bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fuzzy Weighted Ordered Weighted Average-Gaussian Mixture Model for Feature Reduction
Authors: S Charles. , Arockiam Dr. L. 
Published: May 2018

Feature reduction finds the optimal feature subset using machine learning techniques and evaluation criteria. Some of the irrelevant features are existed in the real-world datasets that should be removed by using the multi criterion decision approach. The relevant features are determined by using the WOWA criteria in fuzzy set. There are two important criteria are considered such as preferential weights and importance weights of features. These weights are used to find the irrelevant features and they are removed from the mixture. In this context, WOWA operator has the capability of assigning the preferential weights and important weights to the features. It helps to obtain the irrelevant, by selecting the relevant features using the weights in the feature reduction process. The objective of this paper is to propose a FWOWA approach helps to discard the irrelevant features by avoiding the overfitting and improve the accuracy of the cluster. The irrelevant features are determined by applying WOWA. By applying WOWA, the irrelevant features are examined and it is removed from the Gaussian Mixture using (RPEM).Â Â Â
ANALYSIS OF HUMAN FACE RECOGNITION ALGORITHM USING PCA+FDIT IN IMAGE DATABASE FOR CRIME INVESTIGATION
Authors: Manjula V. S. 
Published: May 2018

In general, the field of face recognition has lots of research that have put interest in order to detect the face and to identify it and also to track it. Many researchers have concentrated on the face identification and detection problem by using various approaches. The proposed approach is further very useful and helpful in real time application. Thus the Face Detection, Identification Â which is proposed here is used to detect the faces in videos in the real time application by using the FDIT (Face Detection Identification Technique) algorithm. Thus the proposed mechanism is very help full in identifying individual persons who are been involved in the action of robbery, murder cases and terror activities. Although in face recognition the algorithm used is of histogram equalization combined with Back propagation neural network in which we recognize an unknown test image by comparing it with the known training set images that are been stored in the database. Also the proposed approach uses skin color extraction as a parameter for face detection. A multi linear training and rectangular face feature extraction are done for training, identifying and detecting. Â Â Thus the proposed technique Â Â is PCA + FDIT technique configuration only improved recognition for subjects in images are included in the training data.Â Â It is very useful in identify a single person from a group of faces. Â Â Thus the proposed technique is well suited for all kinds faces frame work for face detection and identification. The face detection and identification modules share the same hierarchical architecture. They both consist of two layers of classifiers, a layer with a set of component classifiers and a layer with a single combination classifier. Â Also we have taken a real life example and simulated the algorithms in IDL Tool successfully.
DEFINING QUALITY CRITERIA IN SITUATIONAL METHOD ENGINEERING
Authors: Azzouz Samir , Kraiem Naoufel , Ghezala Henda Ben 
Published: May 2018

Method engineering is a field of engineering that has been created a need expressed by engineers. These engineers faced problems in using conventional methods such as SSADM, DSDM, OOAD...In this way, Method engineering was created to intend to develop methods to meet these needs. Therefore, these methods have been employed in a wide range of projects led by these architects. In other contexts, we are led to customize a method for a particular project. The method obtained is called Situational Method (SM).In this paper, we define the basics in order to achieve the monitoring of Situational Method quality in the early stages of its setting up to its effective exploitation.Â In addition, we identify criteria that allow us to evaluate the construction of a method in terms of quality.Finally, we discuss the choices we have made in this paper and challenges that we have to raise to achieve this quality concept.
EXTENDING THE VISUAL CRYPTOGRAPHY ALGORITHM USING IMAGE WATERMARKING TECHNIQUE
Authors: Kotthapalli Dilip Kumar , Anitha Dr. V.R. 
Published: May 2018

Visual cryptography is a secret information sharing technique which shares the information in the form of images. It generates noise-like random pixels on share images to hide secret information which on overlay decrypt the information. This technique is known as conventional visual secret sharing schemes. It suffers a management problem, because of which dealers cannot visually identify each share. This problem is solved by the extended visual cryptography scheme (EVCS), which adds a meaningful cover image in each share. While removing the extra cover image it produces extra noise or degrades the hidden image quality. So we propose a new image watermarking technique in this Visual Cryptography Algorithm that places a small image on the noisy image pair at the bottom right corner. So that the cover images need not be removed and it doesn't degrade Â resolution of the secret image.
Maintainability Evaluation of Object-Oriented Software System Using Clustering Techniques
Authors: Mehra Astha , Dubey Sanjay Kumar 
Published: May 2018

