Tarjoman M.,Islamic Azad University at Tehran |
Fatemizadeh E.,Sharif University of Technology |
Badie K.,Research Institute for ICT
Biomedical Engineering - Applications, Basis and Communications | Year: 2012
Content-based image retrieval (CBIR) has turned into an important and active potential research field with the advance of multimedia and imaging technology. It makes use of image features, such as color, texture and shape, to index images with minimal human intervention. A CBIR system can be used to locate medical images in large databases. In this paper we propose a CBIR system which describes the methodology for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the Adaptive neuro-fuzzy inference system (ANFIS) learning to retrieve similar images from database in two categories: normal and tumoral. A fuzzy classifier has been used, because of the uncertainty in the results of classifier and capacity of learning. ANFIS is a good candidate for our categorization problem. Our proposed CBIR system can locate a query image in the category of normal or tumoral images in the online retrieval part. Finally, using a relevance feedback, we improve the effectiveness of our retrieval system. This research uses the knowledge of the CBIR approach to the application of medical decision support and discrimination between the normal and abnormal medical images based on features. We present and compare the results of the proposed method with the CBIR systems used in recent works. The experimental results indicate that the proposed method is reliable and has high image retrieval efficiency compared with the previous works. © 2012 National Taiwan University.
Shourie N.,Islamic Azad University at Tehran |
Firoozabadi S.M.P.,Tarbiat Modares University |
Badie K.,Research Institute for ICT
2011 18th Iranian Conference of Biomedical Engineering, ICBME 2011 | Year: 2011
In this paper, we extracted scaling exponents of multichannel EEG signals recorded from two groups of artists and non-artists. We compared them to investigate the difference between artists and non-artists. The EEG signals were recorded while the subjects performed four tasks of visual perception, four tasks of mental imagery and at resting condition. We used Davies-Bouldin's index for evaluation of the feature space quality and the discrimination between the two groups. We observed a noticeable similarity in scaling exponents between visual perception and mental imagery. A considerable discrimination in scaling exponents was observed between the two groups at resting condition. However, the differentiation in scaling exponents between visual perceptions of the two groups was low. This result was observed in scaling exponents between the two groups' mental imageries, too. Thereby, the discrimination in scaling exponents between the two groups decreased with performing a same cognitive task. Additionally, we classified the scaling exponents which were related to the resting conditions and the visual perceptions of the two groups by the Neural Gas classifier. The average accuracies were 87.5% and 46.87%, respectively. These results confirmed the discrimination and the similarity in scaling exponents between resting conditions and visual perceptions of the two groups, respectively. © 2011 IEEE.
Dehghani A.,University of Tehran |
Ghassabi Z.,Islamic Azad University at Tehran |
Moghddam H.A.,K. N. Toosi University of Technology |
Moin M.S.,Research Institute for ICT
Eurasip Journal on Image and Video Processing | Year: 2013
This paper presents a new human recognition method based on features extracted from retinal images. The proposed method is composed of some steps including feature extraction, phase correlation technique, and feature matching for recognition. In the proposed method, Harris corner detector is used for feature extraction. Then, phase correlation technique is applied to estimate the rotation angle of head or eye movement in front of a retina fundus camera. Finally, a new similarity function is used to compute the similarity between features of different retina images. Experimental results on a database, including 480 retinal images obtained from 40 subjects of DRIVE dataset and 40 subjects from STARE dataset, demonstrated an average true recognition accuracy rate equal to 100% for the proposed method. The success rate and number of images used in the proposed method show the effectiveness of the proposed method in comparison to the counterpart methods. © 2013 Dehghani et al.
Tarjoman M.,Islamic Azad University at Abhar |
Fatemizadeh E.,Sharif University of Technology |
Badie K.,Research Institute for ICT
Journal of Medical Engineering and Technology | Year: 2013
Content-based image retrieval (CBIR) has been one of the most active areas of research. The retrieval principle of CBIR systems is based on visual features such as colour, texture and shape or the semantic meaning of the images. A CBIR system can be used to locate medical images in large databases. This paper presents a CBIR system for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the support vector machine (SVM) learning method. This system can retrieve similar images from the database in two groups: normal and tumoural. This research uses the knowledge of the CBIR approach to the application of medical decision support and discrimination between the normal and abnormal medical images based on features. This study presents and compares the results of the proposed method with the CBIR systems used in recent works. The experimental results indicate that the proposed method is reliable and has high image retrieval efficiency compared with the previous works. © 2013 Informa UK, Ltd.
Hassanian-Esfahani R.,Research Institute for ICT |
Kargar M.-J.,University of Tehran
2016 2nd International Conference on Web Research, ICWR 2016 | Year: 2016
This article is a review on news retrieval and mining research areas in recent years based on a qualitative approach. It addresses news retrieval and mining in four main categories of News Retrieval and Extraction, News Content Analysis, News Propagation Analysis, and News Visualization. Each indicated category entails various research areas that have been investigated through several studies. This study depicts the immense extent of news retrieval and mining, the interconnected methods, tools, and theoretical foundations as well as the evaluation methods and the results. The study helps to gain a better understanding of news mining research areas. © 2016 IEEE.
