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Top 10 read research articles in the field of Advanced Information Technology @ 2024

Survey Of Web Crawling Algorithms

    Rahul kumar1 Hakima Mellah, Anurag Jain2 and Chetan Agrawal3, 1Radharaman Institute of Technology and Science, India, 2Radharaman Institute of Technology and Science, India, 3Radharaman Institute of Technology and Science, India

    ABSTRACT

    The World Wide Web is the largest collection of data today and it continues increasing day by day. A web crawler is a program from the huge downloading of web pages from World Wide Web and this process is called Web crawling. To collect the web pages from www a search engine uses web crawler and the web crawler collects this by web crawling. Due to limitations of network bandwidth, time-consuming and hardware's a Web crawler cannot download all the pages, it is important to select the most important ones as early as possible during the crawling process and avoid downloading and visiting many irrelevant pages. This paper reviews help the researches on web crawling methods used for searching.

    KEYWORDS

    Web crawler, Web Crawling Algorithms, Search Engine.


    For More Details :
    https://aircconline.com/avc/V3N3/3316avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




A Method For Detecting False Positive And False Negative Attacks Using Simulation Models In Statistical Enroute Filtering Based Wsns

    Su Man Nam1 and d Tae Ho Cho2, 1Sungkyunkwan University, Republic of Korea, 2Sungkyunkwan University, Republic of Korea

    ABSTRACT

    In wireless sensor networks, adversaries compromise sensor nodes to damage the network though potential threats such as false positive and false negative attacks. The false positive attacks cause energy drain and false alarms, and false negative attacks generate information loss. To address the false positive attacks in the sensor network, a statistical en-route filtering (SEF) detects the false report in intermediate nodes. Even though the scheme detects the false report against the false positive attack, it is difficult to detect false MACs in a legitimate report against the false negative attack in the SEF-based WSN. Our proposed method effectively detects the false positive and false negative attacks in the sensor network through a simulation model. The experimental results indicate that the proposed method increase detection power while maintaining the energy consumption of the network against the false positive and false negative attacks.

    KEYWORDS

    Wireless Sensor Networks, Network Security, Simulation models, Statistical En-route Filtering Network Protocols


    For More Details :
    https://aircconline.com/avc/V3N3/3316avc02.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




Colour, Texture And Shape Feature Analysis For Person Re-Identification Technique

    Poongothai1 , and Suruliandi2, Manonmaniam Sundaranar University, Tamilnadu, India

    ABSTRACT

    Person re-identification across different surveillance cameras has become one of the recent and challenging approaches in the area of video surveillance system. Although many methods have been introduced for re-identification, certain issues like illumination, pose variation and occlusion are unsolved. All the existing methods focused only on developing learning methods by varying the features. The aim of this work is to analyze the effectiveness of feature for re-identification. The colour, texture and shape features has taken for the analysis. The images are collected from multiple databases for training and testing. The analysis shows that every feature has its unique properties and works according to that to solve the issues

    KEYWORDS

    Re-identification, Colour, Texture, Shape ,Surveillance


    For More Details :
    https://aircconline.com/avc/V3N3/3316avc03.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




Discerning Spam In Social Networking Sites

    Sarita Yadav , Aakanksha Saini , Akanksha Dhamija and Yoganta Narnauli, GGSIPU, New Delhi, India

    ABSTRACT

    Social Networking Sites, in the present scenario, are an amalgam of knowledge and spam. As their popularity surges among the users day by day so does it among the spammers looking at easy targets for their campaigns. The threat due to spams causing atrocious harm to the bandwidth, overloading the servers, spreading malicious pages online et cetera has increased manifold making it necessary for researchers to foray into this field of spam detection and reduce their effect on the various social networking sites.
    In this paper, we propose a framework for spam detection in the two largest social networking sites namely, Twitter and Facebook. We’ll be utilizing the data publically available on these two giants of social networking era. Initially, we’ll be citing the various approaches that have already been explored in this field. After that we’ll briefly explain the two methods that we used to collect the datasets from these websites.

    KEYWORDS

    API’s, Honeypots, Facebook, Social Networking websites, Spam, Twitter, SVM, Weka, Naïve Bayes Algorithm, Simple K means clustering.


    For More Details :
    https://aircconline.com/avc/V3N2/3216avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




A Survey On Handwritten Character Recognition (Hcr) Techniques For English Alphabets

    Manoj Sonkusare1, and Narendra Sahu2, 1Ujjain Engineering College,Ujjain, India, 2Women’s Polytechnic College,Indore, India

    ABSTRACT

    Nowadays Hand written Character Recognition (HCR) is major remarkable and difficult research domain in the area of Image processing. Recognition of Handwritten English alphabets have been broadly studied in the previous years. Presently various recognition methodologies are in well-known utilized for recognition of handwritten English alphabets (character). Application domain of HCR is digital document processing such as mining information from data entry, cheque, applications for loans, credit cards, tax, health insurance forms etc. During this survey we present an outline of current research work conducted for recognition of handwritten English alphabets. In Handwritten manuscript there is no restriction on the writing technique. Handwritten alphabets are complicated to recognize because of miscellaneous human handwriting technique, difference in size and shape of letters, angle. A variety of recognition methodologies for handwritten English alphabets are conferred here alongside with their performance.

    KEYWORDS

    Handwritten Character Recognition (HCR), features extraction, Optical Character Recognition (OCR), classifiers, Pre-Processing.