In todayâ€™s world data is produced every day at a phenomenal rate and we are required to store this ever growing data on almost daily basis. Even though our ability to store this huge data has grown but the problem lies when users expect sophisticated information from this data. This can be achieved by uncovering the hidden information from the raw data, which is the purpose of data mining.Â Data mining or knowledge discovery is the computer-assisted process of digging through and analyzing enormous set of data and then extracting the meaning out of it. The raw and unlabeled data present in large databases can be classified initially in an unsupervised manner by making use of cluster analysis. Clustering analysis is the process of finding the groups of objects such that the objects in a group will be similar to one another and dissimilar from the objects in other groups. These groups are known as clusters.Â In other words, clustering is the process of organizing the data objects in groups whose members have some similarity among them. Some of the applications of clustering are in marketing -finding group of customers with similar behavior, biology- classification of plants and animals given their features, data analysis, and earthquake study -observe earthquake epicenter to identify dangerous zones, WWW -document classification, etc. The results or outcome and efficiency of clustering process is generally identified though various clustering algorithms. The aim of this research paper is to compare two important clustering algorithms namely centroid based K-means and X-means. The performance of the algorithms is evaluated in different program execution on the same input dataset. The performance of these algorithms is analyzed and compared on the basis of quality of clustering outputs, number of iterations and cut-off factors.
A Proposed Non Linear Block Based Approach for Image De-Noising Using Wavelet
Authors: Singh Tajinder , Bedi Rajeev , Gupta S.K 
Published: May 2018

Coding of images or processing of images has played a momentous role in the success of digital communications and multimedia. Coding plays a major role is 3D mobile generation. The image processing methods have been exploited through the years to improve the quality of digital images. In the image processing system De-noising based coding is used extensively. As we know that, in low bit rate applications, the blocking artifacts problem arises, which severely reduce the visual quality of the image. Reducing blocking artifacts is essential to render the compressed visual data acceptable to the viewer. So, to detect and reduce noise from the image is a major task. So removing the noise from original signal is still a challenging problem for researchers. There have been several published algorithms and each approach has its assumptions, advantages, and limitations. For real-time applications like television, photo-phone, etc. it is essential to reduce the noise power as much as possible and to retain the fine details and the edges in the image as well. Moreover, it is very important to have very low computational complexity so that the filtering operation is performed in a short time for online and real-time applications. The main focus of this paper is first to define an algorithm and based on that a non linear threshold filter is described which not only preserve the actual image structures in the presence of different types of noises (Salt & peepers, Speckle and Gaussian Noise) as well as it provide betterÂ PSNR, MSE, MAE, & Time Complexity than others Classical algorithms.
Usability Evaluation Approach for VLS: A Conceptual Framework
Authors: Omieno Kelvin Kabeti , Oenga Laban , Raburu Dr. George 
Published: May 2018

E-learning software systems have been proposed by many researchers and academics as alternative platform for pedagogy other than traditional face-to-face. One of such information systems (IS) is Virtual learning Systems (VLS). VLS are becoming an increasingly common form of education due to the need for a platform that provides ability to connect people with required sets of skills, regardless of their location in the world.Â However, user satisfaction has always been a major factor in the success of software, regardless of whether the software is closed proprietary or open source software (OSS). Although user-centred designs are gaining recognition among virtual learning systems (VLS) community, many design scenarios still do not incorporate usability as one of their primary goals. Accordingly, many individuals believe that if VLS was more usable, its popularity would increase tremendously. Although there are strong usability models for IS, there is still potential to improve the usability of VLS.Â The usability assessment of VLS projects is an area where relatively little research has been conducted, and, accordingly, the main contribution of this work is a methodology that evaluates the usability maturity of a VLS project. Consequently, the study presents a usability maturity model that is aimed at usability-related issues for virtual learning system projects. The model to be developed is a response to a need for measuring the extent to which virtual learning systems software projects support usability. Specifically, it is intended for assessing and improving the usability aspect in VLS software development. The deductions from the research findings will be especially useful to e-learning practitioners, ICT and Education professionals and policy makers and researchers in Virtual Learning Environments.
MULTIPLE-ACCESS TECHNOLOGY OF CHOICE IN 3GPP LTE
Authors: Frank Ibikunle , Ike Dike , Jimi Ajayi , Kayode Onasoga 
Published: May 2018

