Sharif Digital Repository

Treebanks are not large enough to reliably model precise lexical phenomena. This deficiency provokes attachment errors in the parsers trained on such data. We propose in this paper to compute lexical affinities, on large corpora, for specific lexico-syntactic configurations that are hard to disambiguate and introduce the new information in a parser. Experiments on the French Treebank showed a relative decrease of the error rate of 7.1% Labeled Accuracy Score yielding the best parsing results on this treebank  

Original scientific paper Developing a model for citizens' satisfaction with public services is one of the effective factors for improvement of service quality. In recent years, many studies have been carried out to identify a model for citizens' satisfaction with public sector services. In the structure of the presented models in the literature, one of the most important issues regarding organizations giving public services is identification of service scopes that have the most impact on citizens' satisfaction. This paper aims to develop a model to identify citizens' satisfaction status with public services. To do so, first, key factors influencing citizens' satisfaction with public... 

A one dimensional model of the pulmonary arterial network along with systemic circulation was introduced to quantify the human pulmonary artery hemodynamics. A lumped parameter model of the right ventricle was used as the inlet boundary condition. A time varying elastance related the volume and pressure of the right ventricle was imposed in the model. By using a four element Windkessel model, blood flow rate throughout the right ventricle was in hand. An asymmetric structured tree was chosen as the outlet boundary conditions. Simulation was based on solving one-dimensional equations of conservation of mass and momentum by using finite volume method. Blood flow rate, pressure and velocity... 

This paper is aimed at investigating some computational aspects of different isoperimetric problems on weighted trees. In this regard, we consider different connectivity parameters called minimum normalized cuts/isoperimetric numbers defined through taking the minimum of the maximum or the mean of the normalized outgoing flows from a set of subdomains of vertices, where these subdomains constitute a partition/subpartition. We show that the decision problem for the case of taking k-partitions and the maximum (called the max normalized cut problem NCPM), and the other two decision problems for the mean version (referred to as IPPm and NCPm) are NP-complete problems for weighted trees. On the... 

We consider an interacting system of spin variables on a loopy interaction graph, identified by a tree graph and a set of loopy interactions. We start from a high-temperature expansion for loopy interactions represented by a sum of non-negative contributions from all the possible frustration-free loop configurations. We then compute the loop corrections using different approximations for the nonlocal loop interactions induced by the spin correlations in the tree graph. For distant loopy interactions, we can exploit the exponential decay of correlations in the tree interaction graph to compute loop corrections within an independent-loop approximation. Higher orders of the approximation are... 

The problem of finding nearest neighbors in a certain distance is well defined in machine learning area. There are well-known and exact solutions for it. However, in real world problems, especially in machine vision area, where we have a moving sensor and we want to know which objects of the scene are in the measurement range of it, two issues are important. First, usually in these problems, the time cost is more important than accuracy. It means they can tolerate some measurements error if they can do the process in real-time. Second, the location of an object can be described in the three-dimensional space and does not require the higher dimensions. According to these issues, we introduced... 

In action recognition, a body pose, or simply pose, is defined as a state of the 3D position of skeleton joints which varies while an action is performed. Then an action can be defined as a sequence of specific poses, called key-poses in this paper. Key-poses are contained in the so called key-frames, which are surrounded by several other frames. Key-frames can be selected using minimum energy criterion. In this paper, a method is proposed to automatically extract key-poses out of key-frames. Furthermore, a novel learning method, named Fisher forest, is proposed which enables action recognition methods to use different types and even various number of joints for different actions, poses, or... 

In this paper, we study the multiplicity of the Laplacian eigenvalues of trees. It is known that for trees, integer Laplacian eigenvalues larger than 1 are simple and also the multiplicity of Laplacian eigenvalue 1 has been well studied before. Here we consider the multiplicities of the other (non-integral) Laplacian eigenvalues. We give an upper bound and determine the trees of order n that have a multiplicity that is close to the upper bound [Formula presented], and emphasize the particular role of the algebraic connectivity. © 2019 Elsevier Inc  

Grammar induction is one of attractive research areas of natural language processing. Since both supervised and to some extent semi-supervised grammar induction methods require large treebanks, and for many languages, such treebanks do not currently exist, we focused our attention on unsupervised approaches. Constituent Context Model (CCM) seems to be the state of the art in unsupervised grammar induction. In this paper, we show that the performance of CCM in free word order languages (FWOLs) such as Persian is inferior to that of fixed order languages such as English. We also introduce a novel approach, called parent-based constituent context model (PCCM), and show that by using some... 

The objective of this research is to design a method for selection of an appropriate location to establish plywood and veneer plants in Iran. Due to the climate of this region as well as the destruction of the forests and lack of proper plantation, the supporting forests to feed this industry are limited. Thus, it is vital to optimize the other strategically factors in order to make these plants capable of competing with the foreign plants which have access to less expensive input materials. In case of improper utilization of the resources, this industry can not compete with the imported products. The decision is made within the framework of benefits, opportunities, costs and risks (BOCR).... 

