Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1195
Image Classification using Support Vector Machine and Artificial Neural Network
Статья научная
Image classification is one of classical problems of concern in image processing. There are various approaches for solving this problem. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and Support Vector Machine (SVM) applying for image classification. Firstly, we separate the image into many sub-images based on the features of images. Each sub-image is classified into the responsive class by an ANN. Finally, SVM has been compiled all the classify result of ANN. Our proposal classification model has brought together many ANN and one SVM. Let it denote ANN_SVM. ANN_SVM has been applied for Roman numerals recognition application and the precision rate is 86%. The experimental results show the feasibility of our proposal model.
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Image Denoising using Tri Nonlinear and Nearest Neighbor Interpolation with Wavelet Transform
Статья научная
In this paper new methods Tri Non Linear Interpolation and nearest neighbor interpolation for image denoising in wavelet domain are proposed. Tri non linear interpolation methods better de-noising method which preserves the image feature like edges and background. Interpolation is way through which images are enlarged. The nearest neighbor interpolation used forward wavelet and enlarges the size of image which retains the image parameter. The nearest neighbor interpolation technique is fruit full for variety of noisy images. PSNR is key parameter for measurement of image quality throughout this text. The existing methods used the threshold technique for noise removal but our methods image quality is better as compared to the existing threshold technique.
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Image retrieval using hypergraph of visual concepts
Статья научная
Retrieving images similar to query image from a large image collection is a challenging task. Image retrieval is most useful in the image search engine to find images similar to the query image. Most of the existing graph based image retrieval methods capture only pair-wise similarity between images. The proposed work uses the hypergraph approach of the visual concepts. Each image can be represented by combination of the several visual concepts. Visual concept is the specific object or part of an image. There are several images in the database which can share multiple visual concepts. To capture such a relationship between group of images hypergraph is used. In proposed work, each image is considered as a vertex and each visual concept as a hyperedge in a hypergraph. All the images sharing same visual concept, form a hyperedge. Images in the dataset are represented using hypergraph. For each query image visual concept is identified. Similarity between query image and database image is identified. According to these similarities association scores are assigned to images, which will handle the image retrieval.
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Immune-Inspired Self-Protection Model for Securing Grid
Статья научная
The application of human immunology in solving security problems in Grid Computing seems to be a thought-provoking research area. Grid involves large number of dynamic heterogeneous resources. Manually managing the security for such dynamic system is always fault prone. This paper presents the simple immune based model for self-protection (SIMS) of grid environment from various attacks like DoS, DDoS, Probing, etc. Like human body helps to identify and respond to harmful pathogens that it doesn't recognize as "self", in the same manner SIMS incorporates the immunological concepts and principles for safeguarding the grid from various security breaches.
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Impact of Collaborative ALM on Software Project Management
Статья научная
To produce a release of software, ALM is a key for streaming the team’s ability. ALM consists of the core disciplines of requirements definition and its management, asset management, development, build creation, testing, and release that are all planned by project management and orchestrated by using some form of process [1]. The assets and their relationships are stored by the development team repository. Detailed reports and charts provide visibility into team’s progress. In this paper we will describe how the ALM involves software development activities and assets coordination for the production and management of software applications throughout their entire life cycle.
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Impact of IS Strategy and Technological Innovation Strategic Alignment on Firm Performance
Статья научная
The alignment between information systems strategy and business strategy as an important driver of competitiveness has predominantly been assessed through quantitative methods without exploring in detail factors that influence strategic alignment and their implications for perceived business performance. Most IS-business strategic alignment studies dominantly focus on entire business and IS strategies resulting in many findings that are too general and inconclusive. This study aims at assessing strategic alignment factors, their interrelationships, and how they influence the IS-business alignment and its consequential effect on the performance of six universal banks in Ghana. The study followed the systematic procedure of grounded theory design and adopted qualitative dominant crossover mixed analysis. The findings of the study indicate strategic alignment between information systems strategy and technological innovation impacts positively on the performance of a firm where IT utilization complements resources and capabilities.
