop Streaming allows writing mapper and reducer in other languages like Python. In this paper, we are going to show an alternative way of processing the growing unstructured content data by using python. We will also compare the performance between java based and non-java based programs.
Building micro service for user engagement
Authors: Sharma Devansh , Anandan R , Manikandan A , Narayanan Kumar , Swaraj Paul C
Published: May 2018

The emails that are being sent today are done manually through the use of email providers like Gmail, Yahoo, Hotmail etc. with a copy paste mechanism of the same message. This requires more human resource and time. The system now being developed will be able to send the emails to thousands number of user without any copy-paste mechanism in very less time and with great accuracy handling all errors, if occurs, through the use of Amazon web services & Google Cloud services. Thus, the messages received by every user will be unique instead of the same message being sent to all. The email micro service will be responsible for handling out all the essential needs, verification & validation, automation, clean code and follows a proper SDLC as per current industry standards. The track ability feature will also be provided to track all the emails that are being sent to the users. Thus, the automation will be done and will save a lot of human resource and time.
Web image re-ranking using query specific in cloud computing
Authors: V. Anbazhagu U , Balakrishna R , Sajeev Ram A , Latha M
Published: May 2018

Question answering (QA) allows all users to get information in enhanced technique. In this project we suggest a system for inspiring textual answer with appropriate media data. Our system consists of three components Interpretation median picking, Inquiry propagation, Data pick and Launching. Interpretation median picking is used to select various types of answers. Inquiry propagation is used for extracting the root words from the given query. Data pick and Launching is used for selecting the appropriate answer and producing the result. We use Stemming algorithm, Naïve Bayes classifier algorithm and page ranking algorithms. Stemming algorithm is used to extract the root word from the given searched query. Naïve Bayes classifier algorithm is used for selecting the type of medium. By using the page ranking algorithm the optimal solution is got. Our approach automatically determines which media will be a best solution for the given query. It automatically harvests the data from website for getting the answer. Our approach can enable a novel multimedia question answering (MMQA) approach as users can find multimedia answers by matching their questions with those in the pool. We are enhancing community contributed answers. Any user who is unaware of data can get the information promptly. Our approach is to deal with the complex questions in an effective way. Based on the generated queries, we vertically collect image and video data with multimedia search engines.
An effective approach for video condensation by ribbon carving
Authors: Latha M , V. Anbazhagu U , . .
Published: May 2018

The proposed system aims in developing a method to stream video based on time intervals. Regular or irregular sub-sampling is not sufficient for scaling of video in time. Seam carving has been used where an Image can be resized either by inserting or removing pixels. Ribbon carving is an extension of seam carving which resizes the video in temporal direction. The non-parametric kernel model used for background subtraction has been replaced with temporal median filter. It enhances the processing speed and memory allocation has been more efficient, thus reducing the time of video without loss of data.
Smart grids investigation and analysis in terms of cost benefits
Authors: Rubini B , Shanmugasundaram N , Pradeepkumar S
Published: May 2018

Currently, different advanced technologies are implemented in power networks, with aim to improve power quality and reliability of grid operation. Naturally, Distribution Automation and Management Systems (DAMS), Smart power equipment, Advanced Metering Structure, Distributed Energy Resources and/or systems Demand Response are implemented in electricity distribution networks. Smart Grid Solutions coordinate different advanced technologies in an efficient energy management system. Outline Smart Grid Solutions, with investments of estimation, possible benefits and operation costs, is presented in this article, with estimation of cost-effectiveness in a lifetime of particular systems.
Factors influencing short-term solvency in Indian automobile industry
Authors: Abey Joji , Velmurugan R
Published: May 2018

The automobile industry in India occupies a vital role in the economic progress of the nation. The reputation of any industry depends on its liquid position, which helps a company in settling their dues in time. Liquidity denotes to the firm’s capacity to pay their outstanding dues. The article considers liquidity position of automobile industry by employing correlation and regression test. The data required for the study is secondary in nature. The required data are collected from Capitaline database for the period ranging between 2008 and 2017. The collected data is analyzed by making use of correlation and regression. The result reveals that liquidity position of a company depends on age, inventory turnover ratio, dividend payout ratio and leverage.
Analysis of diabetic retinopathy using naive bayes classifier technique
Authors: Sudha V , Karthikeyan C
Published: May 2018