    For More Details :
    https://aircconline.com/avc/V3N1/3116avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




Resolving Of Vertex Disclosure And Multi Community Disclosure In Social Networks

    Gowthamy.R1, and Uma.P2, 1Nandha Engineering College, India, 2Nandha Engineering College, India

    ABSTRACT

    Social network acts as a platform for sharing different types of information between different typed of users.Social network is modeled as a graph, consisting of vertex and edges. Users involved in sharing data are considered as vertex or node and relationship between different users is mentioned as edges. Main issues likevertex identity disclosure and multicommunity identity disclosurepresent recently in social network. Information about each user identity is vertex identity. Different types of communities where the user involved in social network is defined as multicommunity identity. To overcome these two risks a privacy preservation technique KW –Structural Diversity Anonimity is introduced. Where K denotes number of nodes in social network and W is a time stamp recording of updation made in the network.

    KEYWORDS

    Privacy preservation, vertex disclosure and multicommunity disclosure,KW -structural diversity anonymity technique.


    For More Details :
    https://aircconline.com/avc/V3N1/3116avc02.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol3.html




Foreground Object Extaction Based On Independent Component Analysis

    Rahul Paul and Sushanta Mukhopadhyay, ISM Dhanbad,India

    ABSTRACT

    Moving objects are often characterized by coherent motion that is distinct from that of the background. This makes motion a very useful feature for segmenting video sequence. Extracting moving objects from videos is important for many applications like surveillance, traffic analysis etc. In this paper a novel and efficient moving object segmentation algorithm is proposed that is based on independent component analysis (ICA). Moving objects and static background are considered to be independent, so independent component analysis is applied on frames of a video sequence to identify the preliminary independent components containing moving objects. This source image data obtained after ICA are further processed using anisotropic diffusion. Anisotropic diffusion is used here to reduce the noise present in the preliminary source image without removing the significant parts of the image content. Finally, a post-processing step based on morphology is applied on the obtained objects to remove small unnecessary objects and to smooth the object boundary to produce the final segmented images indicating the moving objects. The method is tested on various datasets and experimental results establish the satisfactory performance of the proposed algorithm.

    KEYWORDS

    Motion segmentation, Independent component analysis, anisotropic diffusion, mathematical morphology


    For More Details :
    https://aircconline.com/avc/V2N4/2415avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol2.html




Vision Assisted Pick And Place Robotic Arm

    Nisha1, Dinesh Kumar2, Sekar3, and Indira4, 1 Madurai Kamaraj University, India, 2Madurai Kamaraj University, India, 3Madurai Kamaraj University, India, 4Madurai Kamaraj University, India

    ABSTRACT

    This paper presents the design of a Vision assisted pick and place robotic Arm. The main objective of the paper isto pick and place an object from one place to other by 2 DOF robotic arm. USB camera is used as a vision sensor to measure the dimensions of the object to be picked. The USB camera collects the image of the object is transferred to the LabVIEW API with image processing toolkits and modules to process the image. The processed dimension of the object is transmitted via RS-232 serial communication to the microcontroller LPC2129. The appropriate PWM signal is generated by LPC2129 respectively to the servomotors. The robotic arm is designed with servomotors. Digital image processing algorithms are implemented to process the image captured by the USB camera to find the exact dimension of the object thereby to assist the robotic arm to finest. NI-IMAQ - Machine vision based functions are implemented and the results are presented.

    KEYWORDS

    Robotic Manipulator, NI-IMAQ- Machine Vision, Image Processing, LPC2129 microcontroller


    For More Details :
    https://airccse.org/journal/avc/papers/2315avc02.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol2.html




More On Interval-Valued Intuitionistic Fuzzy Soft Multi Sets

    Anjan Mukherjee1, Ajoy Kanti Das2, and Abhijit Saha3, 1 Tripura University, India, 2ICV-College, India, 3Techno India College, India

    ABSTRACT

    In 2013, Mukherje et al. developed the concept of interval-valued intuitionistic fuzzy soft multi set as a mathematical tool for making descriptions of the objective world more realistic, practical and accurate in some cases, making it very promising. In this paper we define some operations in intervalvalued intuitionistic fuzzy soft multi set theory and show that the associative, distribution and De Morgan’s type of results hold in interval-valued intuitionistic fuzzy soft multiset theory for the newly defined operations in our way. Also, we define the necessity and possibility operations on intervalvalued intuitionistic fuzzy soft multi set theory and study their basic properties and some results.

    KEYWORDS

    Soft set, interval-valued intuitionistic fuzzy set, interval-valued intuitionistic fuzzy soft set, intervalvalued intuitionistic fuzzy soft multi set.


    For More Details :
    https://airccse.org/journal/avc/papers/2215avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol2.html




A New Image Quality Metric Using Compressive Sensing And A Filter Set Consisting Of Derivative And Gabor Filters

    Dong-O Kim and Rae-Hong Park, Sogang University, Korea

    ABSTRACT

    This paper proposes an image quality metric (IQM) using compressive sensing (CS) and a filter set consisting of derivative and Gabor filters. In this paper, compressive sensing that is used for acquiring a sparse or compressible signal with a small number of measurements is used for measuring the quality between the reference and distorted images. However, an image is generally neither sparse nor compressible, so a CS technique cannot be directly used for image quality assessment. Thus, for converting an image into a sparse or compressible signal, the image is convolved with filters such as the gradient, Laplacian of Gaussian, and Gabor filters, since the filter outputs are generally compressible. A small number of measurements obtained by a CS technique are used for evaluating the image quality. Experimental results with various test imagesshow the effectiveness of the proposed algorithm in terms of the Pearson correlation coefficient (CC), root mean squared error, Spearman rank order CC, and Kendall CC..

    KEYWORDS

    Compressive Sensing, Derivative Filters, Difference Mean Opinion Score, Gabor Filter, Image Quality Assessment.

    For More Details :
    https://airccse.org/journal/avc/papers/2115avc01.pdf


    Volume Link :
    https://airccse.org/journal/avc/vol2.html








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