Volume 10, Number 4

In this paper, the Eighteenth Order Convergent Method (EOCM) developed by Vatti et.al is considered and this method is further studied without the presence of second derivative. It is shown that this method has same efficiency index as that of EOCM. Several numerical examples are given to illustrate the efficiency and performance of the new method.

AMS Subject Classification: 41A25, 65K05, 65H05.

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An injective function g:V(G)→{F₀,F₁,F₂,...,F_n+1},where F_jis the jth Fibonacci number(j=0,1,...,n+1), is said to be Fibonacci cordial labeling if the induced functiong∗: E(G) →{0,1}defined by g ∗(xy)=(f(x)+f(y)) (mod2) satisfies the condition |e_g(1)−e_g(0)|≤1. A graph having Fibonacci cordial labeling is called Fibonacci cordialgraph. In this paper, i inspect the existence of Fibonacci Cordial Labeling of DS(Pn),DS(DFn),EdgeduplicationinK_{1, n},Jointsum ofGl(n),DFn⊕K_1,nand ring sum of star graph with cycle with one chord and cycle with two chords respectively.

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Today internet has become a trusted factotum of everyone. Almost all payments like tax, insurance, bank transaction, healthcare payment, payment in e-commerce are done digitally through debit or credit card or through e-wallet. People share their personal information through social media like Facebook. Twitter, WhatsApp etc. The government of every developing country is going to embrace e-Governance system to interact with people more promptly. The information shares through these applications are the burning target to intruders. This paper utilized the imperceptibility as well as the robustness of steganography techniques which are increased by embedding multiple bits in a particular region selected either based on some image attributes or by Human Visual Perception.

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Day by day, data is growing rapidly. Analysis of the data is necessity. As per recent survey data generated in last 2 years is more than the data created in entire previous history of human. Data created in different form and in diversified manner. It can be structured, it can be semi-structured, or it can be unstructured. To analyze diversified by agricultural data we can use the tools of Big Data like Pig. Using Pig, we can analyze varieties of data. Pig is a platform for analysis of data. Biggest advantage of Pig is it can process any diversified data very quickly and allows us to use user defined functions. Use Case of Pig is ETL. It is used to extract the data from sources then after applying transformation we can load it into the data warehouse. We will do analysis of state wise proportion circulation of Numeral of operative properties for all societal collections in 2005-06 and 2010-11 using Pig.

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For last two decades, the demand for wireless spectrum has been increasing rapidly with tremendous developments in the telecom industry. There also has been huge growth in flow of multimedia traffic over the last decade. Thus, the demand for additional bandwidth is increasing exponentially despite the fact that the electromagnetic spectrum is a finite resource. On the other hand, spectrum occupancy is found to be quiet low in most of the allocated bands. Thus, the under-utilization of the precious spectrum is unaffordable if persistent growth of new and existing wireless services are to be sustained. Cognitive radio (CR) is a future technology initiated by many research organizations and academic institutions to increase the spectrum utilization of underutilized spectrum channels to ameliorate scarcity problem of valuable electromagnetic spectrum. There exists number of issues and challenges in designing and implementation of the cognitive radio. These issues need to be rigorously resolved before a cognitive radio is realised.

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To measure testability before the actual development starts will play a crucial role to the developer, designers and end users as well. Early measurement of testability, especially in early requirement stage to assist the developer for the further development process, and will also assures us to produce and deliver the high quality requirement that can surely reduce the overall cost and improves the quality of development process. Taking view of this fact, this paper identifies testability estimation factors namely understandability and modifiability and establishes the correlation among testability, understandability and modifiability. Further, a model is developed to quantify software testability in requirement phase and named as Requirement Testability Model of Object Oriented Software-RTM^OOS. Furthermore, the correlation of Testability with these factors has been tested and justified with the help of statistical measures.

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Data mining has become one of the emerging fields in research because of its vast contents. Data mining is used for finding hidden patterns in the database or any other information repository. This information is necessary to generate knowledge from the patterns. The main task is to extract knowledge out of the information. In this paper we use a data mining technique called classification to determine the playing condition based on the current temperature values. Classification technique is a powerful way to classify the attributes of the dataset into different classes. In our approach we use classification algorithms like Decision Tree (J48), REP Tree and Random Tree. Then we compare the efficiencies of these classification algorithms. The tool we use for this approach is WEKA (Waikato Environment for Knowledge Analysis) a collection of open source machine learning algorithms.