Third-Generation Partnership Project (3GPP) standardizes an Evolved UMTS Terrestrial Radio Access Network (EUTRAN)as air interface in its release 8 LTE. Orthogonal Frequency Division Multiple Access(OFDMA) and Single Carrier-Frequency Division Multiple Access(SC-FDMA)are key technologies for the air interface of mobile broadband systems.It isÂ evident that mobile broadband access technologies are reaching a commonality in the air interface and networkingÂ architecture; they are being converged to an IP-based network architecture with OFDMA based air interface technology.Â The air interface of E-UTRAN is based on OFDMA in downlink and SC-FDMA in the uplink, making it possible to efficientlÂ utilize bandwidth due to the orthogonally between sub-carriers and by assigning subsets of sub-carriers to individual usersÂ which allows for simultaneous data rate transmission from several users and differentiated quality of service for each user.Â In this paper, wehighlight the technologies behindOFDMA and SC-FDMA and also carry out performance comparison ofÂ the two air interface technologies. We brieflydescribe the 3GPP LTE standard, and its implementation using OFDMA andÂ SC-FDMA technology.
Performance Analysis of Stable Election Protocol for Clustered Heterogeneous Wireless Sensor Networks
Authors: Bhattacharya Partha Pratim , Rathi Neha 
Published: May 2018

While wireless sensor networks are increasingly equipped to handle more complicated functions, these battery poweredsensors which used in network processing, use their constrained energy to enhance the lifetime of the network especiallyÂ in a heterogeneous settings. Clustered techniques have since been employed to optimize energy consumption in thisÂ energy constrained wireless sensor networks. In Classical clustering protocols, equal energy is assigned to all nodes andthey cannot take full benefit of the presence of node heterogeneity. SEP, a heterogeneous-aware protocol is used toÂ prolong the time interval before the death of the first node which is crucial for many applications where the feedback fromthe sensor network must be reliable. The performance of SEP in comparison to LEACH Protocol is analyzed in this paperwhose goal is to increase the stable region and as a result decrease the unstable region and improve the quality of thefeedback of wireless sensor network, in presence of heterogeneous nodes.
A Variable Step Size for Acoustic Echo Cancellation Using Normalized Sub band Adaptive Filter
Authors: Ojhla Harjeet Kaur , Talwar Dr. Rajneesh , Darekar Jyoti 
Published: May 2018

Numerous various step size normalized least mean square (VSS-NLMS)Algorithms have been derived to solve the problem of fast convergence rate and low mean square error.Here we find out the ways to control the step size. A normalized subband adaptive filter algorithm uses a fixed and variable step size, which is chosen as a trade-off between the steady-state error and the convergence rate. A variable step size for normalized subband adaptive filter is derived by minimizing the mean-square deviation between the optimal weight vector and the estimated weight vector at each instant of time. The variable step size is presented in terms of error variance. Therefore, we verify thedifferentÂ algorithmseither they are capable of tracking in stationary and non-stationary environments. The results show good tracking ability and low misalignment of the algorithm in system identification. Parameters are tracking, steady state errors, and misalignment, environment, step size.
A FRAME WORK FOR WEB INFORMATION EXTRACTION AND ANALYSIS
Authors: Abburu Dr Sunitha , Babu G. Suresh 
Published: May 2018

Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured.Â But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies Â data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.Â Â It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making.Â The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.
Logical Circuits for Extended Content Matching in Hardware Based NIDPS
Authors: Georgiev Dejan , Tentov Aristotel 
Published: May 2018

In this paper we present logical circuits for efficient detection of rolled out contents. As network speed increases and security mattersÂ there is a demand for implementation of hardware based Network Intrusion Detection and Prevention Systems (NIDPS). On the other hand hardware based NIDPS are lacking the flexibility of detection of so named "evasion" techniques. Here we present simple but efficient enhancement to content matching in hardware with minimal basic memory elements (flip-flops) used.
A New Approach of Location Based Routing in MANETs
Authors: Sharma Priyanka , Gaur PK , Verma Lal Pratap 
Published: May 2018

The highly dynamic nature of MANETs results in frequent and unpredictable changes in the network topology, which add to the difficulty and complexity to routing among the mobile nodes within the network. Thus, establishing communication among mobile nodes is a great challenge in itself, resulting in network overloading & discarding of data packets. Nodes can change position quite frequently, which means we need a routing protocol that quickly adapts to the topology changes which is our objective. Â In this paper focus has been put on the strategy to address the packet drop ratio which is an integral and important factor of communication in MANETs by minimizing the request zone. In Mobile Ad-Hoc Networks, as the coverage area increases the packet drop ratio also increases which degrades the network performance and Quality of Service (QOS).Location Aware Routing Â will be used as a base protocol for the proposed work which is a class of Reactive protocol to design optimized routing algorithm.
COLOR MEDICAL IMAGE COMPRESSED USING QUINCUNX WAVELETS AND SPIHT CODING
Authors: Hacene Ismail Boukli , Beladgham Mohamed , Bessaid Abdelhafid 
Published: May 2018

