bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the factors that prevent adherence to treatment in patients with diabetes mellitus and the strategies that contribute to the improvement in adherence
Authors: Likhodey Natalia V. , Kalashnikova Marina F. , Likhodey Elena M. , Fadeyev Valentin V.
Published: March 2018

This review examined the current problem of low adherence to treatment in patients with chronic diseases, particularly type 2 diabetes mellitus. According to the definition of the World Health Organization, adherence to treatment is the degree to which a patients behaviour corresponds to the doctors recommendations with respect to medications and implementation of dietary advice and/or lifestyle changes. The current medical literature includes a large number of scientific publications devoted to the study of various factors that lead to low adherence to treatment. The term barriers is most often used to designate these factors. The first part of this work contains an analysis of the main factors that impede compliance to the doctors recommendations, such as socioeconomic and psychological (personal) barriers related to the disease itself, the peculiarities of its treatment and the organisation of medical care (the health care system).
The second part of this review examines the different theoretical models of patient behaviour and strategies that improve adherence to treatment. Most researchers believe that there is an unsatisfactory (low) adherence to treatment and that none of the existing intervention strategies can improve adherence to treatment among all patients. The cornerstone of the entire diabetes management system is the training of patients within the framework of developed structured programmes. Conversely,, success depends on the individual approach, the course of the disease and the mandatory consideration of the individual psychological characteristics of each person. Establishment of a partnership built on trust between a doctor and a patient contributes to greater patient satisfaction with treatment and improved adherence, and this relationship ultimately affects the treatment efficacy and clinical outcomes.
Possibilities of metabolic surgery for the treatment of type 2 diabetes mellitus in patients with grade 1 alimentary obesity
Authors: Salukhov Vladimir V. , Ilinskii Nikita S. , Vasil'ev Evgenii V. , Sardinov Ruslan T. , Gladyshev Dmitrii V.
Published: March 2018

Many studies have demonstrated the high effectiveness of bariatric surgery in patients with grade 23 obesity and type 2 diabetes mellitus. Currently, surgery is one of the most effective ways to decrease body mass, to maintain long-term weight loss and to manage type 2 diabetes mellitus. Particular interest has been generated by the strong influence of bariatric surgical interventions on the disruption of carbohydrate metabolism in patients who undergo surgery. This change leads to an improvement in the course of type 2 diabetes mellitus as well as its full remission. This review presents information on the mechanisms that are needed to improve glycaemic control in patients with obesity even after bariatric surgery. This review also contains a comparative analysis of how various surgical interventions influence the course of diabetes, the reasons for postbariatric glycaemia and predictors of the effectiveness of bariatric surgeries in terms of metabolic control in patients with type 2 diabetes mellitus.
Until recently, the primary focus of the studies by bariatric surgeons was on patients with grade 23 obesity and type 2 diabetes mellitus. However, in this review, special attention is given to the patients with a body mass index that ranges from 30 to 35 kg/m. Gained experience of the bariatric surgeons leads to high effectiveness with respect to the influence on the course of diabetes in patients with grade 1 obesity, which allows us to significantly expand the range of patients who should be recommended for this surgery. In addition, some information concerning surgical and metabolic complications of bariatric surgical intervention is provided, which allows us to seriously consider this treatment.
Clinical and immunological characteristics of diabetes mellitus in patients with autoimmune polyglandular syndrome type 1 in Russia
Authors: Sozaeva Leila S. , Zilberman Lubov I. , Svetlova Galina N. , Andrianova Ekaterina A. , Kareva Maria A. , Ivanova Olga N. , Stepanova Svetlana M. , Savelyeva Larisa V. , Mayorov Alexandr Y. , Troshina Ekaterina A. , Orlova Elizaveta M. , Husebye Eystein S. , Peterkova Valentina A.
Published: March 2018

Background. Autoimmune polyglandular syndrome type 1 (APS type 1) is a rare inherited autoimmune disease caused by mutations in AIRE gene (autoimmune regulator) and characterized by list of components. Diabetes mellitus (DM) can be one of components of this disease.
Aims. To show frequency of DM in patients with APS type 1 in Russia, to describe clinical and immunological aspects of DM in patients with APS type 1
Materials and methods. 113 patients have been enrolled in the study, 16 of them had DM (15/16) or impaired glucose tolerance (1/16). Antibodies against glutamate decarboxylase, tyrosine phosphatase, zinc transporter-8, insulin and -cells of pancreas were investigated in 30 patients with APS type 1 without DM and in 11 patients with APS type 1 and DM. ELISA test was used for detection autoantibodies.
Results. Frequency of DM in patients with APS type 1 in Russia is 14.1% (16/113). Some patients had slow-progressive DM 19%(3/16). Antibodies against insulin and -cells were not specific and also were not sensitive markers for DM in APS type 1. Antibodies against tyrosine phosphatase and zinc transporter-8 test showed high specificity (100% и 97%), but low sensitivity (42% и 33,3%). Antibodies against glutamate decarboxylase were less specific (70%) and had very low sensitivity (58,3%).
Conclusions. Frequency of DM in patients with APS type 1 in Russia is high to compare to other countries. 20% of Russian patients had slow-progressive course of DM. Antibodies against tyrosine phosphatase and zinc transporter-8 were the most specific for DM in patients with APS type 1, but sensitivity of these antibodies was low.
An novel cluster based feature selection and document classification model on high dimension trec data
Authors: Kumari Lalitha , Satyanarayana Ch.
Published: March 2018