The vital issues of diabetes are Diabetic retinopathy (DR) and Retinal Vascular Disease which leads to the blindness. The DR disease may be detected by the early regular screening. and the automatic detection of this disease is a great solution and which is more reliable to identify the normality level in Fundus images (FI). The FI contains the texture discrimination capacity to differentiate the healthy images. The Data mining technique are used for identifying the retinal features of DR disease. The Data mining technique contains two stages. In first stage the features of DR disease extract from the Retinal Images (RI). The highlights for DR disease determination incorporate blood vessels, optic nerve, neural tissue, neuroretinal edge, optic plate size, thickness and change and which are removed by applying Data mining strategy. The result of the different information mining arrangement systems was looked at utilizing quick excavator apparatus. Gullible bayes and Support Vector Machine classifiers are utilized to anticipate the early discovery of eye disease diabetic retinopathy and observed that Naive bayes technique to be enhance the exactness of 89% precise.
Smart curiosity sinks node prediction mining algorithm for path optimization in wireless sensor network
Authors: Kannagi A
Published: May 2018

As of late, data miming and handling for wireless sensor systems (WSNs) have turned into a theme of dynamic research in a few fields of software engineering, for example, the circulated frameworks, the database frameworks, and the data mining. Managing the large amounts of information and efficiently using this information in improved path optimization has become increasingly challenging. In this paper, we will demonstrate how sink node predicted and integrated for path relationships and patterns in linked data, i.e., the interdependencies between data items at the lowest elemental level. The problem of path optimization has been approached using various techniques. The path selection plays the vital role in achieving the quality of service parameter and secure communication. Considering multiple routing, the security can be enforced with various strategies. Using few parameters namely the congestion, delay and hop count would support improve the performance of the network as well as lifetime. With the motivation, an efficient smart curiosity sink node prediction mining algorithm has been presented in this paper. First, both the source and destination nodes maintain information about the routes and network conditions. Based on that a single efficient path has been selected for data transmission. On the other side, the receiver verifies the path being followed, the route available and their conditions. Using this information the delay approximation is performed to decide the legitimate of the path being selected and the traffic incur in the way. The proposed method identifies several network threats and detects the presence of the node in the route. The proposed plan improves the performance of mining data efficiency as well as increases the throughput.
Analysis of multi server Markovian queue with functioning vacation and intolerance of customer
Authors: Shanmugasundaram S , Murugesan R
Published: May 2018

In this article, we analyze the operating behavior of two server Markovian queueing model with functioning vacation and infinite population. If the server is halt his service suddenly in a normal busy period and repair work is done immediately and service starts. The server failure and repair rates are follow exponential distribution, when the system become vacation the server takes functioning during this period the customer wait in the queue and server serves the customer with the lower service rate. The steady state behavior is also obtained, the various performance measures are also determined. The numerical example is given to test the feasibility of the model.
An efficient software verification using multi-layered software verification tool
Authors: V. Gayetri Devi S , Nalini C , Kumar N
Published: May 2018

Rapid advancements in Software Verification and Validation have been critical in the wide development of tools and techniques to identify potential Concurrent bugs and hence verify the software correctness. A concurrent program has multiple processes and shared objects. Each process is a sequential program and they use the shared objects for communication for completion of a task. The primary objective of this survey is retrospective review of different tools and methods used for the verification of real-time concurrent software. This paper describes the proposed tool ‘F-JAVA’ for multithreaded Java codebases in contrast with existing ‘FRAMA-C’ platform, which is dedicated to real-time concurrent C software analysis. The proposed system is comprised of three layers, namely Programming rules generation stage, Verification stage with Particle Swarm Optimization (PSO) algorithm, and Performance measurement stage. It aims to address some of the challenges in the verification process such as larger programs, long execution times, and false alarms or bugs, and platform independent code verification
Contrast Enhancement of Grayscale and Color images using Adaptive Techniques
Authors: A A Mariena , G.R Sathiaseelan J
Published: May 2018

Contrast enhancement is an emerging research area in digital image processing domain. It is an important factor in any subjective evaluation of image quality in medical image processing. As there are possibilities for degradation of image quality during the acquisition, there arises the need of an efficient contrast enhancement technique that can remove the redundant pixels from the images prior to final processing. In this paper, we have proposed two adaptive approaches for contrast enhancement. The first approach is used for enhancing grayscale image using mathematical morphology and second approach is for color image using enhanced sigmoid function. The enhancement process of grayscale image was evaluated by using PSNR and that of color image was evaluated by using a factor called measure of contrast. The experimental results indicate that the two proposed methods show better performance for image in grayscale as well as in color.
Machine Learning for High Risk Pregnancies Pre-Term Birth Prediction: A Retrospective
Authors: Ramla M , Sangeetha S , Nickolas S
Published: May 2018