Nazaktabar H.,University of Tehran |
Badie K.,Research Institute for ICT |
Ahmadabadi M.N.,University of Tehran
Wireless Networks | Year: 2016
In many real world applications of wireless sensor networks, it is enough for the sensors to send just an approximation of their observations. In these networks dual prediction scheme (DPS)—including two predictive models one in the sensor side and its copy in the sink side—is widely used. In DPS, the total data transmission through the network is a function of the model’s prediction power and the size of its free parameters. In this paper, a DPS using a reinforcement learning based signal predictor (RLSP) algorithm is proposed. RLSP learns the environment’s signal and builds the predictive model gradually based on its experiences. At the moment the model gets invalid, RLSP only needs to learn and transmit the environmental data of that moment. As a result, the amount of data transmission in the network and consequently energy consumption is very low. The simulation results on 16 benchmarking signals and comparison with time series-based DPSs confirm these properties of RLSP. © 2016 Springer Science+Business Media New York
Samimi H.,Research Institute for ICT
IET Communications | Year: 2011
Transmit laser selection (TLS) diversity scheme has been proposed recently for free-space optical communication systems and its bit error rate (BER) performance has been investigated over K-distributed turbulence channels based on lengthy simulations. Moreover, for a limiting case of strong turbulence conditions that have been modelled by negative exponential distribution, a closed-form expression for the average BER has been presented in the open technical literature. In this study, first a novel approximate analytical expression is derived for the probability density function (PDF) of the resulting channel irradiance corresponding to a TLS diversity scheme over the K channel. The approximated PDF accurately estimates the statistics of the channel irradiance over a wide range of channel conditions. Then, based on the derived PDF, an analytical closed-form expression is presented for the average BER, which can be used to estimates the BER of the system very accurately over K-distributed turbulence channels without resorting to lengthy simulations. Additionally, based on the derived analytical results, the effect of using laser pulse shape with increased peak-to-average optical power ratio on the system performance is investigated. Numerical results are further demonstrated to confirm the analytical results. © 2011 The Institution of Engineering and Technology.
Dehghani A.,K. N. Toosi University of Technology |
Moghaddam H.A.,K. N. Toosi University of Technology |
Moin M.-S.,Research Institute for ICT
Eurasip Journal on Image and Video Processing | Year: 2012
In this article, we propose a new method for localizing optic disc in retinal images. Localizing the optic disc and its center is the first step of most vessel segmentation, disease diagnostic, and retinal recognition algorithms. We use optic disc of the first four retinal images in DRIVE dataset to extract the histograms of each color component. Then, we calculate the average of histograms for each color as template for localizing the center of optic disc. The DRIVE, STARE, and a local dataset including 273 retinal images are used to evaluate the proposed algorithm. The success rate was 100, 91.36, and 98.9%, respectively. © 2012 Dehghani et al; licensee Springer.
Najafi E.,Research institute for ICT |
Baraani A.,University of Isfahan
Journal of Theoretical and Applied Information Technology | Year: 2012
Enterprise architecture (EA) is a new approach that organizations should practice to align their business strategic objectives with information and communication technology (ICT). Enterprise Architecture encompasses a collection of different views and aspects of the enterprise which constitute a comprehensive overview. Such an overview cannot be well-organized regardless of incorporating a logical structure called Enterprise Architecture Framework (EAF). EAF presents a comprehensive and transparent map of an organization showing how all organization elements (business and IT) work together to achieve defined business objectives. It clarifies the way in which these elements support the business processes of the organization. Several distinctive EAF have been proposed till now, the main challenges any of these EAF faced are (1) defining process is heavy, prolonged and tedious (2) Keeping EA artifacts up-to-date is an awkward work. These challenges make the artifacts of EA useless and unreliable. A number of researchers and practitioners try to eliminate these challenges by using Service Oriented (SO) paradigm with common and famous EAF like Zachman and FEAF. But none of them completely clarify how SO practices with EA concepts combination may be realized and what are the important elements of it, they just show an abstract mapping between these two concepts and state that this combination can be possible. In this article we try to present a service oriented EAF (SOEAF) to eliminate aforementioned challenges and elaborated this framework in details. CEA Framework involves a SO Roadmap that is completely compatible with ITIL and a Classification Schema that cover all aspects of organization, these aspects categorize according to Purpose, Pattern or Practice, Policy, Stakeholder and Resource. We believe that by using the proposed SOEAF referred to as CEA Framework, created enterprise architecture is flexible and agile enough to define rapidly and sense the environment quickly then, adapt and adopt business and information changes appropriately. © 2005 - 2012 JATIT & LLS. All rights reserved.
Khyavi M.H.,Research Institute for ICT |
Rahimi M.,Research Institute for ICT
SIGMIS-CPR 2015 - Proceedings of the 2015 ACM SIGMIS Conference on Computers and People Research | Year: 2015
Information security management (ISMS) subject is a new area which has been discussed in various companies and organizations and many large and small security companies also are thinking of investigating on this topic. However experience has shown that imitation of a scientific and technological issue and its implementation at the national level not only showed best real effect of that ever(but also) has caused a huge waste of resources. In this paper, we have an idea for localization of ISMS which in regard to ISO standards and importance of this subject, prepares the facility and best area for research and work on ISMS. In this essay we introduce a new circle which cover a new level in ISMS subject. Copyright 2015 ACM.