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Impact of Internet of Things (IoT) as Persuasive Technology
Статья научная
The Internet of Things (IoT) adds a new dimension to how people and things can communicate and collaborate. Society and the Internet are now being interconnected tightly and purposely. The research aims to analyze how IoT as a persuasive technology can affect human behavior and increase the awareness and effectiveness of IoT products among users. How will the Internet of Things infrastructure facilitate humans to change their attitudes and behaviors towards specific routine work? Our objective is to analyze which factors influence the acceptance and rejection of particular behaviors and the core motivators that persuade people to do something or to avoid something. We aim to determine whether IoT will facilitate humans to change their focused behaviors or not. Because of the rapid convergence of digital and physical worlds and the advent of digital technology, the Internet and social media have opened up a new world of affordances, constraints, and information flows from a design perspective. This article discusses how digital architecture affects behavior and the ramifications for designers who want to influence behavior for social and environmental good. In this paper we aim to give a brief introduction to persuasive technology, especially as it pertains to human adoption of IoT technology. We discuss a number of current research opportunities in IoT gadgets and their adoptions [1]. Our results indicate that persuasive (IoT) infrastructure can be expected to achieve a change of driving behaviour among their adopters. Furthermore, attention should be paid to an appropriate selection and implementation of persuasive strategies.
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Impact of Throughput in Enhancing the Efficiency of Cognitive Radio Ad Hoc Network - A Study
Статья научная
Cognitive Radio Ad Hoc Networks (CRAHNs) constitute a viable solution to solve the current problems of inefficiency in the spectrum allocation, and to deploy highly reconfigurable and self-organizing wireless networks. Cognitive Radio (CR) devices are envisaged to utilize the spectrum in an opportunistic way by dynamically accessing different licensed portions of the spectrum. However the phenomena of channel fading and primary cum secondary interference in cognitive radio networks does not guarantee application demands to be achieved continuously over time. Availability of limited spectrum and the inadequate spectrum resource usage necessitates a new communication standard to utilize the existing wireless spectrum opportunistically. This paper discusses currently existing mechanism for providing better efficiency by utilizing cognitive network intelligence. The frequencies used are utilized to the maximum extent without any interference. This paper aims in comparing the techniques used for enhancing the throughput in CR.
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Impact of Variation in Pause Time and Network Load in AODV and AOMDV Protocols
Статья научная
A MANET is a collection of mobile nodes by wireless links forming a dynamic topology without any network infrastructure such as routers, servers, access points/cables or centralized administration. The communication within the network is facilitated through a protocol which discovers routes between nodes. The two major classifications of routing protocols are unipath and multipath. In this paper, the performance comparison of widely used on-demand unipath and multipath routing protocols such as AODV and AOMDV is carried out in terms of variation in pause time and network load under RWM in CBR Traffic. These protocols have been selected for simulation due to their edges over other protocols in various aspects.
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Impact of weighting factor on cosine similarity based avalanche forecasting model
Статья научная
Snow avalanche is an inevitable issue that is faced by mankind residing near the hilly and the mountainous regions. It is a natural disaster that is frequently observed in such terrains. Prediction of these avalanches is crucial for wellbeing of mankind. The concept of using cosine similarity with nearest neighbour is an innovative idea in nearest neighbour based avalanche forecasting model. The results of the model are encouraging, but a need for a mechanism that will provide additional preference to the significant parameters is observed. Present work focuses on the application of weighting factor to the nearest neighbour model with cosine similarity. Use of weighting factor helps in further tuning of the forecasting model. Selection of weighting factors for each parameter is accomplished by considering the effect of each parameter on the avalanche activity. The accuracy of the model is gauged using performance measures - Critical Success Index and Bias and by the changes reflected in the confusion matrix. An increase of 0.1978 and 0.4167 is observed in the values of Critical Success Index after the application of the weights to the forecasting model for dataset combination I and II respectively. The proposed work is implemented using the snow and meteorological data for the Bahang region of Himachal Pradesh, India.
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Статья научная
A computer vision-based automated fire detection and suppression system for manufacturing industries is presented in this paper. Automated fire suppression system plays a very significant role in Onsite Emergency System (OES) as it can prevent accidents and losses to the industry. A rule based generic collective model for fire pixel classification is proposed for a single camera with multiple fire suppression chemical control valves. Neuro-Fuzzy algorithm is used to identify the exact location of fire pixels in the image frame. Again the fuzzy logic is proposed to identify the valve to be controlled based on the area of the fire and intensity values of the fire pixels. The fuzzy output is given to supervisory control and data acquisition (SCADA) system to generate suitable analog values for the control valve operation based on fire characteristics. Results with both fire identification and suppression systems have been presented. The proposed method achieves up to 99% of accuracy in fire detection and automated suppression.