TREC text documents are complex to analyze the features its relevant similar documents using the traditional document similarity measures. As the size of the TREC repository is increasing, finding relevant clustered documents from a large collection of unstructured documents is a challenging task. Traditional document similarity and classification models are implemented on homogeneous TREC data to find essential features for document entities that are similar to the TREC documents. Also, most of the traditional models are applicable to limited text document sets for text analysis. The main issues in the traditional text mining models in TREC repository include :1) Each document is represented in vector form with many sparsity values 2) Failed to find the  document semantic similarity between the intra and inter clusters 3) High mean squared error rate. In this paper, novel feature selection based clustered and classification model is proposed on large number of different TREC repositories. Traditional latent Semantic Indexing and document clustering models are failed to find the topic relevance on large number of TREC clinical text document sets due to computational memory and time. Proposed document feature selection and clustered based classification model is applied on TREC clinical benchmark datasets. From the experimental results, it is proved that the proposed model is efficient than the existing models in terms of computational memory, accuracy and error rate are concerned.
Sequential particle filter with covariance features classified with artificial neural nets for continuous Indian sign language recognition
Authors: Praveen Kumar P , V.G.D. Prasad Reddy P , Srinivasa Rao P
Published: March 2018

Machine translation of sign language is a complex and challenging problem in computer vision research. In this work, we propose to handle issues such as hands tracking, feature representation and classification for efficient interpretation of sign language from isolated sign videos. Hands tracking is attempted in a sequential format with one hand after the other by nullifying the effects of head movement using serial particle filter. The estimated hand positions in the video sequence are used to extract the hand portions to create a feature covariance matrix. This matrix is a compact representation of the hand features representing a sign. Adaptability of the feature covariance matrix is explored in developing relationships with new signs without creating a new feature matrix for individual signs. The extracted features are then applied to a neural network classifier which is trained with error backpropagation algorithm. Multiple experiments were conducted on a 181 class signs with 50 sentence formations with 5 different signers. Experimental results show the proposed sequential hand tracking is closer to ground truth. The proposed covariance features resulted in a classification accuracy of 89.34% with the neural network classifier.
SRR loaded half-mode substrate integrated waveguide monopole slot antenna for multiband applications
Authors: V Ramakrishna T , T P Madhav B , Venkateswara Rao M , Babu Rao A , Sunaina A , Avinash A , Shivani B
Published: March 2018

In this article A two layered printed microstrip line monopole slot antenna is proposed for multiband applications. The proposed antenna comprises of size 47*40*1mm with a modified half mode substrate integrated waveguide (M-HMSIW). By changing the slot width at the bottom ground the multiband characteristics has been obtained. A split ring resonator is placed on beside the patch to enhance the characteristics such as gain and bandwidth of the antenna. The proposed antenna works in the region of LTE band (2.1GHz) and WLAN (5.7GHz) and it also holds some applications at x-band applications. The simulated return loss and varied parametric vswr of the proposed antenna has been analyzed using ANSYS EM tool. The simulated results state a peak gain of 22dB and average gain of 5.7 dB. The result of the proposed antenna states that it is the best suitable for various multiband applications
Design and fabrication of portable laser cutting and engraving machine
Authors: Jamaleswara Kumar P. , Siva Sai Tarun A. , Gowtham M. , Thamma Rao P. , Yashwanth G.
Published: March 2018

Now a days digital control technology is became more and more useful to run the machines like portable laser cutting and engraving machines that can cut on the different surface contingent upon the power of the laser diode. In this paper the fundamental goal is to design and fabricate the laser cutting and engraving machine which is convenient to controlled by the Arduino CNC. It is accessible and perfect utilization for small and medium scale industries. This model is small, simple to work, cost of manufacturing and to effortlessly transport from one work station to other work station.
Optimization of integrated supply chain network problem using hybrid genetic algorithm approach
Authors: Chuluunsukh Anudari , Chen Xing , Yun YoungSu
Published: March 2018

