IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY
Year:2018 | Volume:10 | Issue:35-36|Papers Count:6

In spite of the success of the imperialist competitive algorithm (ICA) in solving optimization problems, this algorithm still suffers from frequent entrapment in the local minimum and low rate convergence. In this paper, a new version of this algorithm, called the modified chaotic orthogonal imperialist competitive algorithm (COICA), is proposed. In the absorption policy of our proposed version, each colony searches the space of movement toward to imperialist through the definition of a new orthogonal vector. The probability of choosing powerful empires is also defined through the Boltzmann distribution function and selection is done through the roulette wheel method. The proposed algorithm is used to training of multilayer perceptron neural network (MLP) to classify standard data sets, including ionosphere and sonar. The K-Fold cross validation method was used to performance evaluation of this algorithm and generalizability assessment of the trained neural network with the proposed version. The results obtained from the simulations confirm reduction of neural network training error and generalizability improvement of our proposed algorithm.

Many of processing cores integrated on chip have high speed; Photonic Network-on-Chips is one of the simple methods to solve addressing problem in huge interconnection networks. For this reason, multiprocessing chips with high performance and high bandwidth are needed in future. Photonic Network-on-Chips is a new generation of Network-on-Chip which can solve the traditional networks limitations and has many advantages such as high communication bandwidth, low transfer latency and power consumption. On the other hand, Photonic Network-on-Chips has many challenges. Routing photonic data on photonic layer is one of the important challenges, because the path selection has influence to optical loss factor. In this paper, deadlock free adaptive turning models routing algorithm, circuit switching and different traffic pattern to reduce optical loss on photonic layer with 5port deadlock free router and 2-D Mesh topology is proposed. Finally, we compare our simulation result with similar algorithm such as dimension order XY routing algorithm and the resulted improvement is shown.

Nowadays, smart home is considered one of the most important applications of the Internet of Things (IoT) which provides efficiency, home security, energy & cost saving to everyone’ s life. Despite the advantages of this technology, privacy and security concerns require more considerations. IoT-A is considered in this paper as a reference architecture that follows evaluating protocols, making sure from the consistency of things and protocols, and providing a comprehensive solution for different applications of IoT. This paper works on IoT-A and targets this challenge in IoT and smart home, and proposes a security architecture to improve security in all levels including design, implementation, and protocols. This paper uses the term Security Framework as a way to identify all technologies, procedures, software, and other components for providing security in smart homes. At first, this paper studies all vulnerabilities and threats of the reference architecture, and then propose an improved model to satisfy all security requirements. The proposed model reasonably satisfies all security and privacy requirements of smart homes based on IoT-A.

Recognition of hand writing on paper, on display or on air is an important challenge in computer vision. Air-writing recocognition is especially difficult due to three dimentionality of space. In this research work the aim is recognizing persian digits which are written in air in front of a Kineckt sensor using a fingertip and the sensor can detect the digit using its depth image. For hand and fingertip segmentation we use K-means algorithm. To extract the features we use a novel method called slope variation detection, and to classify the features Hidden Markov Models (HMM) is used. Recognition rate of Persian digits using a local database with 10 times mutual validation is 96%. This novel method was compared with some other similar methods in the literature. The results confirm relative priority of the proposed method.

ISMS is not a standalone concept. It has its derivatives from various different international bodies and standards, Included ISO 17799/BS17799-ISO17799 which are for the IT security industry, and ISO 9000 which is for the TQM industry. Effective factors on ISIM are classifiable as two general categories of soft and hard. Analyzing the current security conditions of information and a detailed overall view of it is essential to practically stabilize a successful ISMS. Thus, the project’ s main goal is to identify and prioritize the effective parameters to reach a better stage of planning and focus. The Statistical society of this study is academic experts, managers, and employees of IT department. In this study, the social security organization (SSO) branches in the province of Guilan is case study, and FAHP is used for analyzing the data. The results showed that soft factors, i. e., management, cultural & social factors, are more important than hard factors, i. e., technical, technological & financial factors, in ISMS, and management factors are also most important than the two other factors, ie cultural & social factors.

With the advent of web 2. 0 and social networks users and consumers share their opinions and thoughts about various products and services. It is very important for producers and vendors to capture and analyze these user generated contents and extract information such as pros and cons of their products as compared to products from competitors. Negative opinions and criticizing reviews help vendors to enhance their products or services and, hence improve their market shares. This research aims to extract opinions and reviews containing a report of failure or weakness in a product. A random forest initially classifies and filters opinion texts potentially containing a fault report. Later, an LDA (latent Dirichlet allocation) based topic modeler summarizes the reports by their source and severity. Experiments over a reasonably large set of reviews from Amazon web site reveal that random forests trained with as small set of labeled samples performs well in detecting failure cases. Summary results by LDA conceptually groups different failure types and identifies their sources and, as a byproduct, suggests widely used textual patterns in fault reports.