Sharif Digital Repository

In this paper, we analyze the variation of the gravitational action on a bounded region of spacetime whose boundary contains segments with various characters, including null. We develop a systematic approach to decompose the derivative of metric variations into orthogonal and tangential components with respect to the boundary and express them in terms of variations of geometric objects associated with the boundary hypersurface. We suggest that a double-foliation of spacetime provides a natural and useful set-up for treating the general problem and clarifies the assumptions and results in specialized ones. In this set-up, we are able to obtain the boundary action necessary for the variational... 

Multi sender attribute-based broadcast authentication scheme for the network containing resource constrained nodes is the main focus of this research. In this paper, we proposed a framework in which each element of a set of authorized users whose attributes satisfy a special sign control policy can generate a valid signature. In this framework, there exists a trusted server who receives and verifies the validity of the generated attribute-based signatures and broadcast the intended message through the nodes of the network in an efficient and authenticated manner. We also proposed a new symmetric-based broadcast authentication scheme which is used for broadcasting the authenticated messages... 

Financial time series have been extensively studied within the past decades; however, the advent of machine learning and deep neural networks opened new horizons to apply supercomputing techniques to extract more insights from the underlying patterns of price data. This paper presents a tri-state labeling approach to classify the underlying patterns in price data into up, down and no-action classes. The introduction of a no-action state in our novel approach alleviates the burden of denoising the dataset as a preprocessing task. The performance of our labeling algorithm is experimented with using machine learning and deep learning models. The framework is augmented by applying the Bayesian... 

Learning a foreign language encompasses a process of trial and error that can lead to the progression of the learner's interlanguage, meaning that the learners make use of their language knowledge that receives feedback and brings about progress through diagnosis of the problems and being corrected by the teacher. Therefore, there exists a need to analyze the underlying reasons causing the students to remain taciturn with a low willingness to communicate (WTC) during a language class. There has been much work done investigating the role of the learner's stable personal characteristics (traits) along with their situational changes at a specific time (states) that influence the student's... 

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's characteristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing functions which are widely accessible by researchers and this has led to an easy algorithm implementation. In this method, after polishing and quality control of images, using city-block distance function and watershed segmentation algorithm, pores and throats are detected and 3-D network is produced. This method can also be applied on 2-D images... 

In this paper, we try to recognize and distinguish different groups of arrhythmia using novel features which have been obtained from the heart rate's phase space in recent years. For this purpose, we used Triangular Phase Space Mapping (TPSM) and Parabolic Phase Space Mapping (PPSM). For recognition, we used three groups of 15 subjects using the Physionet database (Arrhythmia, Congestive Heart Failure (CHF), and Atrial Fibrillation (AF)) with Normal Sinus Rhythm (NSR). The obtained features discriminate arrhythmia from NSR by p