Sharif Digital Repository

The petroleum industry suffers from reservoir souring phenomena, which has negative impacts on production facilities, health, and environment. Injection of incompatible water into the reservoir (waterflooding), which is considered as an enhanced oil recovery (EOR) method, is one of the most common causes of reservoir souring. In general, injected brine, especially seawater, contains high amounts of sulfate ion (SO42−). A high concentration of sulfate in the presence of sulfate-reducing bacteria (SRB) leads to the microbial reservoir souring. During this phenomenon, sulfide, specifically hydrogen sulfide gas (H2S) appears in the producing fluid of the reservoir. In this paper, a coupled... 

The fabrication of supported noble metal nanocrystals (NCs) with well-controlled morphologies have been attracted considerable interests due to their merits in a wide variety of applications. Photodeposition is a facile and effective method to load metals over semiconductors in a simple slurry reactor under irradiation. By optimizing the photodeposition process, the size, chemical states, and the geometrical distribution of metal NCs have been successfully tuned. However, metal NCs with well-controlled shapes through the photodeposition process have not been reported until now. Here, we report our important advances in the controlled photodeposition process to load regular noble metal NCs.... 

The government's support for rooftop photovoltaic systems has significantly increased their installed capacity, leading to the creation of numerous independent microgrids (MGs). However, multi-microgrids (MMGs), which comprise these MGs, often do not share operational data with neighboring microgrids. This lack of information can lead to congestion at the common coupling point, particularly at midnight when energy prices are low, an issue that this paper addresses for the first time. This paper will break the day into two scales: daytime and nighttime. Then, to manage the congestion, it will introduce a nighttime energy storage charging market managed by an aggregator. This charging market... 

This study aimed to explore the effects of elevated CO2 (e[CO2]) on wheat performance under drought stress, while investigating the role of eco-physiology, carbohydrate metabolic and antioxidant enzymes to predict the grain yield. Wheat genotype Lianmai6 was grown under ambient (400 ppm) and elevated (800 ppm) CO2 concentrations, with subsequent exposure to drought stress prior to anthesis. Leaf parameters, including photosynthetic rate (An), stomatal conductance (Gs), and transpiration rate (E), were significantly declined under drought. Grain yield parameters were adversely affected by drought stress, while An with water use efficiency (WUE) and yield traits increased under e[CO2].... 

This paper proposes an efficient mechanism that mitigates crosstalk faults in Network-on-Chips (NoCs). This is done by using a Packet Manipulating mechanism called PAM for reliable data transfer of NoCs. PAM investigates the transitions of a packet to minimize the forbidden transition patterns appearing during the flit traversal in NoCs. To do this, the content of a packet is manipulated using three different manipulating mechanisms. In other words, PAM manipulates the content of packet in three manipulating modes including: vertical, horizontal and diagonal modes. Then, comparing the transitions of these manipulating mechanisms, a packet with minimum numbers of transitions is selected to be... 

In this paper, we aim to improve meeting summarization performance using discourse specific information. Since there are intrinsically different characteristics in utterances in different types of function segments, e.g., Monologue segments versus Discussion ones, we propose a new summarization framework where different summarizers are used for different segment types. For monologue segments, we adopt the integer linear programming-based summarization method; whereas for discussion segments, we use a graph-based method to incorporate speaker information. Performance of our proposed method is evaluated using the standard AMI meeting corpus. Results show a good improvement over previous... 

Linear segmentation of a meeting conversation is beneficial as a stand-alone system (to organize a meeting and make it easier to access) or as a preprocessing step for many other meeting related tasks. Such segmentation can be done according to two different criteria: topic in which a meeting is segmented according to the different items in its agenda, and function in which the segmentation is done according to the meeting's different events (like discussion, monologue). In this article we concentrate on the function segmentation task and propose new unsupervised methods to segment a meeting into functionally coherent parts. The first proposed method assigns a score to each possible boundary... 

In this paper we investigate the role of discourse analysis in extractive meeting summarization task. Specifically our proposed method comprises of two distinct steps. First we use a meeting segmentation algorithm in order to detect various functional parts of the input meeting. Afterwards, a two level scoring mechanism in a graph-based framework is used to score each dialogue act in order to extract the most valuable ones and include them in the extracted summary. We evaluate our proposed method on AMI and ICSI corpora and compare it with other state-of-the-art graph based algorithms according to various evaluation metrics. The experimental results show that our algorithm outperforms the... 

Summary keywords are words that are used in the reference extracted summary, therefore can be used to discriminate between summary sentences from non-summary ones. Finding these words is important for the extractive summarization algorithms that measure the importance of a sentence based on the importance of its constituent words. This paper is focused on extracting summary keywords in the multi-party meeting domain. We test previously proposed keyword extraction algorithms and evaluate their performance to determine summary keywords. We also propose a new approach which uses discourse information to find local important keywords and show that it outperforms all the previous methods. We... 

In this article we tackle the problem of multi-party conversation summarization. We investigate the role of discourse segmentation of a conversation on meeting summarization. First, an unsupervised function segmentation algorithm is proposed to segment the transcript into functionally coherent parts, such as Monologuei (which indicates a segment where speaker i is the dominant speaker, e.g., lecturing all the other participants) or Discussionx1x2,...,xn (which indicates a segment where speakers x 1 to xn involve in a discussion). Then the salience score for a sentence is computed by leveraging the score of the segment containing the sentence. Performance of our proposed segmentation and... 

