The directional sensor networks (DSNs) are mainly focused to prolong the network lifetime and to optimize the energy consumption of sensors. The number of sensors deployed in an environment is much higher than those required for providing the coverage; therefore, the energy-aware methods are needed to select the sensors. Coverage is considered a major problem in DSNs and is a criterion for quality of service (QOS).In this regard, the sensor scheduling method has been discussed by researchers to prolong the sensor lifetime in a network. The present paper proposes an NSGAII-based algorithm to solve the sensors 'scheduling. This paper aimed at finding a practical solution in solving the multi-objective problems by using the multi-objective evolutionary algorithm method. There are two parameters presented for evaluating the solutions, including the number of sensors, the target coverage. To confirm the high performance of the proposed algorithm, it was compared with the recently presented algorithm. According to the simulation findings, the algorithm had better results in the comparison parameters. Manuscript profile

Voting system as one of the bases of electoral regulation plays a drastic role in attracting citizens’ participation in administration of election process, due to direct interaction with voters. The Islamic Republic of Iran with a religious-republic-based regime, has continually administrated elections in different levels of country management after Islamic revolution. One of the challenges that serially arises in handling varieties of elections in different periods is the problem of invalid or void ballots which causes decrement of valid ballots’ final count, and consequently, degrades the desirability of elections’ statistical outcomes. With the goal of reducing impacts of aforementioned challenge, this research proposes a score-distribution-based voting system with feasibility of assigning score to “plurality-selected” which provides the conditions of fair selection based on preferences for voters by allowing arbitrary score distribution among candidates. Also, the research results indicates that the feasibility of assigning score to “plurality-selected” option potentially reduces the count of invalid and specially, void ballots, and increases the count of final correct votes. Manuscript profile

This ability in fuzzy UML, practically leaves the customers and market’s need without response in this important and vital area. Here, the available sequence diagrams in fuzzy UML will map into fuzzy Petri net. However, the formal models ability will be added to the Semi-formal fuzzy UML. This formalization will add the automatic processing ability to the Semi-formal fuzzy UML. Further more, the other advantages of this mapping is: access to non-functional parameters such as reliability automatically to the considering systems, study the verification of the designed plan and also decrease the expenses because of satiety to make lab sample before its implementation. Using the fuzzy UML mapping into fuzzy Petri net in control, critical and real-time systems will be more applicable. Manuscript profile

Morphology has a special place in any language, including written and spoken applications. Markov method is used to labeingl and determine the role of words.emergence in software sciences has eliminated 0 and 1 computations, putting them within an infinite space of between 0,1. This characteristic of fuzzy logic has resolved ambiguity in numerous previous problems. The sentence roles in Persian language were specified based on the fuzzy logic’s capability to resolve ambiguity. In two defuzzification methods Mean Of Max, Central Average, the role of words in the sentence is identified and the success rate of each method is obtained. Finally, Mean Of Max with a success rate of 64% proved to be a defuzzifier delivering the best output among two different defuzzification methods. ** * * * * * * * * * * * * * * * * * * ****** * * * * * * * * * Manuscript profile

An architecture shows to what extent a system meets the needs of the stakeholders, so designing a desired architecture produces very high-quality software tailored to the needs of the stakeholders. Thus, finding a software architecture model is quite critical, and to achieve this goal, a suitable architecture style model must be used. In this regard, attempts are made to deploy the behavior of the candidate software styles as well as the stakeholders’ desired model as functions graphs, so that the desired architecture style model graphs, which meet the maximum needs of the stakeholders, are selected by comparison. Fuzzy Cubic Spline is used in the structure of the proposed algorithm, which requires turning qualitative data into quantitative data. To evaluate the proposed approach, a controlled experiment is also conducted. The proposed approach is compared with an analytic hierarchy process-based approach (AHP), TOPSIS and PTFG (Prioritizing using tensor and fuzzy graphs) in the experiment. The results analysis demonstrates that our approach needs to less time complexity and is much easier to use and highly accurate. Manuscript profile