With the emergence of social networks and improvements in the internet speed, the video data has become an ever-increasing portion of the global internet traffic. Besides the content, the quality of a video sequence is an important issue at the user end which is often affected by various factors such as compression. Therefore, monitoring the quality is crucial for the video content and service providers. A simple monitoring approach is to compare the raw video content (uncompressed) with the received data at the receiver. In most practical scenarios, however, the reference video sequence is not available. Consequently, it is desirable to have a general reference-less method for assessing the... 

In this study, an integrated 2D numerical model is applied to investigate the mechanical effects of the vegetation and soil type on slope stability. The developed model can assess the mechanical aspects of vegetation in slope stabilization. For this purpose, a case study of the Kheyrud forest located in northern Iran is considered as a real case site. Different scenarios including; three soil types (fine grain with low-, medium-, and high-strength) and two vegetation types (Maple and Common-ash) are assessed in the stability analysis (based on safety factor). The results confirm that the considered vegetation can prevent shallow landslide occasions, but has a limited impact on deep landslide... 

In this paper, the joint problem of project selection and project scheduling under uncertain environment is formulated, analyzed, and solved by multistage stochastic programs. First of all, a general mathematical formulation which can address several versions of the problem is presented. A multi-period project selection and scheduling problem is introduced and modeled by multistage stochastic programs, which are effective for solving long-term planning problems under uncertainty. A set of scenarios and corresponding probabilities is applied to model the multivariate random data process (costs or revenues, available budget, chance of success). Then, due to computational complexity, a scenario... 

We consider the problem of walking a simple robot in an unknown street. The robot that cannot infer any geometric properties of the street traverses the environment to reach a target t, starting from a point s. The robot has a minimal sensing capability that can only report the discontinuities in the depth information (gaps), and location of the target point once it enters in its visibility region. Also, the robot can only move towards the gaps while moving along straight lines is cheap, but rotation is expensive for the robot. We maintain the location of some gaps in a tree data structure of constant size. The tree is dynamically updated during the movement. Using the data structure, we... 

An important manufacturing technology spectrum is to consider rapid and sensitive assemblies through convergent product (CP) in digital environment. We integrate functions and sub-functions using a comprehensive mathematical optimization process. To form the CP, a web-based fuzzy network is considered in which a collection of base functions and sub-functions configure the nodes and each arc in the network is to be a link between two nodes. The aim is to find an optimal tree of functionalities in the network adding value to the product in the web environment. First, a purification process is performed in the product network to assign the links among bases and sub-functions. Then, fuzzy... 

Data streams are endless flow of data produced in high speed, large size and usually non-stationary environments. The main property of these streams is the occurrence of concept drifts. Using decision trees is shown to be a powerful approach for accurate and fast learning of data streams. In this paper, we present an incremental regression tree that can predict the target variable of newly incoming instances. The tree is updated in the case of occurring concept drifts either by altering its structure or updating its embedded models. Experimental results show the effectiveness of our algorithm in speed and accuracy aspects in comparison to the best state-of-the-art methods  

The brain is one of the vital organs in the body. The main cerebral distribution center of blood flow in the brain is the circle of Willis (CoW). In more than 50% of healthy brains and in more than 80% of dysfunctional ones, at least one artery of the circle of Willis is absent or underdeveloped. These variations reduce the collateral flow availability and increase the risk of stroke and transient ischemic attack in patients with atherosclerosis. Thus it is essential to simulate the circle of Willis and investigate the effects of stenosis. In this work the systemic arteries along with the circle of Willis are simulated using the finite volume method and one-dimensional equations of... 

This study investigates critical run-off and sediment production sources in a forested Kasilian watershed located in northern Iran. The Water Erosion Prediction Project (WEPP) watershed model was set up to simulate the run-off and sediment yields. WEPP was calibrated and validated against measured rainfall-run-off-sediment data. Results showed that simulated run-off and sediment yields of the watershed were in agreement with the measured data for the calibration and validation periods. While low and medium values of run-off and sediment yields were adequately simulated by the WEPP model, high run-off and sediment yield values were underestimated. Performance of the model was evaluated as... 

A new method for exploiting the semantic hierarchical structure of visual concepts in video event recognition task is proposed in this paper. The visual concepts are detected using the readily available Convolutional Neural Network (CNN) structures which make the recognition system extremely efficient in cases with limited hardware resources. The employed CNNs assign scores to each of the predetermined visual concepts in each video frame and the resulting concept scores are fed to the proposed hierarchical post-processing scheme. Our post-processing module takes advantage of the semantic hierarchy of the concepts to enhance the recognition accuracy of event recognition. The hierarchical... 

Edit distance is one of the most fundamental problems in computer science. Tree edit distance is a natural generalization of edit distance to ordered rooted trees. Such a generalization extends the applications of edit distance to areas such as computational biology, structured data analysis (e.g., XML), image analysis, and compiler optimization. Perhaps the most notable application of tree edit distance is in the analysis of RNA molecules in computational biology where the secondary structure of RNA is typically represented as a rooted tree. The best-known solution for tree edit distance runs in cubic time. Recently, Bringmann et al. show that an O(n2.99) algorithm for weighted tree edit...