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آخرین شماره

No 17
Vol. 5 No. 1
Winter 2017
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In this paper a new digital background calibration method for successive approximation register analog to digital converters is presented. For developing, a perturbation signal is added and also digital offset is injected. One of the main advantages of this work is that it is completely digitally and eliminates the nonlinear errors between analog capacitor and array capacitors due to converter’s capacitors mismatch error by correcting the relative weights. Performing of this digital dithering method does not require extra capacitors or double independent converters and it will eliminate mismatches caused by these added elements. Also, No extra calibration overhead for complicated mathematical calculation is needed. It unlike split calibration, does not need two independent converters for production of two specified paths and it just have one capacitor array which makes it possible with simple architecture. Furthermore, to improve DNL and INL and correct the missing code error, sub radix-2 is used in the converter structure. Proposed calibration method is implemented by a 10 bit, 1.87-radix SAR converter. Simulation results with MATLAB software show great improvement in static and dynamic characteristics in applied analog to digital converter after calibration. So, it can be used in calibration of successive approximation register analog to digital converters.
Ebrahim Farshidi - Shabnam Rahbar
DOI : 0
کلمات کلیدی : SAR;converter ، calibration ، perturbation ، subs radix-2 ، DNL and INL
This paper presents a reliable model for mobile codes in distributed networks, which represents reliable mobile agent execution. The model ensures non-blocking mobile agent execution and forces the once property without relying on correct fault detection. A mobile agent execution is blocking if a fault of agent prevents the agent from continuing in its execution. The once problem is related to non-blocking in the sense that solutions to the latter may lead to multiple executions of the mobile agent. A solution to reliable mobile agent execution needs to ensure both the non-blocking and once properties. The analytical results show new theoretical perceptions into the statistical behaviors of mobile agents and provide useful tools for executing mobile agents in networks. The results show that agents' behavior is influenced by places' characteristics and the agents' behavior can be managed to network. In this paper, we analyzed the average time consuming of mobile agents between two places. The approach, Fault-Tolerant approach for mobile codes offers a user-transparent fault tolerance which can be selected by the user for every single application given to the environment. Thereby, the user can decide for every application weather it has to be treated fault-tolerant or not. We proposed a reliable execution model of mobile codes and analyzed the life expectancy, including the average time consuming of mobile agents between two places, the average number of places agents will visit, and the agents' life expectancy.
Hodjat Hamidi - Maryam Parvini
DOI : 0
کلمات کلیدی : Mobile Computing ، Mobile Code ، Computer Network ، Computing Paradigms
Sparse coding is an unsupervised method which learns a set of over-complete bases to represent data such as image, video and etc. In the cases where we have some similar images from the different classes, using the sparse coding method the images may be classified into the same class and devalue classification performance. In this paper, we propose an Affine Graph Regularized Sparse Coding approach for resolving this problem. We apply the sparse coding and graph regularized sparse coding approaches by adding the affinity constraint to the objective function to improve the recognition rate. Several experiments has been done on well-known face datasets such as ORL and YALE. The first experiment has been done on ORL dataset for face recognition and the second one has been done on YALE dataset for face expression detection. Both experiments have been compared with the basic approaches for evaluating the proposed method. The simulation results show that the proposed method can significantly outperform previous methods in face classification. In addition, the proposed method is applied to KTH action dataset and the results show that the proposed sparse coding approach could be applied for action recognition applications too.
Mohsen Nikpour - Mohammad Reza Karami-Mollaei - Reza Ghaderi
DOI : 0
کلمات کلیدی : Sparse Coding ، Manifold Learning ، Graph Regularization ، Affinity ، Image Representation ، Image Classification
Nowadays, routers are the main backbone of computer networks specifically the Internet. Moreover, the need for high-performance and high-speed routers has become a fundamental issue due to significant growth of information exchange through the Internet and intranets. On the other hand, flexibility and configurability behind the open-source routers has extended their usage via the networks. Furthermore, after assigning the last remaining IPv4 address block in 2011, development and improvement of IPv6-enabled routers especially the open-sources has become one of the first priorities for network programmers and researchers. In IPv6 because of its 128-bits address space compared to 32-bits in IPv4, much more space and time are required to be stored and searched that might cause a speed bottleneck in lookup of routing tables. Therefore, in this paper, Bird as an example of existing open source router which supports both IPv4 and IPv6 addresses is selected and Bloom-Bird (our improved version of Bird) is proposed which uses an extra stage for its IP lookups using Bloom filter to accelerate IP lookup mechanism. Based on the best of our knowledge this is the first application of Bloom filter on Bird software router. Moreover, false positive errors are handled in an acceptable rate because Bloom-Bird scales its Bloom filter capacity. The Bloom-Bird using real-world IP prefixes and huge number of inserted prefixes into its internal FIB (Forwarding Information Base), shows up to 61% and 56% speedup for IPv4 and IPv6 lookups over standard Bird, respectively. Moreover, using manually generated prefix sets in the best case, up to 93% speedup is gained.
Bahram Bahrambeigy - Mahmood Ahmadi - Mahmood Fazlali
DOI : 0
کلمات کلیدی : Bird ، Bloom Filter ، Forwarding Information Base ، IPv4 ، IPv6 ، Open Source Routers
