en
jalali
1391
12
1
gregorian
2013
3
1
5
1
online
1
fulltext
fa
A Mobility Based Cooperative MAC Protocol for Wireless Networks
In this paper, we propose a cooperative MAC protocol based on IEEE 802.11 standard for wireless ad hoc networks. In this protocol, a low data rate direct transmission link is replaced by two faster transmission links using an appropriate relay node. We investigate the challenges and issues of this problem by designing an efficient MAC scheme to improve the network throughput by finding the best relay node. Assuming that the relay node is fixed for a given interval time, the effect of nodes’ mobility in finding the best relay node is investigated. The proposed scheme introduces a solution to improve the throughput and preserve the cooperation stability in the mobile ad hoc networks. To validate the protocol, we compare the results with CoopMAC protocol. Simulation results show that the proposed protocol outperforms the CoopMAC protocol in terms of throughput.
Cooperative, Diversity, Relay, Helper selection, Throughput, MAC
1
9
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-134&slc_lang=en&sid=1
2018/10/7
1397/7/15
2018/10/7
1397/7/15
Abdorasoul
Ghasemi
003194753284600458
003194753284600458
Yes
Mina
Fahimi
003194753284600459
003194753284600459
No
fa
Non-Homogeneous Cluster Head Selection for Energy-Aware Hierarchical Routing Protocols in Wireless Sensor Networks
In Wireless Sensor Networks (WSNs), sensor nodes are equipped with a limited energy battery. Energy consumption is a very challenging field in WSN. In this paper, we modify the Low Energy Aware Clustering Hierarchy (LEACH) and the Extended LEACH (XLEACH) protocols to increase the lifetime of the network. The main difference of our protocol is based on non-homogenous probability of Cluster Head (CH) selection. We consider a virtual reference node in the protocol. Each node chooses its probability of CH selection properly so that its energy consumption would be close to the energy consumption of the reference node. Our simulation illustrate that the lifetime of the network increases considerably without increasing the complexity of the protocols. According to the simulations, this method makes energy consumption more efficient than the LEACH or XLEACH, and consequently prolongs the network lifetime. Moreover, the modification does not affect the delay in the protocols.
Wireless Sensor Network (WSN), Routing, Energy efficiency, Network Lifetime, Cluster Head Selection
11
18
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-135&slc_lang=en&sid=1
2018/10/72018/10/7
1397/7/15
2018/10/72018/10/7
1397/7/15
Reza
Saadat
003194753284600460
003194753284600460
Yes
Mahmood
Saadat
003194753284600461
003194753284600461
No
fa
A Semi-Supervised Method for Multimodal Classification of Consumer Videos
In large databases, lack of labeled training data leads to major difficulties in classification process. Semi-supervised algorithms are employed to suppress this problem. Video databases are the epitome for such a scenario. Fortunately, graph-based methods have shown to form promising platforms for semi-supervised video classification. Based on multimodal characteristics of video data, different features (SIFT, STIP, and MFCC) have been utilized to build the graph. In this paper, we have proposed a new classification method which fuses the results of manifold regularization over different graphs. Our method acts like a co-training method that tries to find the correct label for unlabeled data during its iterations. But, unlike other co-training methods, it takes into account the unlabeled data in the classification process. After manifold regularization, data fusion is doneby a ranking method which improves the algorithm to become competitive with supervised methods. Our experimental results, run on the CCV database, show the efficiency of the proposed classification method.
Semi-supervised learning, co-training, video classification, multimodal features
19
26
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-136&slc_lang=en&sid=1
2018/10/72018/10/72018/10/7
1397/7/15
2018/10/72018/10/72018/10/7
1397/7/15
Mahmood
Karimian
003194753284600462
003194753284600462
Yes
Mostafa
Tavassolipour
003194753284600463
003194753284600463
No
Shohreh
Kasaei
003194753284600464
003194753284600464
No
fa
Evaluating the Effect of Learner’s Knowledge, Background, and Attention’s on Trust Using Open Learner Model
The learner model is a distinctive characteristic of any Adaptive Educational Systems (AES) and Intelligent Tutoring Systems (ITS). The learner model not only is the base of adaptation in AES and ITS systems, but also in some way is used for assessment of learners. Hence, the accuracy of learner model is an important issue. In Open Learner Model (OLM), the learner’s belief can change the learner model. Regarding this problem, it should be determined that how much a system can trust in learner’s belief about his/her model and which characteristics of a learner affect on correctness of learner belief. In this paper we investigate if learner knowledge, background and attention have effect on system trust in Open Learner Modeling. We choose these parameters according to their importance in the learning system. To obtain learner’s knowledge and background multiple choice questions are utilized. The value of attention is estimated by Toulouse-Pieron Test. To evaluate the effect of mentioned characteristics of learner the chi-square distribution is used. The obtained results indicate that the value of learner’s knowledge, background and attention affect on trust value.