In this paper, an integrated supply chain network (ISCN) problem is designed. The ISCN problem is composed of forward and reverse logistics and represented by a nonlinear mixed integer programming (NMIP). The objective of the ISCN problem is to maximize the total profit which is consisted of total revenues and total costs resulting from its implementation. A hybrid genetic algorithm (HGA) approach proposed in this paper is applied to solve the NMIP. In numerical experiment, five scales of the ISCN problem are presented and they are solved using the proposed HGA approach and some conventional approaches. Experimental results show that the proposed HGA approach outperforms the others.
Optimal customer relationship management in telecalling industry by using data mining and business intelligence
Authors: Kamalakannan T. , Mayilvaghnan P.
Published: March 2018

Decision making system in telecommunication industries plays a more important role where it is required to find customer churn. Customer churn prediction requires finding out and analyzing the information about the business data intelligence techniques which can be done efficiently by adapting the business intelligence techniques. Business intelligence provides tools to predict and analyze the historical, current and predictive views of business operations. However, this would be more complex task with high volume of data which are gathered from million of telephone users for the time being. It can be handled effectively by introducing the data mining techniques which select the most useful information from the gathered data set from which decision making can be done efficiently. In this research method, telecommunication industry is considered in which customer churn prediction application is focused. The main goal of this research method is to introduce the data mining technique which can select the most useful information from the telecommunication industry dataset. This is done by introducing the Hybrid Genetic Algorithm with Particle Swarm Optimization (HGAPSO) method which can select the most useful information. In this research, the hybrid HGAPSO combines the advantages of PSO and GA optimally. From the selected information, decision making about the customer churn prediction can be done accurately. Finally decision making is done by predicting the customer behaviour using Support Vector Machine classification approach. The performance metrics are considered such as precision, recall, f-measure, accuracy, True Positive Rate (TPR), False Positive Rate (FPR), time complexity and ROC. Experimental results demonstrated that HGAPSO provides highly scalable which is used for prediction examination in the business intelligence.
Implementation of hybrid filter technique for noise removal from medical images
Authors: Choubey Shruti Bhargava , Subba Rao S.P.V.
Published: March 2018

Image denoising is used to eliminate the noise while retaining as much as possible the important signal features. The function of image denoising is to calculate approximately the original image form the noisy data. Image denoising still remains the challenge for researchers because noise removal introduces artifacts and causes blurring of the images. Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). MR images are typically corrupted with noise, which hinder the medical diagnosis based on these images.  The presence of noise not only causes as undesirable visual quality as well as lowers the visibility of low contrast objects. in this paper noise removal approach has proposed using hybridization of three filter with DWT method.Results calculated in terms of PSNR,MSE & TIME.
Enhanced tensor factorization framework using non-negative and probabilistic tensor factorization approaches for microblogging content propagation modelling
Authors: Baggyalakshmi N. , Kavitha A. , Marimuthu A.
Published: March 2018

With the aim of identifying the user’s preferences, Content propagation modeling from the micro-blogging sites aids diverse organizations. In existing studies, four user behavior aspects were used by the content propagation model that is to say topic virality, user’s position, user susceptibility and user virality. The propagation occurrences are signified as a tensor factorization model so-called V2S is presented with the aim of deriving the behavioral aspects via which the content propagation is designed. On the other hand, it doesn’t comprise the linguistic patterns in the content that decreases the performance of the content propagation. Moreover, by utilizing advanced tensor approaches, the factorization structure is improved. Therefore the performance of the complete system is decreased meaningfully. With the aim of overcoming the aforesaid problems, Enhanced V2S (EV2S) Tensor Factorization framework is presented in this research that make use of the Probabilistic Latent Tensor Factorization (PLTF) as well as Non-negative Tensor Factorization (NTF) in order to derive the behavioral facets. NTF is presented for decreasing the content propagation errors. By making use of fast gradient descent technique, the unrestrained issue, which happens in this model is solved. This research system identifies the reposts as well as re-tweets in huge datasets proficiently with minimum processing time. From the experimentation outcomes, it is proved that the EV2S-PLTF tensor factorization performs better when compared to the previous tensor frameworks.
Methodology for regression testing with open source tool
Authors: Hema Shankari K. , Thirumalai Selvi R.
Published: March 2018

The paper describes our methodology for optimizing regression testing that forms a major part of software maintenance. It necessitates the use of an automated testing tool, and we have selected Selenium, an open source tool. For simple projects, a formula is proposed that has been derived through data mining with Selenium. A genetic algorithm is added to this methodology for industry based projects, where the test cases are so large that they have to be grouped as Test Suites; this algorithm reconfigures Test suites in each cycle of regression testing. Commonly used APFD metric ignores fault severity but is included in our formula; this severity is determined by professional testers. The use of ANN to amend severity without manual intervention enhances the genetic algorithm. Tables presented in the paper are from both simple and industry projects. Comparison is made with IBM’S RFT, a proprietary tool for automated testing.
A fuzzy analytic hierarchy attribute weighting and deep learning for improving CHD prediction of optimized semi parametric extended dynamic bayesian network
Authors: Gomathi K. , Shanmuga Priyaa D.
Published: March 2018

