Sharif Digital Repository

Wireless sensor networks (WSNs) are tiny devices with limited computation and power supply. For such devices, data transmission is a very energy-consuming operation. Data aggregation eliminates redundancy and minimizes the number of transmissions in order to save energy. This research explores the efficiency of data aggregation by focusing on different aspects of the problem such as energy efficiency, latency and accuracy. To achieve this goal, we first investigate data aggregation efficiency with constraint on delay, which can be compatible with other important system properties such as energy consumption and accuracy. By simulation, we will show that, depending on the application, we can... 

DNA Microarray is the state-of-the-art technology in analyzing gene expression data. It has made it possible to measure expression levels of thousand of genes simultaneously. Microarray classification has been widely used in effective diagnosis of cancers and some other biological diseases. But the most challenging issue is the intense asymmetry between the dimensionality of genes and tissue samples which can wreck the classification performance. This dissertation will focus on gene selection and reduction solutions and presents a novel classification scheme which uses both gene selection and dimension reduction in its different stages. We have improved one of the recently proposed topology... 

The increased need for experimental verification of the seismic performance of conventional and novel structural systems has resulted in highly sophisticated dynamic test procedures. Hybrid simulation is one of the most efficient experimental methods for assessment of dynamic and rate-dependent behavior of large-scale structural systems under earthquake excitation. Compared to earthquake simulations using shake tables, hybrid simulation may have significant advantages in terms of cost, scale, geometry, and required physical mass of structures. However, recent hybrid simulations have been limited to simplified structural models with only a few degrees of freedom. Currently, the major... 

Recommender systems are in the center of network science and becoming increasingly important in individual businesses for providing efficient personalized services and products to users. The focus of previous research in the field of recommendation systems was on improving the precision of the system through designing more accurate recommendation lists. Recently, the community has been paying attention to diversity and novelty of recommendation list as key characteristics of modern recommender systems. In many cases, novelty and precision do not go in the same direction and the accuracy-novelty dilemma is one of the challenging problems in recommender systems, which needs efforts in making a... 

Nowadays, the world is based on the interaction between individuals, groups and different systems. The actual networks that have a complex structure and behavior are called complex networks. Complex networks are one of the new knowledge that studies the connections. The complex systems represented as graph, with non-trivial topological features—features that do not occur in simple networks.With the vast development of computer networks, complex networks appear in different categories such as social networks, citation networks, collaboration networks and communication networks. Data mining is the process of exploring hidden knowledge in data bases and it has applications in complex networks.... 

The World Wide Web has been experiencing a massive growth regarding its content and users in recent years; therefore the need for effective means of accessing and processing available items has attracted a wide range of researchers and industries. Recommender systems has emerged to help both users to find what they may be interested in and the producers to sell their products more efficiently. As the number of these techniques grow, the need to evaluate them properly increases as well. However the proposed evaluation metrics are very diverse and often inconsistent with each other. Although there had been immense research in this field, there is no united and proper approach for evaluation of... 

Real time hybrid simulation is considered as one of the most efficient experimental methods for investigation of the behavior of structures and their components during seismic loading. In pseudo-dynamic approach of hybrid simulation considered in this study, the majority of the structural mass is modelled numerically and inertia forces are calculated in the numerical model.Using this approach, loading can be carried out on a real-time basis, and component scaling requirements will be reduced. As a result, in addition to lower costs, this testing method is sometimes considered to be more realistic compared to shaking table tests. However, several challenges are currently faced in... 

Sentiment analysis, is a subfield of natural language processing that aims at opinion mining to analyze thoughts, orientation and evaluation of users within some texts. Different organizations in multiple social domains, use this approach as a tool to asses their strengths and shortcomings. In sentiment analysis, the goal is to use machine learning techniques with the purpose of specifying users’ positive or negative orientation about a product or merchandise. The solution to this problem includes two main steps: extracting aspects and determining users’ positive or negative sentiments in respect to the aspects. Two main challenges of sentiment analysis in Farsi, are lack of comprehensive... 

Cerebrovascular Attack has been ranked the second or third of top 10 death causes in Taiwan. It has caused about 13,000 deaths every year since 1986. Once Cerebrovascular Attack (CVA) occurs, it not only leads to the huge cost of medical care, but even death. All developed countries in the world put CVA prevention and treatment in high priority. However, it is necessary to build a detective model to enhance the accurate diagnosis of CVA. From this detective model, CVA classification rules were extracted and used to improve the diagnosis and detection of CVA. This study acquired 2449 valid samples from this CVA prevention and treatment program, and adopted three classification algorithms,... 

Adopting a mixed-methods research approach, this study investigated the impacts of four task planning conditions, i.e. online planning (OLP), pre-task planning (PTP), combined pre-task planning and online planning (PTP+OLP), and no planning (NP) on written narrative output which was elicited by means of a picture composition from 80 female advanced EFL learners. The narratives were analyzed in terms of complexity, accuracy, and fluency (CAF). Moreover, in the qualitative part of this study, how learners planned during pre-task planning time and the content of their narratives were analyzed. The results of the one-way ANOVAs showed that the PTP+OLP group produced significantly more complex,...