In the field of medical diagnostics, interested parties have resorted increasingly to color medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. This paper introduces an algorithm for color medical image compression based on the quincunx wavelets coupled with SPÃHT coding algorithm.Â In order to enhance the compression by our algorithm, we have compared the results obtained with those of other methods containing wavelet transforms. For this reason, we evaluated two parameters known for their calculation speed. The first parameter is the PSNR; the second is MSSIM (structural similarity) to measure the quality of compressed image. The results are very satisfactory regarding compression ratio, and the computation time and quality of the compressed image compared to those of traditional methods.
An Efficient Fuzzy Technique for Detection of Brain Tumor
Authors: Sirisha P.G.K. , Raju C. Naga , Reddy R. Pradeep Kumar 
Published: May 2018

Â Â In this epoch Medical Image segmentation is one of the most challenging problems in the research field of MRI scan image classification and analysis. The importance of image segmentation is to identify various features of the image that are used for analyzing, interpreting and understanding of images. Image segmentation for MRI of brain is highly essential due to accurate detection of brain tumor. This paper presents an efficient image segmentation technique that can be used for detection of tumor in the Brain. This innovative method consists of three steps. First is Image enhancement to improve the quality of the tumor image by eliminating noise and to normalize the image. Second is fuzzy logic which produce optimal threshold to avoid the fuzziness in the image and makes good regions regarding Image and tumor part of the Image. Third is novel OTSU technique applied for separating the tumor regions in the MRI. This method has produced better results than traditional extended OTSU method.
Continuous & Piecewise Convex Behavior Of Maximum Values Of Some Generalized Measures Of Fuzzy Cross Entropy.
Authors: Gandhi C.P. 
Published: May 2018

Consider two fuzzy sets A and B with same supporting points and the corresponding fuzzy vectors and respectively, where each can vary subject to the total fuzziness and each is known to us .In this paper, a comprehensive and straightforward procedure is made available to find the maximum values of some existing measures of generalized fuzzy cross entropy. Further, the continuous and piecewise convex behavior of the values so obtained is also discussed mathematically as well as graphically. Finally, a numerical example is used to illustrate the proposed method.
Similarity Measurement in the Hybrid of Semantic Web Search Engine
Authors: Abdullah Noryusliza , Ibrahim Rosziati 
Published: May 2018

Semantic Web approach with the assistance of ontology is widely used to give more reliable application in retrieving information and knowledge.Â It is capable to discover the World Wide Web (WWW) that is presented in natural-language text.Â Based on previous research, incorporating categorization with ontology concept has proven to give better results.Â However, performing hybrid of the search engine using another technique that is user profiling has a promising potency in enhancing the searching process.Â Utilizing searching time and giving relevant results are the contributions of this research.Â The proposed hybrid techniques integrate ontologies, categorization and user profiling concept.Â In user profiling, similarity measure is adopted in making comparison between two different ontologies.Â WordNet and UTHM Onto are the independent ontologies used in this process.Â The preliminary experimental results have given interesting results in terms of data arrangement and time usage.
Comparing the impact of Clustering with Content Based Image Retrieval Approaches for Plant Identification
Authors: Asrani Komal , Jain Renu 
Published: May 2018

Contour Based retrieval of images is an active and challenging field of research. Â Among various parameters available for contour based image retrieval, shape is considered an important aspect because it is closest to the human perception. Most of the shape based image retrieval methods require large processing time for generating accurate results due to huge database. To reduce the search time, we have divided the database into clusters on the basis of eccentricity of leaf using K-Means approach. After making the clusters, different contour based approaches are applied for leaf/plant identification and results are compared. Â The leaf image is processed to generate feature vectors which are stored in database. Â We have used Swedish leaf image database (SLID) consisting of 15 species with 75 leaves per class and total of 1125 leaf images. In this paper, we compare results of contour based retrieval approaches with and without clustering. From these results, it is found that by incorporating clustering, performance of contour based retrieval approaches remains same but retrieval time is reduced.
An Offline SEO (Search Engine Optimization) Based Algorithm to Calculate Web Page Rank According to Different Parameters
Authors: Rani Parveen , Singh Er. Sukhpreet 
Published: May 2018

SEO stands for Search Engine Optimization. It is a technique that searches various web pages for specified keywords and ranks these Web pages according to some parameters. They are used to feed pages to search engines. Â The main importance of SEO is that it helps to find the relevant data and increase the rank of a webpage in search enginesâ€™ results. In our paper, we develop a new algorithm M-HITS (Modified HITS) to provide the page rank. M-HITS Algorithm is a new version of HITS algorithm. It is developed by extending the properties of HITS algorithm.