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Implementation of Fair-exchange and Anonymous Online E-cash Protocol for E-commerce
Статья научная
In the world of internet, e-commerce is one of the most prominent sectors where user wants to shop and pay online for online products. E-cash is one of these payment methods. In e-cash, every time a unique string is generated for user so that user uses that string to pay for any online product. At the time of online purchasing a trust should be maintain between customers and merchant such that the product price which is going to pay by customer is fair or not, the merchant is indeed genuine to deliver the product after getting online payment or not. Trust issues are resolved by using fair exchange concept at the time of online purchasing. Anonymity is also a major concern; it means that true identity of users must be hidden from merchant. By keeping these issues in mind we proposed a protocol which ensures users anonymity by using e-cash payment method and fair exchange by using off-line TTP which invokes by customer when any dispute occur from merchant side. In this paper, we implement our proposed protocol and also analyze its performance and compare it with other protocol.
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Implementation of Improved Cryptography Algorithm
Статья научная
A network is an interconnected group of independent computing devices which uses a different set of protocols to communicate with each other independently and meaningfully. This communication should be carried out securely. Due to different attacks, this security sometimes gets compromised. So, to communicate securely different cryptography algorithms are used i.e., symmetric and asymmetric algorithms. Cryptography helps to achieve authentication, confidentiality, integrity, non-repudiation, and availability of data. Nowadays many algorithms provide security to data but these algorithms have various security flaws. To improve the strength of these algorithms, a new security protocol is designed using features of symmetric key and asymmetric key algorithms. The security principles can be achieved by AES and RSA algorithms. The main purpose of designing this algorithm is to provide better security to data in transit against passive as well as from active attacks. The new proposed hybrid algorithm is implemented in MATLAB R2019a. This algorithm will be analysed and compared on three parameters like avalanche effect, performance, and security against attacks. The proposed model will contribute towards improving the excellence of educators and academics, as well as increase competitiveness of educational programmes on cybersecurity among similar institutions in the EU countries.
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Implementation of MIMO and AMC Techniques in WiMAX Network based VANET System
Статья научная
Vehicular Ad-hoc Networks (VANETs) are expected to implement wireless technologies such as Dedicated Short Range Communications (DSRC) which is a category of Wi-Fi. Other candidates of long distance wireless technologies are cellular, satellite, and WiMAX. VANETs can be viewed as component of the Intelligent Transportation Systems (ITS). This paper presents the implementation of Multiple Inputs Multiple Outputs (MIMO) and Adaptive Modulation and Coding (AMC) techniques in WiMAX based Vehicular Ad-hoc Network. This designed system provides multiple radio channels in between transmitter and receiver for transmission and reception of the data by using the concept of MIMO technology. Also AMC provides the selection of different modulation techniques depending on the signal to noise ratio of the channel. These two techniques provide the significant change in the throughput, delay, jitter, and packet delivery ratio and packet loss ratio than existing vehicular ad-hoc network. WiMAX based VANET provides high speed, low cost per bit and large coverage area.
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Implementation of Palm Print Biometric Identification System Using Ordinal Measures
Статья научная
Personal identification is one of the most important requirements in all e-commerce and criminal detection applications. In this framework, a novel palm print representation method, namely orthogonal line ordinal features, is proposed. The palm print registration, feature extraction, palm print verification and palm print recognition modules are designed to manage the palm prints and the palm print database module is designed to store their palm prints and the person details in the database. The feature extraction module is proposed to extract the ordinal measurements for the palm prints. The verification module is designed to verify the palm print with the personal identification record. The recognition module is proposed to find out the relevant person associated with the palm print image. The proposed palm print recognition scheme uses the intensity and brightness to measure the ordinal measurement. The ordinal measures are estimated for the 4 x 4 regions of the palm print images.
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Implementation of Python Interoperability in Java through TCP Socket Communication
Статья научная
Programming language interoperability is highly desirable for a variety of reasons, such as the fact that if a programmer implements specific functionality that has previously been implemented in another language, the software component can simply be reused. Because they are particularly well-suited and efficient at implementing features, certain languages regularly arise to handle issue areas. There are numerous third-party programs available for a variety of languages. When programmers have experience with and preferences for several programming languages, collaboration on complex projects is easier. A range of techniques and methods have been used to handle various cross-language communication challenges. The importance of interoperability and cross-language communication between Java and Python via socket programming is examined in this research article through an empirical model of different execution environment paradigms that can help guide the development of improved approaches for integrating Python libraries with Java without the need for extra libraries or third-party libraries. The interoperability strategy benefits from the quality and availability of Python libraries in Java by cutting down on development time, maintenance needs, general usability, upkeep, and system integration without incurring additional costs. It is versatile to use this interoperability strategy since identical scripts are run in Java client contexts in the same way that they were used in Python. There are different Python modules used in the research article to exemplify and evaluate the expressions, built-in functions, strings, collections, data exploration, statistical data analysis using NumPy, SciPy, and Pandas, and Scikit-Learn for machine learning with linear regression.