Several Data mining techniques have been developed to enhance the prediction accuracy and analyze several events in Coronary Heart Disease (CHD).  One among them was Extended Dynamic Bayesian Network (EDBN) which integrates   temporal abstractions with DBN. Then EDBN was extended as Optimized Semi parametric Extended Dynamic Bayesian Network (OSEDBN) to handle Complex temporal abstractions in irregular interval time series data. The deep learning network is generated the various time points in the next level to improve the analysis and prediction of CHD. In this paper, Optimized Semi parametric Extended Deep Dynamic Bayesian Network (OSEDDBN) is proposed by integrating deep learning architecture with OSEDBN to improve the ability of extracting more important data and support complex structures from various types of input sources. Additionally the Fuzzy Analytic Hierarchy Process (FAHP) approach is used to compute the global weights for the attributes based on their individual contribution. The global weights of the attributes obtained by FAHP are utilized for training OSEDDBN to further improve the prediction of Coronary Heart Disease (CHD) risks. The performance of EDBN, OSEDBN, OSEDDBN, and OSEDDBN-FAHP are evaluated in terms of Precision, Recall and F-Measure.
A distributed big data library extending Java 8
Authors: A R Quadri MD. , Sruthi B. , SriRam A. D. , Lavanya B.
Published: March 2018

Java is one of the finest language for big data because of its write once and run anywhere nature. The new release of java 8 introduced few strategies like lambda expressions and streams which are helpful for parallel computing. Though these new strategies helps in extracting, sorting and filtering data from collections and arrays, still there are problems with it. Streams cannot properly process with the large data sets like big data. Also, there are few problems associated while executing in distributed environment. The new streams introduced in java are restricted to computations inside the single system there is no method for distributed computing over multiple systems. And streams store data in their memory and therefore cannot support huge data sets. Now, this paper cope with java 8 behalf of massive data and deed in distributed environment by providing extensions to the Programming model with distributed streams. The distributed computing of large data programming models may be consummated by introducing distributed stream frameworks.
A critical study on applicability of sokoban game for building cognitive model of a student for career assessment
Authors: Chandra Prakash V. , Sastry J. K. R. , Rao V.Kantha , Vineetha T. , Harika V. , Abhishek Reddy A.
Published: March 2018

Career assessment is extremely important for a student to choose the best career in his/her life. A career counsellor may assess a student by considering his/her academic record and the scores obtained in IQ tests, reasoning, quantitative-aptitude, etc. and suggest a suitable career. After studies, when the student gets employment in his/her selected career, at times, the student may find it very difficult to continue in his/her career. A major reason may be that the psychology of the student may not match with the psychology that is expected for the chosen career. Hence, it is highly essential for the counsellors to assess the psychological factors of a student before suggesting a suitable career. Game playing is one method through which psychological factors of a student can be assessed. This paper presents a critical study on applicability of Sokoban game for assessing student’s psychological factors so that an Expert system can build a cognitive model of a student for career assessment.
Personalized web search on e-commerce using ontology based association mining
Authors: Sekhar Babu B. , Lakshmi Prasanna P. , Vidyullatha P.
Published: March 2018

In current days, World Wide Web has grown into a familiar medium to investigate the new information, Business trends, trading strategies so on. Several organizations and companies are also contracting the web in order to present their products or services across the world. E-commerce is a kind of business or saleable transaction that comprises the transfer of statistics across the web or internet. In this situation huge amount of data is obtained and dumped into the web services. This data overhead tends to arise difficulties in determining the accurate and valuable information, hence the web data mining is used as a tool to determine and mine the knowledge from the web. Web data mining technology can be applied by the E-commerce organizations to offer personalized E-commerce solutions and better meet the desires of customers. By using data mining algorithm such as ontology based association rule mining using apriori algorithms extracts the various useful information from the large data sets .We are implementing the above data mining technique in JAVA and data sets are dynamically generated while transaction is processing and extracting various patterns.
Hadoop high availability through multiple active name nodes
Authors: Vijaya Lakshmi P , V.S Ramesh K , Likhitha P , Pranay Kumar M
Published: March 2018

HDFS having only single dynamic name node, if that name node occur hardware or software failure, the entire HDFS model will be inac-tive position until the recovery of name node. So that to reduce that problem the standby name nodes are placed, which they are an inactive position. On failover occur to primary name node all its metadata will transfer to the standby name nodes. After primary name node fails remaining standby nodes elects one of the nodes to take the position of primary name node. But on transferring the metadata to remaining standby name nodes there will be heavy burden to the primary name nodeIn this paper, we proposed a solution to reduce the load on the primary name node by transferring the metadata to remaining standby name nodes. We compress the entire metadata in the primary name node and sent that data into remaining all standby name nodes.
Enhancement of security in cloud computing with secure multi-party computation
Authors: Vijaya Kumar A , J.V.Vineetha N , Sai Chakradar P , Kalyan Sai K
Published: March 2018