Any birth before 28 weeks of gestation is termed as Pre-Term. This has substantial impact in the emotional reactions of mothers. The post-traumatic stress notably in the mother could be of chronic psychological risk. Moreover, it is to be addressed in the global scenario for sustainable development. Predicting stillbirths is still a distant reality. A plethora of works have been carried out and this paper present the summaries and analysis of current research. The primary focus of the paper is to throw light on the challenging issue of Preterm Birth Prediction. Myriad of machine learning techniques are used by various researchers each with its own estimation accuracy and type of ML model.
Effective lossy and lossless color image compression with Multilayer Perceptron
Authors: PL. Chithra Dr , Christoper Tamilmathi A
Published: May 2018

This paper presents the effective lossy and lossless color image compression algorithm with Multilayer perceptron. The parallel structure of neural network and the concept of image compression combined to yield a better reconstructed image with constant bit rate and less computation complexity. Original color image component has been divided into 8x8 blocks. The discrete cosine transform (DCT) applied on each block for lossy compression or discrete wavelet transform (DWT) applied for lossless image compression. The output coefficient values have been normalized by using mod function. These normalized vectors have been passed to Multilayer Perceptron (MLP). This proposed method implements the Back propagation neural network (BPNN) which is suitable for compression process with less convergence time. Performance of the proposed compression work is evaluated based on three ways. First one compared the performance of lossy and lossless compression with BPNN. Second one, evaluated based on different sized hidden layers and proved that increased neurons in hidden layer has been preserved the brightness of an image. Third, the evaluation based on three different types of activation function and the result shows that each function has its own merit. Proposed algorithm has been competed with existing JPEG color compression algorithm based on PSNR measurement. Resultant value denotes that the proposed method well performed to produce the better reconstructed image with PSNR value approximately increased by 21.62%.
Tri-Chrominance Texture Pattern: A New Feature Descriptor
Authors: I.Jeena Jacob Dr , K.G.Srinivasagan Dr , S. Gomathi Dr , Joyce Beryl Princess Ms , P.Betty Ms , P.Ebby Darney Mr
Published: May 2018

Feature extraction plays a vital role in the information management system. This paper proposes Tri-Chrominance Texture Pattern (TCTP), a feature descriptor for extracting the features from images. This pattern helps to extract the inter-channel chrominance relationship, along with texture information of the image. The analysis were done in a natural image dataset, Corel database (DB1), pure colored texture database, Colored Brodaz Texture database (DB2) and a biometric dataset, Indian Face Image database (DB3). The proposed work outperforms the existing works in all the datasets. The analysis on DB1 shows significant improvement over the previous works like Local Binary Pattern (LBP) (78.64%/57.35%), Local Tetra Pattern (LTrP) (79.84%/56.8%) and Local Oppugnant Color Texture Pattern (LOCTP) (82.64%/58%) as 83.25%/58.2% in terms of Average Precision/ Average Recall. The analysis made in the Colored Brodaz database (DB1) shows the result of TCTP as improved from LBP (91.75%/75.18%), LTrP (91.64%/76%) and LOCTP (99.21%/89.38%) to (99.8%/93.47%).  The Average Recognition Rate (ARR) of face recognition in DB3 database using the proposed work shows considerable improvement from LBP (78.2%), LTrP (91.9%) and LOCTP (89.1%) as 88.5%. The computational complexity of the proposed work is much lesser than LTrP and LOCTP.
A Game Theory Approach for Efficient Node Clustering Based on Unstable Ranging Transmission in MANET
Authors: Preethi Author R , R. Anbuselvi Author Dr
Published: May 2018

