Discovering Important Nodes in graph data attracted a lot of attention. Social networks are good examples of graph data in which each node represents a person and each edge represents a relationship between two people. There are several methods for the task of discovering Important Nodes in graph data. In this paper, Important people are defined with their roles in society or organization. We propose an efficient method to discover leaders in graph network. For this purpose, both structural feature like entropy and inherent features including from, to, subject and message's time of social networks are used to propose a novel method for discovering Important Nodes in social networks. The proposed method was applied to Enron dataset and compared with previous methods. The proposed method succeeded to first, discover more Important roles in Enron dataset, second, determine CEO as leader of Enron Corporation and third, discover two out of four CEOs among top VIPs.

In this study 400 cow’s lymph Nodes from different areas of body such as : Mandibular, parotid, lateral retropharyngeal, prescapular or superficial cervical, iliac, prefemoral or subiliac, and popliteal lymph Nodes from Shahrekord abattoir were collected. The specimens were selected from inbreeding breed and two sexes with aged 1 to 4 years .After collecting of specimen's factors such as: Length, width and thickness of each lymph node were measured by caliper device. All factors between two sexes and different ages were analyzed and compared using t and Duncan’s tests (p<0.05). It was revealed that , the maximum length, wide and thickness were observed in prescapular (72.98 ± 1.37 mm), iliac (34.61 ± 9.94 mm) and prescapular (16.18 ± 4.11mm) lymph Nodes respectively and on the other hand, the minimum length, width and thickness of lymph Nodes were observed in mandibular (40.18 ± 8.01mm),(22.37 ± 5.44mm) and iliac (11.06 ± 1.94mm) lymph Nodes respectively. These factors were larger in male than in female. By comparing factors between ages, the maximum dimensions of lymph Nodes were observed in 2 year old animals.

Efficient distribution of service requests between fog and cloud Nodes considering user mobility and fog Nodes’ overload is an Important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog Nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog Nodes and outperforms the existing methods in terms of response time and acceptance rate.

Different types of contact, including contact between node pairs, any-contact of Nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for Nodes, improves the performance of these networks. However, there exists an Important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

Today, social networks have found many applications in human daily life, so that identifying the behavior of members of this type of networks and the associations within them is of particular importance. Due to the structure and communication between members of social networks, some members within this type of network have more Important roles than other members. In this study, a method for identifying more Important associations was discussed. For this purpose, new features were introduced using network centralization features and then the importance of this type of features was investigated by Rough set theory. The experimental results showed that with increasing the number of popular Nodes among an association introduced in this study and at the same time decreasing the amount of density, intermediate and proximity characteristics, the effect of the number of popular Nodes on the association will remain more evident.

The notion of strong arcs in a fuzzy graph was introduced by Bhutani and Rosenfeld in [1] and fuzzy end Nodes in the subsequent paper [2] using the concept of strong arcs. In Mordeson and Yao [7], the notion of "degrees" for concepts fuzzified from graph theory were defined and studied. In this note, we discuss degrees for fuzzy end Nodes and study further some properties of fuzzy end Nodes and fuzzy cut Nodes.

Wireless Sensor Networks need primal information like location of the Nodes to start working and sending environment data. One method for setting a sensor network in a battlefield is to drop them from helicopter or to fire from artillery. It will cost a lot to Equip all network Nodes with GPS. So to reduce these costs, only a few of Nodes called anchor Nodes are equipped with gps. Location of Nodes are estimated by using belief propagation algorithm with measuring distance between Nodes (with use of recieved signal strength) and location information of anchor Nodes. Since the cost of anchor Nodes is reletively high, their number is Important. also position of anchor Nodes affects algorithms error. In this paper, by using multi-objective algorithms with two objectives of error reduction and anchor Nodes number reduction, position and number of anchor Nodes are determined. results show that by using this methond, a few solutions are provided which are better than similar algorithms in terms of error reduction and energy consumption.

The focus of this study is primarily on “the discrepancy in mentality as an Important factor affecting family problems and divorce”. For this purpose, some minor studies were conducted each of which experimentally examined different aspects of mental discrepancy in Iranian families. Almost all of these studies showed that permanent disputes and divorces resulted from the differences in their world-views, thinkings, and impressions in their mutual affairs. At last, the theory of Homogamy with two major revisions were used to explain the reasons and causes of family problems and divorce which were confirmed in minor studies and cases.

The imaging assessment of nodal disease can be challenging for the radiologist because there are multiple sites to review and differing opinions about criteria for abnormal Nodes. The ability to accurately detect nodal metastases is improved with knowledge of the criteria for abnormal Nodes, the nodal drainage patterns, and common imaging pitfalls. In this article, we introduce these basic concepts and review the appropriate approach for evaluation of metastatic cervical lymph Nodes on cross-sectional neck imaging. This presentation would cover the following topics: criteria for abnormal Nodes which includes size, morphology, margin and internal content of the lymph Nodes ( cystic changes, Ca, etc. ), site Classification based on the system devised by American head and neck society and American academy of otolaryngology-head and neck surgery, features Important for Staging and the radiologist’ s role is to describe characteristics pertinent to the N staging, Important features for Management such as extra capsular spread. It would also have a brief review of advanced imaging techniques for nodal metastases and the indications for FNA in head and neck lymphadenopathies.