The license plate edge detection is the most important step of the process of plate identification. Plate recognition system is an automated system that captures vehicle location, vehicle license plate accurately on various vehicles at different times of day and night sets. In this paper the issue of searching the exact location of the license plate from the input images using Sobel operator for edge detection and image processing and histogram analyzing techniques for candidate areas restriction has been examined.The proposed method is tested on the database containing 250 different input images with different background, size and angles in different lighting condition and during different times of the day on different kinds of vehicles (cars, vans and trucks and etc). And the rate of the correct extraction of the exact location of the license plate was 88.4% .The response time and the processing speed of the proposed method is faster in Comparewith existing works. Manuscript profile

In recent years Wireless Sensor Networks have attracted researchers' attention due to vast applications. One of the most prominent issues regarding these networks is coverage which is considered as a quality of Service parameter. In this study, we try to address energy shortage in WSNs through finding a set of optimal coverage nodes in a specific environment. This is performed utilizing effective removal of extra sensors and generating several networks with area coverage. In the first step we use graph based method to classify sensors. The area is divided into several smaller regions in a dynamic manner in such a way that the whole region is covered with sensors. In the next step each set analyzed using genetic algorithm so that optimal or semi-optimal number of active nodes which are necessary to cover the region could be selected. Finally, performance of sensors in coverage of the area is evaluated using Monte Carlo method. Decreasing the number of sensors in each set and generating multiple networks, this method saves more energy which prolongs lifetime of the network. Manuscript profile

Face recognition is one of the most important identification tools in biometrics. Nowadays, the topic of face recognition has many applications in various fields, including public security, identity identification, protection of important and sensitive places, access control, video surveillance, and so on. Two important issues in face recognition applications are speed and accuracy in detection. Various studies have shown that face recognition through Sparce Representation Classification (SRC) works very well.The purpose of this paper is to propose a fast and efficient method for the sparse representation-based face recognition .Due to the fact that retrieving the Sparce Representation based on L1 norm optimization for a large dictionary has a large computational volume, a Smooth L0 norm optimization (SL0) method is used. Also, due to the fact that one of the challenges of face recognition is the existence of brightness changes in images, so we use the P- Laplacein algorithm in the feature extraction step to give us more complete information about the face image by recognizing the edge. As the simulation results on the Extended Yale B and AR database show, the proposed hybrid method has a higher detection rate than the sparse display method. Manuscript profile

Secure Electronic Transaction (SET) protocol is an open protocol, which has the potential to emerge as a powerful tool in securing of electronic transactions. The quality of a design of an Ecommerce protocols has a great influence on achieving non-functional requirements (NFRs) to the system. An increasingly important non-functional attribute of complex software systems is adaptability. Software for adaptive software systems should be flexible enough to allow components to change their behaviors depending upon the environmental and stakeholders' changes and goals of the system. Evaluating adaptability at software to identify the weaknesses of the software and further to improve adaptability of their, are very important tasks. This paper presents a method based on the use of Colored Petri Nets for evaluating Adaptability in SET protocol. We try to see how we can apply the way formalize CPN in terms of quality attributes to evaluate some of them, on the SET protocol Manuscript profile

Digital image processing in recent decades has made considerable progress in theoretical and practical aspects. Nowadays, machine vision techniques have important application in the field of agriculture. One of these applications is detection of different varieties of rice from the bulk sample of rice image. These techniques also have high speed, accuracy and reliability. Texture feature selection is one of the important characteristics used in pattern recognition. The better feature selection of a feature set usually results in better performance in a classification problem. In This work we try to extract features by using co_occurrence matrix and select the best feature set for classification of rice varieties based on image of bulk samples using hybrid algorithm which is called "fuzzy_ imperialist competition” and then classify the best features using support vector machine(SVM). Results of the proposed method showed, the classification accuracy is improved to 96/79%. The feature set which is selected by the fuzzy-Ica provides the better classification performance compared to that obtained by Imperialist competition algorithm. Manuscript profile

This paper, based on the Viterbi algorithm, selects the most likely combination of different wording from a variety of scenarios. In this regard, the Bi-gram and Unigram tags of each word, based on the letters forming the words, as well as the bigram and unigram labels After the breakdown into the composition or moment of transition from the decomposition to the combination obtained from the types of sentences, the educator is used in 194 different wording types, and the sum of them is obtained by the amount of the advance of each wording state and the MAX value is considered as the output of the system. And at the end, the success rate of these methods and the effectiveness of these two types of labeling are compared with each other. Manuscript profile