In Mobile Ad Hoc Network (MANET), improving scalability, energy efficiency and network lifetime are the most important and challenging issues. Node Clustering is a well known solution for handling these issues. While existing work focused on stable transmission range, this paper uses unstable ranges transmission for clustering nodes in network. Game theory has been used in fields of science such as economics and biology, but recently it was used in MANET for clustering problem. Grouping mobile nodes into convenient clusters can reduce routing overhead and provide more scalable solution. The main objective of this work is to clustering of nodes in MANET and selects energy efficient cluster head to improve the network lifetime using game theoretical model. This paper proposes an efficient algorithm for Node Clustering based on Unstable Ranging Transmission (NCURT). In addition to this, a game theory based cluster head (CH) selection algorithm is proposed to selects CH based on Evolutionary game theory approach where each node behaves selfish or unselfish based on the strategy selection. Analytical and simulation studies are carried out to assess the performance of the proposed cluster formation and cluster head selection algorithm. The numerical results verify that the proposed approach is effective and efficient to guarantee life time and energy efficiency in MANET.
A multivariate Gaussian modeling for counting bananas
Authors: M Senthilarasi , T M Navarasy , Kumar C Ram , Mansoor Roomi Mohamed
Published: May 2018

Agriculture industries play an important role in economic development. Many post harvest techniques are performed in these industries. Especially in fruit industries, grading is an important process. As per the grading standard, banana hands must have minimum of twelve banana fingers. In the current scenario, the banana fingers are counted manually which is laborious. In order to reduce manual work, this paper proposes an algorithm for performing an automatic counting system of banana fingers in a bunch/hand using image processing algorithms. The parameters of the Gaussian model is acquired from the samples of fruit distal ends. A multivariate Gaussian modeling is accomplished on HSV color model to detect the distal end of banana fingers using maximum likelihood detection.
Partially Occluded Face Recognition using Dynamic Time Wrapping
Authors: Kumar Ashish , Shanmugavadivu P
Published: May 2018

It is evident that the research contributions in the domain of partially occluded image are quite sparse. This paper presents a novel method, termed as Partially Occluded Face Recognition (POFR) using Maximally Stable External Regions (MSER) feature sets and Dynamic Time Wrapping (DTW). This proposed system works in two phases: Phase-I, creates an annotated database using the non-occluded images, and Phase-II focuses on the detection and recognition of partially occluded probe image, which is also annotated using the mechanism of phase-I. Hence, POFR selectively and dynamically calibrates the annotated database as per the annotation of the probe image. Further, the similarity between the feature sets of the annotated database images and the probe image is computed, using the principle of DTW. The POFR is tested on the face images from University of Stirling dataset and the average accuracy of face recognition is recorded as 88%. This method promises a computational advantage for partially occluded face recognition without any prior reconstruction or synthesis. The POFR finds direct applications in surveillance and security systems.
State model based face mask detection
Authors: M Kavitha , Mansoor Roomi S Mohamed , Priya K , Devi K Bavithra
Published: May 2018

The Automatic Teller Machine plays an important role in the modern economic society. ATM centers are located in remote central which are at high risk due to the increasing crime rate and robbery.These ATM centers assist with surveillance techniques to provide protection. Even after installing the surveillance mechanism, the robbers fool the security system by hiding their face using mask/helmet. Henceforth, an automatic mask detection algorithm is required to, alert when the ATM is at risk. In this work, the Gaussian Mixture Model (GMM) is applied for foreground detection to extract the regions of interest (ROI) i.e. Human being. Face region is acquired from the foreground region through  the torso partitioning and applying Viola-Jones algorithm in this search space. Parts of the face such as Eye pair, Nose, and Mouth are extracted and a state model is developed to detect  mask.
Load Balancing Metric Based Routing Protocol for Low Power and Lossy Networks (lbRPL)
Authors: Sebastian A , Sivagurunathan S , . .
Published: May 2018

IETF ROLL working Group standardized the IPv6 Routing protocol (RPL) for applications over low-power and lossy networks (LLNs). RPL constructs a Destination Oriented Direction Acyclic Graph (DODAG) to organize network topology. RPL shows fast network setup and good scalability. However, it may suffer from load imbalance due to diverse network traffic and heavy load on preferred or forwarding parents. To optimize the load balancing of routes in RPL, this paper proposes load balancing metric based routing protocol called lbRPL. We introduce a new routing metric for RPL called load balancing index (LBI), which exploits load balancing characteristics of RPL nodes to select more load balanced parents and routes. LBI includes ETX, Parent count (Pc) and Remaining Parent Energy (Pe) metrics to make routing decisions. Simulation results show that lbRPL improves network performance, stability and improved network life time to RPL.
An enhanced constraint based technique for frequent itemset mining in transactional databases
Authors: Sivakumar Ramah , J.G.R. Sathiaseelan Dr
Published: May 2018

