Sharif Digital Repository

In this article, we introduce the zero-divisor ideal graph associated to a commutative ring with identity and study some of its properties. We also introduce a geometric quotient of this graph, extend it to reduced schemes, and study the interplay between scheme-theoretical properties of a scheme and graph-theoretical properties of the associated graph  

Sports video analysis and camera calibration are important applications which rely on accurate homography computation as a challenging task. Homography refinement is an important step in the task of accurate homography computation and homography tracking. Also, in certain applications (such as homography tracking) the process speed is of great importance. A robust and fast method for accurate refinement of highly inaccurate homographies in soccer video frames is proposed in this paper. To achieve that goal, a new homography model fitting method named the point-line (PL) method is proposed. It uses point-line correspondences to compute the homography, rather than point correspondences or line... 

Signature verification (SV) is one of the common methods for identity verification in banking, where for security reasons, it is very important to have an accurate method for automatic SV (ASV). ASV is usually addressed by comparing the test signature with the enrolment signature(s) signed by the individual whose identity is claimed in two manners: online and offline. In this study, a new method based on the i-vector is proposed for online SV. In the proposed method, a fixed-length vector, called i-vector, is extracted from each signature and then this vector is used for template making. Several techniques such as nuisance attribute projection (NAP) and within-class covariance normalisation... 

In this paper, we introduce a new dataset for SAD and evaluate certain common methods such as GMM, DNN, and RNN on it. We have collected our dataset in a semi-supervised approach, using subtitled movies, with a labeling accuracy of 95%. This semi-automatic method can help us collect huge amounts of labeled audio data with very high diversity in language, speaker, and channel. We model the problem of SAD as a classification task to two classes of speech and non-speech. When using GMM for this problem, we use two separate mixtures to model speech and non-speech. In the case of neural networks, we use a softmax layer at the end of the network, with two neurons which represent speech and... 

Abstract The effects of both Lithium modification and cooling rate on the microstructure and tensile properties of an in-situ prepared Al-15% Mg2Si composite were investigated. Adding 0.3%Li reduced the average size of Mg2Si primary particles from ~30 μm to ~ 6 μm. The effect of cooling rate was investigated by the use of a mold with different section thickness from 3 to 9 mm. The results show a refinement of primary particle size as a result of both Li additions and increased cooling rate, and their effects were additive. Similarly, both effects increased UTS and elongation values. The refinement by Li and enhanced cooling rate is discussed in terms of an analogy with the effect of Sr and... 

In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques  

Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to... 

The Karkheh River Basin is one of the Iranian river basins with a high potential for hydropower production. While Iran is actively constructing large dams in the Basin for hydropower production, climate change is putting the future status of hydropower production in the Basin in question. Using MODSIM, sensitivity of the Basin to climate change is investigated by estimating stream flow changes and the resulting impacts on hydropower production for different climate change scenarios. Results indicate considerable reductions in annual and seasonal hydropower production due to the expected dry climatic conditions under the existing operation rules. Findings highlight the necessity for revision... 

We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models. By end-to-end training, we mean flat-start training of a single DNN in one stage without using any previously trained models, forced alignments, or building state-tying decision trees. We use full biphones to enable context-dependent modeling without trees, and show that our end-to-end LF-MMI approach can achieve comparable results to regular LF-MMI on well-known large vocabulary tasks. We also compare with other end-to-end methods such as CTC in character-based and lexicon-free settings and show 5 to 25 percent... 

In recent years, end-to-end approaches to automatic speech recognition have received considerable attention as they are much faster in terms of preparing resources. However, conventional multistage approaches, which rely on a pipeline of training hidden Markov models (HMM)-GMM models and tree-building steps still give the state-of-the-art results on most databases. In this study, we investigate flat-start one-stage training of neural networks using lattice-free maximum mutual information (LF-MMI) objective function with HMM for large vocabulary continuous speech recognition. We thoroughly look into different issues that arise in such a setup and propose a standalone system, which achieves... 

I-vectors have proved to be the most effective features for text-independent speaker verification in recent researches. In this article a new scheme is proposed to utilize i-vectors in text-prompted speaker verification in a simple while effective manner. In order to examine this scheme empirically, a telephony dataset of Persian month names is introduced. Experiments show that the proposed scheme reduces the EER by 31% compared to the state-of-the-art State-GMM-MAP method. Furthermore it is shown that using HMM instead of GMM for universal background modeling leads to 15% reduction in EER