Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1165
RDF link generation by exploring related links on the web of data
Статья научная
Interlinking RDF resources is a vital aspect of the Semantic Web technology. It is the basis of Linked Data that provides interlinked datasets on the web. One of the principles of Linked Data is interlinking resources from different data sources on the web. Data interlinking is a critical and challenging problem that every Linked Data generation applications face. Various approaches have been evolved for resolving this problem, but, for more massive datasets, it becomes almost indefinite time while linking similar or related resources. Linking RDF resources is like the problem of entity matching, record matching or duplicate resource detection. More or less they attempt to point to the same problem, but the RDF link generation is the task of finding related resources on the web. In this article, we present an approach for generating RDF links using the similarity measure between two RDF resources and by exploring associated relationships of the matched resources. The idea is to find related resources and link them with an RDF resource that is being generated.
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RFID Based Toll Deduction System
Статья научная
In this research paper we examine RFID based toll deduction system and how to make more efficient and perfect. The vehicle will be equipped with a radio frequency (RF) tag which will detect RF Reader located in on toll plaza. The amount will then automatically deduct from the bank account. This research paper can be considered scalable to implement in motor vehicles used today.
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Статья научная
Almost estimators are designed for the white observation noise. In the estimation problems, rather than the white observation noise, there might be actual cases where the observation noise is colored. This paper, from the viewpoint of the innovation theory, based on the recursive least-squares (RLS) Wiener fixed-point smoother and filter for the colored observation noise, newly proposes the RLS Wiener fixed-interval smoothing algorithm in linear discrete-time wide-sense stationary stochastic systems. The observation y(k) is given as the sum of the signal z(k)=Hx(k) and the colored observation noise (v_c)(k). The RLS Wiener fixed-interval smoother uses the following information: (a) the system matrix for the state vector x(k); (b) the observation matrix H; (c) the variance of the state vector; (d) the system matrix for the colored observation noise (v_c)(k); (e) the variance of the colored observation noise; (f) the input noise variance in the state equation for the colored observation noise.
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Статья научная
Vehicular Ad hoc Network (VANET) is formed to share information on a temporary basis between the vehicular nodes in a wireless medium. The routing information is used to discover the vehicles and the route has to be maintained to transfer the data. It may lead to link failure or breakage in the communication, if there is high network mobility and constrained topology arrangement. In case of failure, it may cause loss of data and delay in the network. So, to avoid breakage, the routing information is stored in traditional protocols like CBAODV and CS-CBAODV. Instead of storing routing information in client side, the idea of storing data in the remote side is taken into consideration to backup permanently. This remote server manages the data in client server which is to be delivered to vehicular node. After analyzing related protocols and simulators, a new reactive based routing protocol is designed in this research work and it is named as RS-CBAODV is used to handle routing information between vehicular node, Client side node (RST i.e. Road Side Terminals) and also in Remote side storage node. To analysis the performance of the proposed protocol, MOVE and NS2 simulator is used to compare both CS-CBAODV and RS-CBAODV protocols.
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Rainfall Events Evaluation Using Adaptive Neural-Fuzzy Inference System
Статья научная
We are interested in rainfall events evaluation by applying adaptive neural-fuzzy inference System. Four parameters: Temperature, relative humidity, total cloud cover and due point are the input variables for our model, each has 121 membership functions. The data is six years METAR data for Mashhad city [2007-2012]. Different models for Mashhad city stations were constructed depending on the available data sets. Among the overall 25 possibilities one model with one hundred twenty one fuzzy IF-THEN rules has chosen. The output variable is 0 (no rainfall event) or 1 (rainfall event). With comparing trained data with actual data, we could evaluate rainfall events about 90.5 percent. The results are in high agreement with the recorded data for the station with increasing in values towards the real time rain events. All implementation are done with MATLAB.