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Cognitive radio is a future technology coined for increasing the utilization of otherwise under-utilized spectrum channels. Providing quality of service (QoS) to diverse flows as per their requirements is a very difficult job as there is no dedicated allocation of wireless channels in cognitive radio (CR) network. The paper selects few critical QoS parameters such as signal-strength, bandwidth and user-mobility that assess the influence on quality of communication between users using rule-based fuzzy inference system. The analytical results show the influence of those QoS parameters on the quality of communicating channels and open new issues in designing protocol structure for CR.

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Presence of missing values in the dataset leads to difficult for data analysis in data mining task. In this research work, student dataset is taken contains marks of four different subjects in engineering college. Mean, Mode, Median Imputation were used to deal with challenges of incomplete data. By using MSE and RMSE on dataset using with proposed Method and imputation methods like Mean, Mode, and Median Imputation on the dataset and found out to be values of Mean Squared Error and Root Mean Squared Error for the dataset. Accuracy also found out to be using Proposed Method with Imputation Technique. Experimental observation it was found that, MSE and RMSE gradually decreases when size of the databases is gradually increases by using proposed Method. Also MSE and RMSE gradually increase when size of the databases is gradually increases by using simple imputation technique. Accuracy is also increases with increases size of the databases.

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Cognitive radio (CR) is a promising solution to improve the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Spectrum handoff is a different type of handoff in CR necessitated by the reappearance of primary user (PU) in the licensed band presently occupied by the secondary users (SUs). Spectrum handoff procedures aim to help the SUs to vacate the occupied licensed spectrum and find suitable target channel to resume the unfinished transmission. The purpose of spectrum mobility management in cognitive radio networks is to make sure that the transitions are made smoothly and rapidly such that the applications running on a cognitive user perceive minimum performance degradation during a spectrum handoff. In this paper, we will survey the literature on spectrum handoff in cognitive radio networks.

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Now a day’s usage of android applications has become a part of our life. By using these applications our work becomes simple and easier in our day to day activities. This paper suggests an android application which is generally useful for the students and parents. It contains various features like notifying the student about the renewal date of library books, alerting students and their parents about the percentage of attendance and reminds them about number of classes they should present to maintain the specified attendance threshold. This application also alerts the students and parents about various events like examinations, workshops to be held, student activities to be conducted etc. This application is user friendly and can be installed in any android smart phone

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Practical effort estimation is very basic and most essential aspect of very organisation to sustain better project management. Accuracy in efforts makes the organisation to surge its business and build motivation among its customers effectively. It was observed that continuous improvement is required for software effort assessment after regular eras.The fundamental point of this examination work is to assess the execution of Re-UCP strategy for estimation of efforts for web application projects. This research work compares the existing effort estimation model results with the Re-UCP effort estimation methods results for web application development projects.

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Data Warehouse design requires a radical rebuilding of tremendous measures of information, frequently of questionable or conflicting quality, drawn from various heterogeneous sources. Data Warehouse configuration assimilates business learning and innovation know-how. The outline of theData Warehouse requires a profound comprehension of the business forms in detail. The principle point of this exploration paper is to contemplate and investigate the transformation model to change over the E-R outlines to Star Schema for developing Data Warehouses. The Dimensional modelling is a logical design technique used for data warehouses. This research paper addresses various potential differences between the two techniques and highlights the advantages of using dimensional modelling along with disadvantages as well. Dimensional Modelling is one of the popular techniques for databases that are designed keeping in mind the queries from end-user in a data warehouse. In this paper the focus has been on Star Schema, which basically comprises of Fact table and Dimension tables. Each fact table further comprises of foreign keys of various dimensions and measures and degenerate dimensions if any. We also discuss the possibilities of deployment and acceptance of Conversion Model (CM) to provide the details of fact table and dimension tables according to the local needs. It will also highlight to why dimensional modelling is preferred over E-R modelling when creating data warehouse.

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The review and comparative analysis of the methods of compression and recognition of speech signals is carried out. The result of the carried out analysis of the existing recognition methods indicates, that all of them are based on the use of “inflexible” algorithms, which are badly adapted to the characteristic features of speech signals, thus degrading the efficiency of the operation of the whole recognition system. The necessity of the use of algorithms for determination of recognition features along with the use of the wavelet packet analysis as one of the advanced directions of the creation of the effective methods and principles of the development of the speech signals recognition systems is substantiated.