The N sets of parties which are allowed by unconditionally the secure multiparty computation (MPC) for computing securely with a registered function f with the help of unbounded adversary computational at some specified field. Here one can corrupt t among n parties maliciously corrupt. The Protocols of MPC which are known and efficient are developed for online or offline framework. Coming to the offline process, the private & random multiplication-triples which is sharable can be generated by the parties in this framework. Later on, these are useful for online to evaluate the multiplication of gates securely in a circuit which describes as f. In this, Protocols of the MPC efficiency depends on the how the offline implementation efficiently. Here, we proposed a simple method, for shared & private multiplication-triples which are random in nature generation without any conditions securely & safely. The typical protocols face this issue, when the random values of shared pairs produced initially. And also, in computing the product values which is shared for every pair. After that, protocols of multiplication and values which are considered as communication intensive. In proposed scheme, the multiplication protocols are completely used in different manner. Later on, we observe that the share multiplication-triples verification by parties or they are extracted securely or not. With the use of setting of the hybrid network and asynchronous, linear communication MPC protocols used which are multiplication gate overhead & indicates as f. The above are the improvements on the typical MPC protocols with the help of hybrid networking setting, asynchronous and complexity of the communication, if we give to result of synchronous setting in our system. It results efficient MPC protocols which are rounded.
UPFC based transmission line power load flow control under different operating methods
Authors: Lingaswamy K , Anil Kumar T , Hari Krishna G , Shiva Prasad N
Published: March 2018

In this paper the methods to control operation of shunt and series inverters using power flow controller (UPFC) is analyzed with real power flow in power system transmission line. These operation mode using UPFC are executed to reduce Swaying in the control framework transport. The execution about every system may be resolved toward the predefined administrative control. Those arrangement What's more shunt converter working under four separate blending from claiming working modes may be used to ponder An example force framework organize. The line flow in MW oscillation damping is predicated with various modes of operations and verified same with MATLAB/ SIMULINK.
ACNM: advance coupling network model sleep/awake mechanism for wireless sensor networks
Authors: Mohammad Habibulla , S. Chandrasekhara Sastry A
Published: March 2018

Wireless Sensor Network (WSN) has attracted many researchers due to its abilities in monitoring remote locations. To gather physical data, such as temperature, humidity, and so on WSNs are utilized. To fulfill the strict constraints like energy consumption and network performance, ongoing wireless sensor networks requires efficient methodologies and practices. The major concern in wireless networks is how to conserve the nodes energy so that network lifespan can be prolonging significantly. The research work focuses on ACNM-DEC (Advance Coupling Network Model-Deterministic Energy-efficient Clustering) protocol i.e. enhancing DEC protocol with sleep awake(S-A) mechanism to utilize energy efficiently. The technique sleep-awake is implemented by simply coupling nodes which are at nearer to one another. The nodes which are paired will switch in two modes i.e. Idle (sleep) and busy (awake). Sleep/wake scheduling is an essential consideration in sensor network applications. Finding an optimal sleep/wake scheduling strategy that would minimize computation and communication overhead, be resilient to node failures, and provide high-quality data service is extremely challenging. In this paper, we present and compare several state-of-the-art algorithms and techniques that aim to address the sleep/wake scheduling issue, which are divided into distributed and centralized manners. The obtained results of the simulation prove that the lifespan of the communication model has been extended in terms of its performance, good energy utility and data transmission.
Design of CPW fed f-shaped circularly polarized antenna for amateur radio vehicular communications
Authors: V. Ramakrishna T , T.P. Madhav B , Amulya D , Sumitra S , Sai Kumar A , Rohit M , Anilkumar T
Published: March 2018

In this paper a compact circularly polarized antenna is proposed to operate in X-band spectrum. The F-shaped monopole element is used as the radiating structure and the closed coplanar-waveguide ground is used on a FR4 substrate. The proposed feeding mechanism with asymmetric ground planes and the three rectangular strips connected to the feed line. The proposed antenna operates with a -10dB reflection coefficient bandwidth from 9.3 GHz to 13 GHz and the circular polarized performance is attained from 9.8 GHz – 11.2 GHz with axial ratio less than 3dB (AR < 3dB). The antenna gain in the boresight direction is found to be achieved as 4.34dB and radiates with a maximum efficiency of 90% which is suited for amateur radio applications in X-band spectrum based vehicular communications.
Incorporating autonomicity and trustworthiness aspects for assessing software quality
Authors: Dehraj Pooja , Sharma Arun , S. Grover P
Published: March 2018