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Random Connection Based Scale-free Networks
Статья научная
Scale-free phenomenon has opened up a new network model as a special form of degree distribution. Preferential connection and growth constitutive are generally considered as the tow key factors in the formation of scale-free network. However, some network model with completely random connections instead of preferential connection can also generate scale-free networks, such as the protein interaction network in a cell. The article constructed such a random connection way: select an arbitrary neighbor vertex of a random vertex to add side. Through our simulation shows this model absolutely has the characteristics of scale-free networks. And the power-law distribution index [1+β^(-1)] of the new model is related to m which is the number of add edges every time. When m is sufficiently large, [1+β^(-1)] tends to quickly stable and the final size is 3. Then we use the Mean field theory analyzed theoretically, and get an analytic solution of degree distribution. Our study reveals that random connections without preferential strategy can also generate scale-free network.
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Random Handwritten CAPTCHA: Web Security with a Difference
Статья научная
It is hard to believe a web form without a CAPTCHA. The web survival in this cut-throat competition is impossible without the mechanisms for blocking spam-boats. The spam-boats have now been made intelligent enough to break through machine printed CAPTCHAs. Handwritten CAPTCHA image can be one solution. In this paper handwritten CAPTCHA images have been used to enhance the web security. Introduction of randomness at various stages is proven to increase the recognition complexity for the spam boats, whereas the ease of recognition of handwritten words by human beings eventually increases the usefulness of such CAPTCHA. The technique used to produce colored image of handwritten letters also has randomness associated with it. The proposed CAPTCHA images contain alphanumeric content, one word with letters and a number with handwritten numerals. CAPTCHA images developed using proposed technique have been tested across various OCRs and online available resources as well.
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Rapid earthquake alarm system and real-time automated action: application of multi-agent hardware
Статья научная
Earthquake is the most dangerous natural disaster in the whole era of human being life. Scientist efforts for predicting earthquake have no prolific result, so far. The earth complexity and geology structures are the main obstacles of these efforts. The importance of time at the occurrence of the earthquake has resulted in using powerful systems for real-time alarming and therefore lessening the casualties of the earthquake. In this paper we have designed a rapid earthquake alarm system and we have implemented it in parallel processing and continuous processing. We have tried to apply hardware intelligent agents for real-time and parallel processing of data and data fusion of sensors. By applying this technology, the performance of rapid earthquake alarm system will be improved. Through this improvement, the rapid and automated action of rapid earthquake alarm system can lead to reducing the effect of earthquake.
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Статья научная
The prevalence of automobile accidents as a major cause of violent deaths around the world has prompted researchers to develop an automated method for detecting them. The effectiveness of medical response to accident scenes and the chances of survival are influenced by the human element, underscoring the need for an automated system. With the widespread use of video surveillance and advanced traffic systems, researchers have proposed a model to automatically detect traffic accidents on video. The proposed approach assumes that visual elements occurring in a temporal sequence correspond to traffic accidents. The model architecture consists of two phases: visual feature extraction and temporal pattern detection. Convolution and recurrent layers are employed during training to learn visual and temporal features from scratch as well as from publicly available datasets. The proposed accident detection and alerting system using Convolution Neural Network models with Rectified Linear Unit and Softmax activation functions is an effective tool for detecting different types of accidents in real-time. The system of accident detection, integrated with the alerting mechanism for prompt medical assistance achieved high accuracy and recall rates.
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Real Time Efficient Scheduling Algorithm for Load Balancing in Fog Computing Environment
Статья научная
Cloud computing is the new era technology, which is entirely dependent on the internet to maintain large applications, where data is shared over one platform to provide better services to clients belonging to a different organization. It ensures maximum utilization of computational resources by making availability of data, software and infrastructure with lower cost in a secure, reliable and flexible manner. Though cloud computing offers many advantages, but it suffers from certain limitation too, that during load balancing of data in cloud data centers the internet faces problems of network congestion, less bandwidth utilization, fault tolerance and security etc. To get rid out of this issue new computing model called Fog Computing is introduced which easily transfer sensitive data without delaying to distributed devices. Fog is similar to the cloud only difference lies in the fact that it is located more close to end users to process and give response to the client in less time. Secondly, it is beneficial to the real time streaming applications, sensor networks, Internet of things which need high speed and reliable internet connectivity. Our proposed architecture introduced a new scheduling policy for load balancing in Fog Computing environment, which complete real tasks within deadline, increase throughput and network utilization, maintaining data consistency with less complexity to meet the present day demand of end users.