Mining frequent patterns is one of the wide area of research in recent times as it has numerous social applications.  Variety of frequent patterns finds usage in diverse applications and the research to mine those in an optimized way is an important aspect under consideration.  So far, many algorithms had been proposed for mining frequent itemsets and each has their own pros and cons.  The basic algorithms used in the process are Apriori, Fpgrowth and Eclat.  Many enhancements of these algorithms are ongoing process in recent times.  In this paper, an enhanced Varied Support Frequent Itemset (VSFIM) algorithm is proposed which is an enhancement of FPGrowth algorithm. Unique minimum support for each item in the transaction is provided and then mining is done in the proposed approach.   The performance of the proposed algorithm is tested with existing algorithms.  It is found that VSFIM outperformed the existing algorithms in both processing time and space utilization.
Skull Stripping Using Pixel Affinity Graph Method for MRI Head Scans
Authors: Shankar R.Siva , Somasundaram K.
Published: May 2018

Skull stripping from Magnetic Resonance Image (MRI) of human head scan gives strong impact in clinical diagnosis. The Pixel affinity graph method is used as preprocessing technique, and it is applied on adjacent pixels in each row and column of the middle slice of MRI volume. By grouping the subsets through affinity on intensity found in pixels on the graph (PAG), we can locate the large connected brain portion as subset in the image. After the region of interest is located, Skull is stripped and brain portion is segmented. The proposed PAG based algorithm is validated by comparing the results obtained by the popular automated skull stripping method, Brain Extraction Tool (BET). The qualitative and quantitative results show that the proposed algorithm giving better results.
RankTagViz: A Semantic Ranking and Tags Visualization of User Travelogues
Authors: Maheswari M. Uma , Sathiaseelan J.G.R.
Published: May 2018

The travelogues contain prosperous geo-referenced information such as tours, weather, and expenses etc. Reading travelogues and finding useful trip information is a tedious task for many people. So as to correlate the georeferenced text meaningfully the semantic ranking is taken in account on the user contributing travelogues. In this way there is a requirement for creating programmed travelogue mining methods to pass on valuable data in a travelogue to its peruses in the more successful way. Visualizing a geo-referenced data with location tags and descriptions makes it helpful for readers to understand the fundamental substance of the travelogue. For user expedient, this paper proposes a Travelogue RankTagViz approach that semantically ranks and visualizes the tags of user travelogues. The RankTagViz contains two phases. In the first phase, the user travelogues are ranked based on semantic. In the next phase, the travelogues are visualized based on the tag and images. During semantic ranking, a semantic dimension reduction method is proposed to pre-process and mine useful information from the travelogues. After that a semantic rank mechanism is proposed to rank travelogues based on tags and POI (Point Of Interest). For tag visualization, location based tags and images are extracted from the travelogues and a novel UI is intended to give a superior client encounter, by arranging both the literary and visual data produced by committed voyagers in an alluring way. Test comes about on an arrangement of gathered travelogues show the proposed techniques' capacity to rank and imagine travelogues.
Approach to analysis of technical -organizational system functioning on the base of semi-markov process theory
Authors: Gavrilin Aleksey , Gorbunova Tatiana , Tumanova Marina , Ratnikov Oleg
Published: May 2018

Relevance of the present task lays in optimization of control over complex systems considering probabilistic and temporal nature of their functioning. Allocated some generic States of the system's normal operation and consider destabilizing situations when the continued functioning of the element in the system becomes difficult, impossible. Including the status when it is necessary to conduct full diagnostic and restoring of the system with explicit damage which makes it impossible for the system to operate in the acceptable mode into the model is described in the work. The proposed solution to this task is based on the mathematical modelling. Considering the general case of nonexponential time of system residence in its own status, the proposed functioning model displays relations between system statuses and probable parameters of its functioning on the base of semi-Markov process theory. Because of this work the explanation of an adequate description of complex system functioning at probabilistic and temporal analysis was presented.
Prediction the wear of sliding bearings
Authors: Aleksandr Dykha , Dmitry Marchenko
Published: May 2018