Autonomic computing covers few self-abilities like self-configuration, self-healing, self-optimization, self-protection, self-adaptability, self-awareness, self-openness etc. in software systems. These self-abilities will lead towards lowering the overall maintenance cost of the software because of minimum level of human intervention. The term Autonomicity refers to the level of autonomic (self) features implemented in the system. The International software quality standard ISO 9126 is now replaced by new software product quality standard ISO/IEC 25010:2011 which defines the framework/model to specify and evaluate the quality of software as a product. However, this does not take into account the self-* features (autonomic aspects) and trust factor of modern day software systems. The present paper proposes here that autonomic characteristics of any system must be considered while assessing the quality of any software product. This autonomic-oriented quality model may be used to assess the software quality in a number of domains. Therefore, a new enhanced software quality model is proposed which considers autonomicity and trustworthiness as a factor of quality.
Enterobacteria virulence factor prediction server
Authors: Thirunavu karasu M , Dinakaran K , N. Sathishkumar E , Gnanendra S
Published: March 2018

The continuous usage of antibiotics has resulted in the increase of multidrug resistance in the bacteria. The drastic increase in the bacterial genome projects has paved a path for the identification of potentially novel virulence-associated factors and their possibility as novel drug targets. Thus in the present study, we have implemented SMO classifiers for the better prediction of proteins based on individual protein sequences amino acid composition (AAC) and the performance of evaluation was checked via threshold dependent parameters such as Sensitivity, Specificity, Accuracy, and Mathew correlation coefficient. The predictions are based on the dataset incorporated in the database of five major virulence factors from six pathogens of Enterobacteriacae.This comprehensive database can serve as a source for the selection of significant virulence factor based on the intellectual Gene ontology terms that play a critical role in the pathogenesis and its surveillance in the host.
An optimized feature selection using fuzzy mutual information based ant colony optimization for software defect prediction
Authors: Manivasagam G , Gunasundari R
Published: March 2018

In recent years, there is a significant notification focused towards the prediction of software defect in the field of software engineering. The prediction of software defects assist in reducing the cost of testing effort, improving the process of software testing and to concentrate only on the fault-prone software modules. Recently, software defect prediction is an important research topic in the software engineering field. One of the important factors which effect the software defect detection is the presence of noisy features in the dataset. The objective of this proposed work is to contribute an optimization technique for the selection of potential features to improve the prediction capability of software defects more accurately. The Fuzzy Mutual Information Ant Colony Optimization is used for searching the optimal feature set with the ability of Meta heuristic search. This proposed feature selection efficiency is evaluated using the datasets from NASA metric data repository. Simulation results have indicated that the proposed method makes an impressive enhancement in the prediction of routine for three different classifiers used in this work.
Dos invasion at network by intruder; protection mecha-nism by “anti-dos invasion firewall”
Authors: S. Govindaraj , S. V. Khanaa , Rukkumani C.
Published: March 2018

Every cyber-warfare done by criminal perpetrators motto is not to know information and data, but are interested in denial of service assaults which never attempt to breach the security or firewall, Rather to intend the network surge for particular span of time and denial of access which ultimately target end legitimate user through two method of DOS attack (crash service or flooding service).The main problem with the “Denial Of Service” attack that it will lead to network surge or corruption of data which is transfer or processed from source to destination via some transmission techniques through network.
A modified PV fed 9 level inverter for standalone applications with reduced number of switches
Authors: V Jaikrishna , Sekhar Dash Subhranhsu , T Alex Linss
Published: March 2018

The power crisis in India is increasing at an alarming rate. Solar power is a domestic source of energy and its availability throughout the year makes it a primary target to solve this crisis. It will never produce any hazardous waste and it won’t pollute the air. But various issues like Power quality problems and Harmonic distortion seep in due to the intermittent nature of PV system. Multi-Level Inverter (MLI) gives solution for PQ issues and helps in high power handling capabilities. In this work a new multilevel inverter topology is proposed. The controlled pulses are generated through sinusoidal PWM techniques. The proposed topology is implemented and the controlled circuit is simulated in MATLAB/SIMULINK. The same is realized in the hardware circuit having a cost effective dsPIC30F2010 digital controller. The proposed topology consists of only seven power electronic switches and that is the main advantage of this topology. The Simulation results and the Hardware results reveal that the suggested technique is highly advantageous.
Optimizing performance of fuzzy decision support system with multiple parameter dependency for cloud provider evaluation
Authors: Rani Uma , Dalal Surjeet , Kumar Jugnesh
Published: March 2018

Manuscript removed
Multiband microstrip patch antenna with rectangular slots on patch for bluetooth and c-band applications
Authors: Dadhich Ajay , Deegwal J. K.
Published: March 2018