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Real Time Handwritten Marathi Numerals Recognition Using Neural Network
Статья научная
Character recognition is an important task in biometrics. This paper uses neural network for real time handwritten Marathi numerals recognition. We have taken 150 online Marathi numerals written in different styles by 10 different persons. Out of these, 50 numerals were used for training purpose and another 100 numerals were used for recognition purpose. The numerals undergo the preprocessing steps using image processing techniques and after character digitization it is further subjected to the multilayer backward propagation neural network for recognition purpose. The proposed research work gives recognition accuracy from 97% and to 100% for the different resolution of input vector.
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Real Time Implementation of Audio Source Localization on Blackfin ADSP-BF527 EZ-KIT
Статья научная
The present paper discusses the implementation of direction of arrival estimation using Incoherent Wideband Music algorithm. The direction of arrival of an audio source is estimated using two microphones plugged in “Line-in” input of a DSP development board. A solution to the problem of fluctuating estimation of the angle of arrival has been proposed. The solution consists on adding an audio activity detector before going on processing. Only voiced sound frames are considered as they fulfill the theoretical constraint of the used estimation technique. Furthermore, the latter operation is followed by integration over few frames. Only two sensors are used. For such a reduced number of sensors, the obtained results are promising.
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Real Time Object Tracking using FPGA Development Kit
Статья научная
The main idea of this work is object tracking using real time video processing. For this purpose we designed an embedded system that performs the object tracking algorithm for accurate tracking of defined object. The theme may be implemented for the security companies, sports and the armed forces to make them more equipped and advanced. The heart of the system is a Field Programmable Gate Arrays development kit. It controls the whole system by receiving the video signal from camera, processes it and sends the video signal to the Liquid Crystal Display or monitor. After receiving video of intended object, target selection is performed to select the target to track and then the tracking algorithm is implemented using image processing algorithms implemented using Field Programmable Gate Arrays development kit. We also interfaced the DC gear motor to control the movement of the camera in order to track the selected object. In order to design the standalone application we transformed our algorithm in Field Programmable Gate Array kit.
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Статья научная
In recent years, with an increasing number of requests, energy, power and temperature have been important keys in embedded systems, which decrease the lifetime of both CPUs and hard disks. The energy consumption is an important issue in computer systems, particularly real-time embedded systems. The frequency and the Revolutions Per Minute are major factors in the reduction of energy consumption in both processors and hard disk drives. Therefore, the main goal of this paper is to present a scheduling mechanism for a real time periodic task that can save more energy. This mechanism is based on increasing, as much as possible, the execution time of the CPU and/or the Read/Write time of the hard disk without passing the task deadline. This will be done by dynamically changing the CPU frequency and/or the RPM of hard disk. Our experimental results demonstrate that the proposed algorithm manages to lower energy consumption by an average of 25% and to reduce the number of missed tasks by 80%.
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Real-Time Air Pollutants Rendering based on Image Processing
Статья научная
This paper presents a new method for realistic real-time rendering of air pollutants based on image processing. The air pollutants’ variable density can create many shapes of mist what can add a realistic environment to virtual scene. In order to achieve a realistic effect, we further enhance thus obtained air pollution data getting from monitor in spatial domain. In the proposed method we map the densities of air pollutants to different gray levels, and visualize them by blending those gray levels with background images. The proposed method can also visualize large-scale air pollution data from different viewpoints in real-time and provide the resulting image with any resolution theoretically, which is very important and favorable for the Internet transmission.