In this paper, we propose an efficient noise robust edge detection technique based on odd Gaussian derivations in the wavelet transform domain. At first, new basis wavelet functions are introduced and the proposed algorithm is explained. The algorithm consists of two stage. The first idea comes from the response multiplication across the derivation and the second one is pruning algorithm which improves fake edges. Our method is applied to the binary and the natural grayscale image in the noise-free and the noisy condition with the different power density. The results are compared with the traditional wavelet edge detection method in the visual and the statistical data in the relevant tables. With the proper selection of the wavelet basis function, an admissible edge response to the significant inhibited noise without the smoothing technique is obtained, and some of the edge detection criteria are improved. The experimental visual and statistical results of studying images show that our method is feasibly strong and has good edge detection performances, in particular, in the high noise contaminated condition. Moreover, to have a better result and improve edge detection criteria, a pruning algorithm as a post processing stage is introduced and applied to the binary and grayscale images. The obtained results, verify that the proposed scheme can detect reasonable edge features and dilute the noise effect properly.
Ehsan Ehsaeian
DOI : 0
کلمات کلیدی : Wavelet Transform ، Edge Detection ، Gaussian Filter ، Multiscale Analysis ، Noise Removal ، Gaussian Bases ، Wavelet Function Derivation ، Admissibility Condition ، Edge Criteria ، N-connected Neighborhoo
Clutter usually has negative influence on the detection performance of radars. So, the recognition of clutters is crucial to detect targets and the role of clutters in detection cannot be ignored. The design of radar detectors and clutter classifiers are really complicated issues. Therefore, in this paper aims to classify radar clutters. The novel proposed MLP-based classifier for separating radar clutters is introduced. This classifier is designed with different hidden layers and five training algorithms. These training algorithms consist of Levenberg-Marquardt, conjugate gradient, resilient back-propagation, BFGS and one step secant algorithms. Statistical distributions are established models which widely used in the performance calculations of radar clutters. Hence In this research, Rayleigh, Log normal, Weibull and K-distribution clutters are utilized as input data. Then Burg’s reflection coefficients, skewness and kurtosis are three features which applied to extract the best characteristics of input data. In the next step, the proposed classifier is tested in different conditions and the results represent that the proposed MLP-based classifier is very successful and can distinguish clutters with high accuracy. Comparing the results of proposed technique and RBF-based classifier show that proposed method is more efficient. The results of simulations prove that the validity of MLP-based method.
Mohammad Akhondi Darzikolaei - Ataollah Ebrahimzadeh - Elahe Gholami
DOI : 0
کلمات کلیدی : Clutter ، Classifier ، Feature ، Neural Network ، Radar
Speech emotion signals are the quickest and most neutral method in individuals’ relationships, leading researchers to develop speech emotion signal as a quick and efficient technique to communicate between man and machine. This paper introduces a new classification method using multi-constraints partitioning approach on emotional speech signals. To classify the rate of speech emotion signals, the features vectors are extracted using Mel frequency Cepstrum coefficient (MFCC) and auto correlation function coefficient (ACFC) and a combination of these two models. This study found the way that features’ number and fusion method can impress in the rate of emotional speech recognition. The proposed model has been compared with MLP model of recognition. Results revealed that the proposed algorithm has a powerful capability to identify and explore human emotion.
Sara Motamed - Saeed Setayeshi - Azam Rabiee - Arash Sharifi
DOI : 0
کلمات کلیدی : Speech Emotion Recognition ، Mel Frequency Cepstral Coefficient (MFCC) ، Fixed and Variable Structures Stochastic Automata ، Multi-constraint ، Fusion Method
Wireless sensor networks (WSNs) are formed by numerous sensors nodes that are able to sense different environmental phenomena and to transfer the collected data to the sink. The coverage of a network is one of the main discussion and one of the parameters of service quality in WSNs. In most of the applications, the sensor nodes are scattered in the environment randomly that causes the density of the nodes to be high in some regions and low in some other regions. In this case, some regions are not covered with any nodes of the network that are called covering holes. Moreover, creating some regions with high density causes extra overlapping and consequently the consumption of energy increases in the network and life of the network decreases. The proposed approach causes an increase in life of the network and an increase in it through careful selection of the most appropriate approach as cluster head node and form clusters with a maximum length of two steps and selecting some nodes as redundancy nodes in order to cover the created holes in the network. The proposed scheme is simulated using MATLAB software. The function of the suggested approach will be compared with Learning Automata based Energy Efficient Coverage protocol (LAEEC) approach either. Simulation results shows that the function of the suggested approach is better than LAEEC considering the parameters such as average of the active nodes, average remaining energy in nodes, percent of network coverage and number of control packets.
Amir Pakmehr - Ali Ghaffari
DOI : 0
کلمات کلیدی : Wireless Sensor Networks ، Clustering ، Network Coverage ، Covering Holes ، Energy Efficient

معرفي نشريه

صاحب امتیاز :Ict Research Institute at ACECR
مدیر مسئول :Habibollah Asghari
سردبیر :Masood Shafiei
هیئت تحریریه :
Abdolali Abdipoor
Mahmoud Naghibzadeh
Zabih Ghasemlooy
Mahmoud Moghavemi
Aliakbar Jalali
Ramazan Ali Sadeghzadeh
Hamidreza Sadegh Mohammadi
Saeed Ghazimaghrebi
Ahmad Khademzadeh
Shaban Elahi
Abbasali Lotfi
Alireza Montazemi
Ali Mohammad Djafari
Rahim Saeidi
شاپا :2322-1437
شاپا الکترونیکی :2345-2773

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