A Multiband Microstrip Patch Antenna with rectangular slots on patch is proposed for Bluetooth and C band applications. The proposed antenna is fabricated by etching rectangular patch of  dimension on a lossy FR-4 substrate with dimensions 40 mm (L) × 40 mm (W) × 1.6 mm (h) , relative permittivity  =4.4 and loss tangent δ = 0.025. 50 ohm microstrip feed line with inset feed is used for proper impedance matching. Proposed antenna is simulated on Computer Simulation Tool (CST) microwave studio suite software and measurement is done on Network Analyzer (VNA). The proposed multiband antenna can be used for IEEE 802.15.1 (operating in 2.402-2.480 GHz band), wireless local area network and other wireless communication applications.
Channel estimation for long term evolution downlink receiver system performance
Authors: N Prabakaran , S Sivakannan , Fernandes J Bennilo , G Thirugnanam
Published: March 2018

3GPP LTE is the advancement of the UMTS because of ever‐increasing requests for brilliant interactive media administrations as indicated by client's desires. Since downlink is dependably an essential factor in scope and limit viewpoints, extraordinary consideration has been given in choosing innovations for LTE downlink collector. In this paper, LTE-downlink receiver framework exhibitions of Channel Response estimations are tried and assessed utilizing FDD transmission plans. An insertion calculation is utilized to acquire all Channel Response estimations. In this model direct addition calculations utilized as a part of recurrence and image area. The high information rates and the high limit can be accomplished by utilizing the upsides of the two advances. These advances have been chosen for LTE downlink receiver. Pilot‐assisted channel estimation is a strategy in which known signs, called pilots, are transmitted alongside information to get channel learning for legitimate deciphering of got signals. This paper goes for channel estimation for LTE downlink receiver framework. The execution of the framework recreated in various remote channel models that comprises of AWGN, RAW AWGN and Veh A channels. The execution of the framework is assessed utilizing distinctive regulations, for example, QPSK, 16 QAM and 64 QAM. Execution of these calculations has been measured as far as Bit Error Rate (BER) Vs Eb/No.
The ongoing construction trends in Shaktipithas of Himachal Pradesh-symbols of living religious heritage
Authors: Bhandari Harveen , Kaur Prabhjot , Ramani Grover Aruna
Published: March 2018

Shaktipithas represent India’s rich cultural heritage. The continuity of functions at these sites further reinstates their significance as    Living Religious Heritage. Their spiritual value is central to hundreds of millions of people who visit them every year. The growing   population, boost in commerce, advancements in construction technology has impacted the construction trends in all spheres and typologies of architecture. Temples, the religious heritage of the country, are being widely affected by this new movement in architecture. These temples were built years ago using characteristic elements from Indian traditional temple styles or regional vernacular elements. With growth in population and rising number of pilgrims, these complexes face shortfall of infrastructure facilities. To accommodate large inflow of pilgrims especially on festivals large scale construction activities are in full swing on these sites. This paper tends to present a thorough insight into the ongoing developments at some popular sites in Himachal Pradesh, India which are in contemporary style using modern methods of construction. It is highly insensitive to the existing character of our religious heritage and deteriorates the built environment. So the need arises to conserve our cultural heritage, take timely measures to make these places sustainable pilgrimage destinations and keep alive their distinct sacred visual impact.
CMOS Front-End of LNA for GPS and GSM wireless applications
Authors: Mudavath Mahesh , Hari Kishore K.
Published: March 2018

This paper describes a layout of a CMOS Low Noise Amplifier for reconfigurable packages which include GPS, GSM Wi-Fi applications. The improvement of a notably linear Radio front-stop, able to function with Galileo and GPS satellite signals suitable for coexisting in a mobile opposed environment for area based offerings, pleasing the fundamental necessities for a mass market product which includes low cost, low footprint, good accuracy, low strength intake and high sensitivity. primarily based on a wideband enter matching, the LNA stages cowl all band of hobby even as reaching a great change-off between excessive gain, low noise parent and coffee electricity intake. The complete simulation analysis of the circuit results in the frequency range of 1.4 GHz to 2 GHz. The noise figure is 1.8 dB at 1.4GHz and rises to 3.4 dB at 2 GHz. The input return and output return losses (S11, S22) of the LNA at a frequency range between 1.4 GHz and 2 GHz are S11= -12 dB, S22 =-44.73 dB at 1.77 GHz and S22 =-26.47 dB at 2 GHz. The overall gain of the LNA (S21) is 13 dB at 1.4025 GHz, 3rd order input intercept point (IIP3) = -3.16 dBm and -1dB compression point is -12.56 dBm. Input Impedance of 50Ω, 3dB Power Bandwidth of 450MHz, and Power Dissipation of 2.7mW at 1.2V power supply.
Integrated and effective in-system debugging approach in FPGA circuits
Authors: Murali A. , Hari Kishore K.
Published: March 2018