learner model, Open learner Model, Learner Model Parameters, Trust value
27
37
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-137&slc_lang=en&sid=1
2018/10/72018/10/72018/10/72018/10/7
1397/7/15
2018/10/72018/10/72018/10/72018/10/7
1397/7/15
Ahmad
A. Kardan
003194753284600465
003194753284600465
Yes
Somayeh
Modaberi
003194753284600466
003194753284600466
No
Seyede Fatemeh
Noorani
003194753284600467
003194753284600467
No
fa
Statistical Machine Translation (SMT) for Highly-Inflectional Scarce-Resource Language
Statistical Machine Translation (SMT) is a machine translation paradigm, in which translations are generated on the base of statistical models. In this system, parameters are derived from an analysis of a parallel corpus, and SMT quality depends on the ability of learning word translations. Enriching the SMT by a suitable morphology analyser decreases out of vocabulary words and dictionary size dramatically. This could be more considerable when it deals with a highly-inflectional, low-resource, language like Persian. Defining a suitable granularity for word segment may improve the alignment quality in the parallel corpus. In this paper different schemes and word’s combinations segments in a SMT’s experiment from Persian to English language are prospected and the best one-to-one alignment, which is called En-like scheme, is proposed. By using the mentioned scheme the translation’s quality from Persian to English is improved about 3 points with respect to BLEU measure over the phrase-based SMT.
Statistical Machine Translation, Segmentation Schemes, Lexical Granularities, Morpheme, Persian Language
39
52
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-138&slc_lang=en&sid=1
2018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
2018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
Saman
Namdar
003194753284600468
003194753284600468
Yes
Hesham
Faili
003194753284600469
003194753284600469
No
Shahram
Khadivi
003194753284600470
003194753284600470
No
fa
Persian to English Personal Name Transliteration Based On the Persian Web Contents
Personal names are out of dictionary words which are usually primary keys in the web queries. Converting a personal name from source language to target language is transliteration. In this paper, we propose a novel algorithm for transliterating a Persian personal name to an English name. This method consists of two stages. At first, in the offline stage, a graph is made by processing Persian web contents. In this graph, names are related based on their neighboring in the web pages. Afterwards, in online stage, each name is transliterated using this graph and name frequencies. Experimental results show that the algorithm is effective in personal name transliteration.
Transliteration, Cross Language Information Retrieval, Machine Translation, Personal names, Graph
53
60
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-139&slc_lang=en&sid=1
2018/10/72018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
2018/10/72018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
Zohre
Haghollahi
003194753284600471
003194753284600471
Yes
Ali Mohammad
Zareh Bidoki
003194753284600472
003194753284600472
No
Alireza
Yari
003194753284600473
003194753284600473
No
fa
A New Blind Signature Scheme Based on Improved ElGamal Signature Scheme
Blind signature scheme, an important cryptographic primitive, is applicable in protocols that guarantee the anonymity of the participants. This scheme is increasingly used in untraceable payment and electronic voting systems. In this paper we improve ElGamal signature scheme and then we propose a new blind signature based on that. ElGamal signature scheme has an important advantage into RSA signature scheme which is non-deterministic and means that there are many valid signatures for any given message. This property also exists in our new blind signature scheme. Having low computational complexity for signature requester and the signer is one of the advantages of the newly developed scheme and as a result makes it very efficient.
digital signature, blind signature, ElGamal digital signature, RSA, electronic payment system, electronic voting system
61
65
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-140&slc_lang=en&sid=1
2018/10/72018/10/72018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
2018/10/72018/10/72018/10/72018/10/72018/10/72018/10/72018/10/7
1397/7/15
Ali
Zaghian
003194753284600474
003194753284600474
Yes
Mohsen
Mansouri
003194753284600475
003194753284600475
No