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Real-Time Group Face-Detection for an Intelligent Class-Attendance System
Статья научная
The traditional manual attendance system wastes time over students’ responses, but it has worked well for small numbers of students. This research presents a real-time group face-detection system. This system will be used later for student class attendance through automatic student identification. The system architecture and its algorithm will be described in details. The algorithm for the system was based on analyzing facial properties and features in order to perform face detection for checking students’ attendance in real time. The classroom’s camera captures the students’ photo. Then, face detection will be implemented automatically to generate a list of detected student faces. Many experiments were adopted based on real time video captured using digital cameras. The experimental results showed that our approach of face detection offers real-time processing speed with good acceptable detection ratio equal to 94.73%.
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Real-Time Tree Counting Android Application and Central Monitoring System
Статья научная
In this study, a cloud-based android application and centralized tracking software were developed to perform an accurate and uninterrupted tree count across open lands. The application is used to count the desired number of trees and species at the same time. User-logged data and location information are saved in real-time to the application's cloud database. The application can work online and with offline mod. In cases where there is no internet connection, it inserts the data to the local SQLite database. After the connection is established, the pairing continues. It's used Google Firebase on the cloud server for data storage. The processing of target locations and GPS coordinates was developed with the Google Map Library. The tree counting application automatically picks up the user's current location when it is first opened. The counting starts after the tree and tree species that the user has selected from the menu. The software developed shows that tree counting is done simultaneously at the desired point. It also solves confusion caused by different tree species during the counting. We've received feedback from 100 people using the application. The users answered five questions. As a result, it is aimed to provide a comfortable transition between tree species and its users with its simple use to eliminate the complexity of counting and save time.
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Real-time Flame Rendering with GPU and CUDA
Статья научная
This paper proposes a method of flame simulation based on Lagrange process and chemical composition, which was non-grid and the problems associated with there grids were overcome. The turbulence movement of flame was described by Lagrange process and chemical composition was added into flame simulation which increased the authenticity of flame. For real-time applications, this paper simplified the EMST model. GPU-based particle system combined with OpenGL VBO and PBO unique technology was used to accelerate finally, the speed of vertex and pixel data interaction between CPU and GPU increased two orders of magnitude, frame rate of rendering increased by 30%, which achieved fast dynamic flame real-time simulation. For further real-time applications, this paper presented a strategy to implement flame simulation with CUDA on GPU, which achieved a speed up to 2.5 times the previous implementation.
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Real-time realistic telepresence using a 360° camera and a virtual reality box
Статья научная
This study focuses on the transmission of live 360 video using Ricoh Theta S which is transmitted to Android phone mounted in BoboVR. The proposed solution is to use a 360 camera that captures the scene in all direction and create an application which streams the captured 360 live video from Laptop (Server) into the Android Phone (Client). The Android phone’s IMU sensor is responsible for the corresponding viewport selected from the 360 environment. The viewport is subject for Stereoscopic SBS to show the 3D effect in accordance with the user’s perception The viewport is subject for Stereoscopic SBS to show the 3D effect in accordance with the user’s perception. A 3D video can be produced by applying the Stereogram SBS. Also, depth can be perceived due to the varying distance between the focal baseline and focal length.
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Recognition of Marrow Cell Images Based on Fuzzy Clustering
Статья научная
In order to explore the leukocyte distribution of human being to predict the recurrent leukemia, the mouse marrow cells are investigated to get the possible indication of the recurrence. This paper uses the C-mean fuzzy clustering recognition method to identify cells from sliced mouse marrow image. In our image processing, red cells, leukocytes, megakaryocyte, and cytoplasm can not be separated by their staining color, RGB combinations are used to classify the image into 8 sectors so that the searching area can be matched with these sectors. The gray value distribution and the texture patterns are used to construct membership function. Previous work on this project involves the recognition using pixel distribution and probability lays the background of data processing and preprocessing. Constraints based on size, pixel distribution, and grayscale pattern are used for the successful counting of individual cells. Tests show that this shape, pattern and color based method can reach satisfied counting under similar illumination condition.
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