Analysis of the compression methods with the use of the orthogonal transformations at the complete exception of minimal decomposition factors is conducted; a maximal possible compression degree is defined. In this compression method the orthogonal transformation of the signal segment with the subsequent exception of the set of the smallest modulo decomposition factors, irrespective of the order of their distribution, is conducted. Therefore the additional transfer of the information on the factors distribution is required.

As a result, two information streams appear, the first one corresponds to the information stream on the decomposition factors, and the second stream transfers information on the distribution of these factors.

Method of the determination of the speech signals recognition features and the algorithm for nonlinear time normalization is proposed and proved.

Wavelet-packet transformation is adaptive, i.e. it allows adapting to the signal features more accurately by means of the choice of the proper tree of the optimal decomposition form, which provides the minimal number of wavelet factors at the prescribed accuracy of signal reconstruction, thus eliminating the information-surplus and unnecessary details of the signals.

Estimation of the informativeness of the set of wavelet factors is accomplished by the entropy. In order to obtain the recognition factors, the spectral analysis operation is used. In order to carry out the temporary normalization, the deforming function is found, the use of which minimizes the discrepancy between the standard and new words realization.

Dedicated to the determination of admissible compression factors on the basis of the orthogonal transformations use at the incomplete elimination of the set of minimal decomposition factors, to the creation of the block diagram of the method of the recognition features formation, to the practical testing of the software- methods. In order to elevate the compression factor, the adaptive uniform quantization is used, where the adaptation is conducted for all the decomposition factors. The program testing of the recognition methods is carried out by means of determination of the classification error probability using Mahalanobis (Gonzales) distance.

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Extending the Internet to connect any physical device with smart technology can be called as the Internet of Things (IoT).It is a proposed development of the Internet in which everything can be connected to the internet enabling them to send and receive data. Selection of energy efficient routing protocols has become an essential step in designing any IoT network. Moreover, the protocol should also be selected to enhance the lifetime of the network. In this article, we evaluate the performance analysis of DEEC (Distributed Energy Efficient Clustering), DDEEC (Developed DEEC), EDEEC (Enhanced DEEC) and TDEEC (Threshold DEEC) for the application in IoT. From MATLAB simulation, it was observed that TDEEC outperforms other routing protocols and is well suited for IoT application.

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The main thrust of the study is to develop a cloud-based application performance monitoring system of the cadets while on board ship training for the Philippine Merchant Marine Academy in San Narciso, Zambales which intended to serve as an alternative system that can be used by the target school in monitoring the performance of the cadets while on ship board and determine its effectiveness.

The researcher has used the descriptive research method wherein the study is focused on the present situations. It involves the recording, description and the presentation of the present system, composition and phenomena.

The Statement of the problem focused in obtaining the effectiveness of the proposed cloud based application in performance monitoring system of the cadets for the Philippine Merchant Marine Academy, San Narciso, Zambales.

Findings showed that the Department of Shipboard Training needs a real time system that can monitor the cadets while on board ship training. Based on the conclusion of this study, the researcher recommends the development of the cloud based application which will monitor the performance of the cadets while on board ship training and lastly, the developed system was tested during the implementation and met no errors.

Based on the findings, the number of respondents as group per course is in parallel to the ratio of the students currently enrolled at PMMA. Majority of the respondents for both the groups came from the existing Group whose ages range from 19-21 years old.As revealed, the majority of the respondents for both the groups are males from the Proposed Group.

In the proposed system out of one hundred percent respondents, thirty or 93.5% cadets; while the officials are nine or 6.5% of the one hundred, from the total of thirty-nine respondents.

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A new framework recognition system for identifying the missed pilgrims in Hajj and Umrah is presented in this paper. The framework recognition system is based on the Wavelet Probabilistic Neural Network (WPNN) classifier. The entire framework recognition system is capable of identifying the missed pilgrims. The framework recognition systems is developed as an application for mobile phones The proposed framework recognition system is applied to a huge database for pilgrims in the Ministry of Hajj Computer server for matching and identifying the missed pilgrim. The results are superior comparing to the existing systems

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The authors show that in a Built-In Self-Test (BIST) technique, based on linear-feedback shift registers, when the feedback connections in pseudo-random test-sequence generator and signature analyzer are images of each other and corresponds to primitive characteristic polynomial then behaviors of faults masking remains identical. The simulation results of single stuck-at faults show how the use of such feedback connections in pseudo-random test-sequence generator and signature analyzer yields to mask the same faults.

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