The present study demonstrates laser bending which is a flexible and (external) tool-free method for bending and shaping of metallic components. The numerical and experimental analysis of the bending behaviors of Ti-6Al-4V titanium alloy sheets has been done under the constant line energy concept. Numerical simulations using Abaqus examine the transient temperature fields, thermal stress, strain, and deformation characteristics. To validate the numerical calculations and observe the effects of process parameters such as laser powers and scanning speeds on the bending capability, the experimental analysis has been conducted and compared with the numerical simulations. In addition, the... 

The huge volume change and unstable interface of the silicon anode usually result in the fracture of the active material and the disconnection with conducting agent/current collector, which would highly hinder the application of silicon in powering battery. Moreover, the un-uniform charge distribution at the surfaces of silicon would cause a degration of capacity at fast charging condition or low temperature. Thus, developing a stable interface with good mechanical stability to tolerate huge volume change of the silicon, and keep the robust adhesive property is one of the effective methods of resolving the above questions but a great challenge. Here, a molecular zipper fastened strategy is... 

This paper proposes a constrained stochastic successive convex approximation (CSSCA) algorithm to find a stationary point for a general non-convex stochastic optimization problem, whose objective and constraint functions are non-convex and involve expectations over random states. Most existing methods for non-convex stochastic optimization, such as the stochastic (average) gradient and stochastic majorization-minimization, only consider minimizing a stochastic non-convex objective over a deterministic convex set. The proposed CSSCA algorithm can also handle stochastic non-convex constraints in optimization problems, and it opens the way to solving more challenging optimization problems that... 

In this paper, GyroSym, a compact highly-stable single-wheel robot is introduced. Symmetrical flywheels have been used as its stabilization mechanism to keep the wheel upright. Thanks to the type of the flywheel used, the dynamic equations of the robot is simplified, the torque needed to tilt the spin axis is reduced, and the space is drastically minimized. Besides, a centrifugal clutch is used to smooth the motion of the robot in forward motion. Two controllers, fuzzy and fuzzy-Padé, were implemented based on their ability to stabilize the robot. Although both prevented the GyroSym from falling over, neither can entirely cancel out the effects of nonlinear behaviors that is present in the... 

In order to examine the impact of structural and thermal scale parameters on thermoelastic vibrations of Euler-Bernoulli nanobeams, this article intends to provide a size-dependent generalized thermoelasticity model with the help of nonlocal strain gradient theory (NSGT) in conjunction with dual-phase-lag (DPL) heat conduction model. To highlight the role of each scale parameter in size-dependent motion and heat conduction equations, normalized forms of these nonclassical coupled thermoelastic equations are extracted by introducing and exploiting some dimensionless parameters. By exploiting power series expansion as a general solution for arbitrary boundary conditions, system of partial... 

Due to the boom in world trade, port authorities are looking into ways of making existing facilities more efficient. One way to improve efficiency, increase capacity, and meet future demand is to use advanced technologies and automation in order to speed up terminal operations. In this paper, we design, analyze, and evaluate four different automated container terminal (ACT) concepts. These concepts include automated container terminals based on the use of automated guidance vehicles (AGVs), a linear motor conveyance system (LMCS), an overhead grid rail system (GR), and a high-rise automated storage and retrieval structure (AS/RS). We use future demand scenarios to design the characteristics... 

In order to examine the impact of structural and thermal scale parameters on thermoelastic vibrations of Euler-Bernoulli nanobeams, this article intends to provide a size-dependent generalized thermoelasticity model with the help of nonlocal strain gradient theory (NSGT) in conjunction with dual-phase-lag (DPL) heat conduction model. To highlight the role of each scale parameter in size-dependent motion and heat conduction equations, normalized forms of these nonclassical coupled thermoelastic equations are extracted by introducing and exploiting some dimensionless parameters. By exploiting power series expansion as a general solution for arbitrary boundary conditions, system of partial... 

As machine learning tasks continue to evolve, the trend has been to gather larger datasets and train increasingly larger models. While this has led to advancements in accuracy, it has also escalated computational costs to unsustainable levels. Addressing this, our work aims to strike a delicate balance between computational efficiency and model accuracy, a persisting challenge in the field. We introduce a novel method that employs core subset selection for reweighting, effectively optimizing both computational time and model performance. By focusing on a strategically selected coreset, our approach offers a robust representation, as it efficiently minimizes the influence of outliers. The... 

We propose a component model for the scheduling of combined-cycle gas turbine (CCGT) units by mixed-integer programming (MIP) in which combustion turbines (CTs) and steam turbines (STs) are modeled as individual units. The hourly schedule of CCGT based on the component model is compared with that of the mode model. The modeling of modes, which includes a combination of CTs and STs, would require certain approximations for representing fuel input-power output curves, ramping rate limits, minimum operating time limits, etc. The approximations can result in sub-optimal schedules. Furthermore, the commitment and dispatch of CCGTs based on the mode model will require a real-time dispatch to... 

Private set intersection (PSI) is a fundamental cryptographic protocol which has a wide range of applications. It enables two clients to compute the intersection of their private datasets without revealing non-matching elements. The advent of cloud computing drives the ambition to reduce computation and data management overhead by outsourcing such computations. However, since the cloud is not trustworthy, some cryptographic methods should be applied to maintain the confidentiality of datasets. But, in doing so, data owners may be excluded from access control on their outsourced datasets. Therefore, to control access rights and to interact with authorized users, they have to be online during...