This paper explores the new approaches for trace-based and In-system debugging of high level synthesis-generated hardware. The presented approach also exhibits the use of the Event Observability Ports (EOP) which provides the source level event observability in the hardware. To trace the events, the use of the independent trace buffers also known as Event Observability Buffers (EOB) is also discussed. The EOB has the signal that specifies the enabling the data storage and allows the storage decisions cycle-by-cycle which are to be made on the basis of EOB-by-EOB. The proposed approach also reveals the timing relationships of the captured events in the trace buffers. To recover the lost relationships among these events, we have introduced two methods in this paper. We also presented the demonstration and effectiveness of the trace strategy of an EOB.
Efficient and low latency turbo encoder design using Verilog-Hdl
Authors: Siva Kumar M , Syed Shameem S , Raghu Sai M.N.V. , Nikhil Dheeraj , Kartheek P. , Hari Kishore K
Published: March 2018

Low complexity turbo-like codes based totally on the simple trellis or simple graph shape consequences in encoding with low complexity. Out of this Convolution, encoder and turbo codes are widely used due to the splendid errors control performance. The most famous communications encoding set of rules, the iterative deciphering calls for an exponential expansion in hardware complexity to acquire expanded encode accuracy. This paper makes a usage of Log-Map based Iterative decoding technique and specialty in the conclusion of the turbo encoder. The rapid codes are designed with the help of Recursive Systematic Convolution and are separated thru interleave, which (thing used to rearrange the bit collection) plays an essential position within the encoding technique. This paper offers the design of the parallel connection of Recursive Systematic Convolution (RSC) encoders and interleave to restrict postpone, results to form a turbo Encoder. The turbo Encoder is designed by way of Verilog-HDL and Synthesized through Xilinx ISE
Analysis of power reduction and implementation on FPGA for AES-128bits using BEDT schemes
Authors: Sapna Kumari C. , Prasad K. V.
Published: March 2018

Due to rapid improvement for innovations in cryptography, the scattered of power link in connections of cryptography contexts instigates to resist through the power disseminated via substitute mechanisms of the communication subsystem, the switches and the sub modules of cutting edge encryption standard (AES). The dynamic power dissemination in joins is real supporter of the power utilization in organize on the chip. Due to self-exchanging and cross coupling capacitance the power consumption is shirking in communications system for security aspects. In the present research work the encoding strategy the key self-exchanging is diminish by examination the exchanging change and afterward the link between the connections is patterned and guaranteed that the power utilization is lessened. To upgrade control utilization in encryption and decoding process, Bit Encryption and Decryption Transition (BEDT) information schemes went for lessening the power disseminated by the AES chiefly include round key module in AES to perform XOR operation between 128 bits plain content and secrete key. The suggested research work in this paper is main basic concept of AES due to its number of round operations and also it will allow 39% of energy sprinkling and 9% of energy utilization without having more number execution debasement and with below 11% range overhead in the other cryptography frameworks. The proposed BEDT schemes depends on both odd modified and even rearranged, and after that sending the information to receiver that will performed utilizing the kind off reversal which lessens increasingly the exchanging movement. In these proposed three schemes, utilizes an easier decoder while accomplishing a higher movement diminishment. In the prior schemes, the quantity of changes from 0 to 1 for two back to back flutters is tallied. The bit transitions reduce the number of transitions before transmitting the data to decryption.
An identity encryption cloud scheme based on SMTP using advanced blow fish algorithm
Authors: Vasantha R. , Satya Prasad R.
Published: March 2018

Essential strategies vicinity unit acquainted with send the lion's share structures to collect the desired info. thanks to the imperfectness of truely the best data coding and additionally the utilization of preferred coding calculation, that wasn't accelerated in standard approaches for the time period procedure, a consolidated coding calculation is planned. This planned calculation gives new stride to stay removed from weaknesses. we will be inclined to apply a few standard algorithms to code AN data as takes as soon as. At to start with, we will be inclined to create new calculation maintaining in mind the tip purpose to provide security issue and time imperative of operation then we have a tendency to be a part of AES utilising multiplexing of keys, development in DES key size and blowfish calculation, at that time we have a propensity to code info using the deliberate calculation. this could improve the protection and muddles the coding. throughout this paper we provide each the coding and unscrambling that backings incessantly application and calculation incorporates a helpful esteem and loss of life penalty this calculation crosswise over cloud advances in encryption and decryption info over SMTP based usually utility.
Future of internet of things (IoT) in 5G wireless networks
Authors: Passi Abhiruchi , Batra Deepak
Published: March 2018

Internet of Things or IoT has evolved and will play a major role in our lives in the near future. Though in the nascent stage, it conceptually means an interconnected network consisting of physical objects, wearables, machines, buildings, automobiles and a variety of other types of devices that contain embedded technology to communicate and sense or interact with their internal states or external environment. With the advent of next generation 5G wireless technology around 2020, a wave of globally connected digital society will come into existence. In this paper we will discuss about the benefits which will be provided to IoT with the onset of 5G wireless technology and the challenges which IoT will offer to 5G.