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Статья научная
Data mining plays an important role in collecting information to make businesses more competitive in present business world. It is seen that the location of any business outlet is a major factor of its success. Establishing different business enterprises include a detail study of localities, people's income status living in those areas, and many other non-spatial factors. This paper is one such idea to suggest those locations for entrepreneurs, based on which they can decide on the where they can setup their business outlet. The proposed algorithm makes use of Delaunay triangulation for capturing spatial proximity and Bezier curves are used to model obstacles. The algorithm is implemented as Web application, which accepts the name of a place and collects data, form clusters and show the feasible locations of the service specified, considering the geographic irregularities and man-made obstructions. In this algorithm, spatial and non-spatial data related to a location are collected and the spatial clustering algorithm is initiated which works based on the obtained data. Clusters are formed based on the unique characteristics of each location. The experimental results are conducted on many different locations of India and in this paper results are shown for three places namely, Mysuru, Patna and Mumbai. The results have shown expected and exciting results.
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Статья научная
Individual user performance over ERP systems in Higher Education Institutions (HEIs) is less researched. Furthermore, the simultaneous impacts of Task-Technology Fit (TTF) on individual user (staff) performance over ERP systems in the context of Tanzania is little known. This study aimed at investigating both the direct and indirect impacts of TTF on staff performance over ERP systems in HEIs in Tanzania. This study was quantitatively designed using the snowball sampling technique by modifying D & M IS success model. The modified framework was subjected to a sample of 163 staff who are using the ERP system to accomplish business processes. The data collected was analyzed using Structure Equation Modelling (SEM). The results show that TTF has considerable direct and indirect impacts towards the performance of staff who are using ERP systems. This implies that whenever an enterprise is implementing an ERP system to improve its business process outcomes then a deep analysis has to be taken on three key elements of TTF i.e. task, technology and individual characteristics. The discussion and implications of impacts were also reported.
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Статья научная
The World Wide Web has immense resources for all kind of people for their specific needs. Searching on the Web using search engines such as Google, Bing, Ask have become an extremely common way of locating information. Searches are factorized by using either term or keyword sequentially or through short sentences. The challenge for the user is to come up with a set of search terms/keywords/sentence which is neither too large (making the search too specific and resulting in many false negatives) nor too small (making the search too general and resulting in many false positives) to get the desired result. No matter, how the user specifies the search query, the results retrieved, organized and presented by the search engines are in terms of millions of linked pages of which many of them might not be useful to the user fully. In fact, the end user never knows that which pages are exactly matching the query and which are not, till one check the pages individually. This task is quite tedious and a kind of drudgery. This is because of lack of refinement and any meaningful classification of search result. Providing the accurate and precise result to the end users has become Holy Grail for the search engines like Google, Bing, Ask etc. There are number of implementations arrived on web in order to provide better result to the users in the form of DuckDuckGo, Yippy, Dogpile etc. This research proposes development of a Meta search engine, called SEReleC that will provide an interface for refining and classifying the search engines’ results so as to narrow down the search results in a sequentially linked manner resulting in drastic reduction of number of pages.
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Improved Apriori Algorithm for Mining Association Rules
Статья научная
Association rules are the main technique for data mining. Apriori algorithm is a classical algorithm of association rule mining. Lots of algorithms for mining association rules and their mutations are proposed on basis of Apriori algorithm, but traditional algorithms are not efficient. For the two bottlenecks of frequent itemsets mining: the large multitude of candidate 2- itemsets, the poor efficiency of counting their support. Proposed algorithm reduces one redundant pruning operations of C_2. If the number of frequent 1-itemsets is n, then the number of connected candidate 2-itemsets is C-n, while pruning operations C_n. The proposed algorithm decreases pruning operations of candidate 2-itemsets, thereby saving time and increasing efficiency. For the bottleneck: poor efficiency of counting support, proposed algorithm optimizes subset operation, through the transaction tag to speed up support calculations. Algorithm Apriori is one of the oldest and most versatile algorithms of Frequent Pattern Mining (FPM). Its advantages and its moderate traverse of the search space pay off when mining very large databases. Proposed algorithm improves Apriori algorithm by the way of a decrease of pruning operations, which generates the candidate 2-itemsets by the apriori-gen operation. Besides, it adopts the tag-counting method to calculate support quickly. So the bottleneck is overcome.
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