The problem of developing a calculation-experimental method for calculating wear of a sliding bearing based on a two-factor wear model (contact pressure - sliding velocity) with identification of wear resistance parameters was considered. On the basis of the proposed wear model, the wear-contact problem for a cylindrical sliding bearing was solved. The equation of equilibrium for medium pressures and the approximating function of linear wear from the arc of contact between the shaft and the bushing were used as the determining equations. To identify parameters of wear resistance in the wear model, a calculation-experimental method for determining calculated dependences of wear resistance parameters was developed on the basis of the wear test by the «cone – three balls» scheme. The results of wear tests of bronze conical specimens with a variable wear spot and two values of sliding velocity were taken as a base. The obtained results were recommended for predicting wear of sliding bearings at the design stage and optimizing their design and operational parameters.
Analysis of modern modeling methods in problems of stabilization of motions of mechatronic systems with differential constraints
Authors: A.Ya Krasinskiy , E.M. Krasinskaya
Published: May 2018

The most important problem of controlling mechatronic systems is the development of methods for the fullest possible application of the properties of our own (without the application of controls) motions of the object for the optimal use of all available resources. The basis of this can be a non-linear mathematical model of the object, which allows to determine the degree of minimally necessary interference in the natural behavior of an object with the purpose of stable implementation of a given operating mode. The operating modes of the vast majority of modern mechatronic systems are realized due to the steady motions (equilibrium positions and stationary motions) of their mechanical components, and often these motions are constrained by connections of various kinds. The paper gives an analysis of methods for obtaining nonlinear mathematical models in stabilization problems of mechanical systems with differential holonomic and non-holonomic constraints.
Fungicidal and antibacterial activity of the hydrogel compositions with silver
Authors: V. Smagin A , V. Smagina M , B. Kolganihina G , B. Sadovnikova N , Y.Gulbe A , S. Bashina A
Published: May 2018

Contamination of the rhizosphere by pathogenic microorganisms is a universal soil-ecological problem leading to heavy losses in tuber and root crop yield of agricultural crops. Suppression of these microorganisms is possible because of special gel compositions with silver ions and nanoparticles as plant-protecting agents. An efficiency test of gel-silver inhibitors was carried out on two common pathogens, the causative agents of late blight (Oomycete Phytophthora infestans) and black leg of potato (Enterobacterium Pectobacterium atrosepticum). The study revealed an exponential relationship between  inhibitor dose and linear (by diameter) and nonlinear (by area) specific growth rates of colonies of microorganisms. According this model the EC50 values of the gel compositions varied from 1 to 86 ppm of the active substance (Ag) and were consistent with other research findings. The fungicidal effect was sufficiently  (3-30 times) lower for gel compositions based on ionic silver in comparison with colloidal forms; whereas bactericidal properties for both agents were similar.
Influence of lignosulfonic acids on the formation of magnetoactive compound in the redox reaction of iron(II) with chromate-anion
Authors: Yu. Kuzyakov Nikolay , A. Veshnyakov Viacheslav , G. Khabarov Yuriy , V. Pankina Galina
Published: May 2018

Chromium and its compounds are widely used in various industries. Wastewater from industrial enterprises using chromium compounds are subject to complete disposal at treatment facilities. The possibility of synthesizing a magnetoactive compound by oxidizing part of Fe(II) cations with chromate-anions in the presence of lignosulfonates was investigated. The magnetic activity was measured on Gouy balance, magnetic characteristics were determined by the magnetic granulometry method. It has been shown that the interaction of Fe(II) cations with chromate-anions passes with the formation of an water soluble intermediate without redox transformations at pH 3.4. Using method of the isomolar series, it was determined that the ratio of chromate-ions and Fe(II) cations in the intermediate is 1:2.33. The intermediate solution is stable for a long time. Synthesized magnetoactive compound samples are ferrimagnets. The use of lignosulfonate and the synthesis with heating can achieve a higher magnetic activity of magnetoactive compound. The optimal lignosulfonate consumption is 0.7 g/g Fe.
Numerical simulation of oil spills based on the GNOME and ADIOS
Authors: Elizaryev A , Maniakova G , Longobardi A , Elizareva E , Gabdulkhakov R , Nurutdinov A , Khakimov R
Published: May 2018

The Exxon Valdez oil spill emergency has shown that simulation of oil spills trajectory is the main action in planning response measures. Modeling the trajectory of the oil slick allows predicting in advance the direction of the motion of the stain, the time it will take to reach the shore and assess the possible environmental consequences for the contaminated coastal zone. In this paper, the Exxon Valdez oil spill trajectory was analyzed using two different models, the GNOME model and the HAZAT trajectory model. Conclusions are drawn about the reasons for the differences in the results provided by the two models. The accuracy of the simulation is strongly related to the input of geographic and meteorological data. In addition, ADIOS software was used to predict the weathering process of the modeled emergency event. It was found that the main factors influencing the change in the physical and chemical characteristics of oil dispersed in the water body are the wind speed and direction, water temperature and wave height.
The study of hydraulic hammer device in drilling tool assembly in hydraulical rotary drilling
Authors: I. Suleimanov R , S. Gabdrakhimov M , Ya. Khabibullin M , M. Zaripova L , R. Vasilyeva E
Published: May 2018

The article presents the study of a hydraulic hammer device for rotary well drilling. The mathematical model of the hydraulic hammer device has been described and studied, the relation of the dynamic load changes on the rock-destruction tool from the principal parameters of the hydraulic hammer device have been obtained. The trial rotary boring with the use of a hydraulic hammer device in drill tool assembly has been carried out, an increase in the drilling penetration rate has been achieved by 47%.
The research of clinker monominerals modified suspensions’ rheological properties
Authors: M M Kosukhin , I V Starostina , A M Kosukhin
Published: May 2018

The findings of studying the influence of the superplasticizers of various natures on rheological properties of clinker monominerals’ water suspensions have been presented. It has been shown that the plasticizing activity of admixtures is determined by the nature and the specific surface of a monomineral and the nature of the admixture’s hydrophilic groups, and for complex admixtures also with the ratio of individual components. The optimal admixture dosages for monomineral suspensions of clinker minerals change in the row C2S, C3S, C3A, C4AF, which allows forecasting the influence of admixtures on rheological properties of systems with cements of various mineral compositions. The obtained data correlate with the research findings of the admixtures’ influence on cements of various mineral composition, which allows deducing the influence of admixtures on the systems with other cements, and providing the economically and technologically feasible selection and consumption of admixtures depending on the type of cement and its mineral composition.
Reclamation of chemical wastes for the production of efficient concrete modifiers
Authors: M M Kosukhin , I V Starostina , A M Kosukhin
Published: May 2018

The research concerning the obtaining of highly-efficient polyfunctional superplasticizers for concretes on the basis of chemical production waste with the purpose of their reclamation and improving the environmental situation in the populated areas has been carried out. The highly-efficient concrete admixtures on the basis of various wastes have been synthesized and patented.  A new efficient modifier based on pyrocatechin production waste has been suggested. The colloid and chemical properties of the obtained modifier and its influence on physical, mechanical and maintenance-engineering characteristics of concrete have been researched. Its comparative evaluation with the known plasticizing admixtures has been presented. It has been demonstrated that the superplasticizer under study is the most efficient in terms of plasticizing activity and improving the physical and mechanical properties of concretes and concrete mixes and has a polyfunctional effect. Its application allows increasing the concrete mixes flowability and concrete strength, reducing the concrete consumption, providing the concrete with fungicidal properties, cutting the production costs and solving ecological problems of the chemical production waste recycling.
Research of the opportunity to use sludge wastes of ferrovanadium production as pigments for silicate paints
Authors: I V Starostina , M M Kosukhin , M M Simonov , Yu.L Starostina
Published: May 2018

The article considers the urgent problem of formation, storage and recycling of sludge materials of various compositions, generated as a result of industrial enterprises wastewater treatment and sanitation. It is pointed out that in spite of a lot of designs concerning the wastewater neutralization sludges recycling, the share of their efficient usage is still negligible. So, one of the most relevant trends of nature protection activity and the rational use of natural resources is developing a technology of these wastes reclamation and applying them for useful products manufacturing. The research of chemical, mineral and grain composition of ferrovanadium production sludge wastes, generated at waste waters neutralization at the «EVRAZ Vanadii Tula», Tula, Russia, has been carried out. A method of obtaining pigments for silicate paints on the basis of these sludges has been considered. The influence of the sludges' thermal treatment conditions on their mineral composition and the properties of paints based on them has been evaluated. The pigments content varies from 1 to 3 %. It has been demonstrated that the most promising is the usage of initial sludges and heat-treated at temperature 1000°С sludges as pigments for high-performance silicate paints.