Sharif Digital Repository

In a recently published article by Backer [Opt. Express 27(21), 30308 (2019).], a computational inverse design method is developed for designing optical systems composed of multiple metasurfaces. The forward propagation model used in this method was a discretized version of the angular spectrum propagator described by Goodman [Introduction to Fourier Optics, 1996]. However, slight modifications are necessary to increase the accuracy of this inverse design method. This comment examines the accuracy of the results obtained by the above-mentioned method by a full-wave electromagnetic solver and explains the reason of their difference. Thereafter, slight modifications to the method proposed by... 

Chiral recognition has long been a challenging issue to deal with in biological systems, drug design and food authentication. Implementing nanoparticle-based probes with intrinsic or induced chirality in this field has addressed several issues concerning sensitivity, reliability, rapidness and the cost of chiral sensing platforms. Yet, research into chiral nanoprobes that can be used for visual monitoring of chiral substances is still in its infancy. As part of this study, a visual chiral recognition platform has been developed in which a combination of blue-emitting carbon dots (BCDs) and mercaptopropionic acid-capped CdTe quantum dots (MPA-QDs) with inherent chiroptical activity were... 

Ecological fitness depends on maintaining object histories to guide future interactions. Recent evidence shows that value memory changes passive visual responses to objects in ventrolateral prefrontal cortex (vlPFC) and substantia nigra reticulata (SNr). However, it is not known whether this effect is limited to reward history and if not how cross-domain representations are organized within the same or different neural populations in this corticobasal circuitry. To address this issue, visual responses of the same neurons across appetitive, aversive and novelty domains were recorded in vlPFC and SNr. Results showed that changes in visual responses across domains happened in the same rather... 

Visual object tracking remains an active research field in computer vision due to persisting challenges with various problem-specific factors in real-world scenes. Many existing tracking methods based on discriminative correlation filters (DCFs) employ feature extraction networks (FENs) to model the target appearance during the learning process. However, using deep feature maps extracted from FENs based on different residual neural networks (ResNets) has not previously been investigated. This paper aims to evaluate the performance of 12 state-of-the-art ResNet-based FENs in a DCF-based framework to determine the best for visual tracking purposes. First, it ranks their best feature maps and... 

Knee osteoarthritis (KOA) is a common musculoskeletal disorder resulting in altered gait patterns. Uncontrolled manifold (UCM) analysis has been demonstrated as a useful approach for quantitative analysis of motor variability and synergies. The present study aimed to investigate the changes in the kinematic synergy, controlling the center of mass (COM) position while walking on normal and narrow paths in people with KOA compared to asymptomatic participants. In this cross-sectional study, twenty people with mild to moderate KOA and twenty asymptomatic individuals walked at their comfortable preferred speed across normal and narrow paths on a treadmill. The UCM analysis was performed... 

This paper proposes a damage assessment framework based on the visual features of a damaged reinforced concrete shear wall, such as crack pattern distribution, crushing areal density, aspect ratio, and the presence of the boundary condition. The study contains two parts including: identifying the performance level of the damaged walls (i.e., Immediate Occupancy, Life Safety, and Collapse Prevention) and estimating the residual strength and drift ratio of the walls. The research database contains 236 images of 72 reinforced concrete shear walls tested in the laboratory under the quasi-static cyclic loadings at various drift ratios between 0 and 4%. To identify the performance level of a... 

A ratiometric fluorescent nanoprobe is developed with a wide color variation for visual determination of spermine (SP) and spermidine (SD) in meat samples. The green emission provided from the combination of yellow emissive quantum dots and blue emissive carbon dots turns into pink when SP or SD are present. The results show that the developed sensor has good linearity in the range of 0.5–10 and 0.5–80 µM for SP and SD and suitable detection limits were achieved including 0.2 and 2.1 µM for SP and SD. The probe was highly selective in the presence of amino acids and other biogenic amines. RGB indices were extracted to build a combinational logic gate for visual and simultaneous detection of... 

In this paper, a novel computer-vision based methodology is developed for predicting the seismic peak drift ratio of damaged reinforced concrete moment frames using surface crack patterns. A comprehensive database comprising 974 surface crack images from cyclic test results of 256 beam-column joint specimens at various drift ratio levels is collected. The database covers a broad range of concrete compressive strengths, rebar and stirrup strengths, longitudinal and transverse reinforcement ratios, beam and column length to depth ratios, in-plane configurations, and failure modes. Multifractal dimensions of damaged beam-column subassembly images are obtained by the box-counting algorithm to... 

Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. Given the ill-posed nature of the problem and its popularity in a broad range of real-world scenarios, a number of large-scale benchmark datasets have been established, on which considerable methods have been developed and demonstrated with significant progress in recent years - predominantly by recent deep learning (DL)-based methods. This survey aims to systematically investigate the current DL-based visual tracking methods, benchmark datasets, and evaluation metrics. It also extensively evaluates and analyzes the leading visual tracking methods. First, the fundamental... 

Neural synchronization has been engaged in several brain mechanisms. Previous studies have shown that the interaction between the time of spiking activity and phase of local field potentials (LFPs) plays a key role in many cognitive functions. However, the potential role of this spike–LFP phase coupling (SPC) in neural coding is not fully understood. Here, we sought to investigate the role of this SPC for encoding the sensory properties of visual stimuli. To this end, we measured SPC strength in the preferred and anti-preferred motion directions of stimulus presented inside the receptive field of middle temporal (MT) neurons. We found a selective response in terms of SPC strength for... 

This article is concerned with remote monitoring and control of the 2-degrees of freedom (DoF) robotic manipulators, which have nonlinear dynamics over the packet erasure channel, which is an abstract model for communication over the Internet, WiFi, or Zigbee modules. This type of communication is subject to imperfections, such as random packet dropout and rate distortion. These imperfections cause a significant challenge for monitoring and control of robotic manipulators in the industrial environments because sensitive data, such as sensor data and control commands may not ever reach to their destination resulting in significant performance degradation. Therefore, the effects of these... 

This study proposes predictive equations for estimating the peak-experienced drift ratio of unreinforced masonry walls based on the visual characteristic of the damages. In this regard, a comprehensive database comprised of 190 images associated with 30 unreinforced masonry walls at different drift ratios between 0.0 and 1.1 percent is collected, and the visual features of the progressive damages are extracted. Various image processing filters are implemented to the images to quantify the cracking length and crushing areas. The filters are capable of distinguishing different crack patterns, such as joint cracking and block cracking. In the following, four scenarios are introduced based on... 

Transformer networks, originally developed in the community of machine translation to eliminate sequential nature of recurrent neural networks, have shown impressive results in other natural language processing and machine vision tasks. Self-attention is the core module behind visual transformers which globally mixes the image information. This module drastically reduces the intrinsic inductive bias imposed by CNNs, such as locality, while encountering insufficient robustness against some adversarial attacks. In this paper we introduce K-sparse attention to preserve low inductive bias, while robustifying transformers against adversarial attacks. We show that standard transformers attend... 

A novel photolithography-based technique was developed to fabricate a quasi-2D heterogeneous calcite micromodel of representative elementary volume size. The effect of brine-chemistry on the mobilization of capillarity and heterogeneity trapped oil after high salinity water injection was evaluated by using diluted seawater, and seawater modified with calcium, sulphate, and silica nanoparticles. Preliminary brine screening was performed based on modified contact angle experiments under dynamic salinity alteration. The main findings are that the chemical composition of brine impacts both the ultimate oil recovery and its speed. The highest and fastest oil recovery was obtained with diluted... 

We provide an efficient ready-to-run code gensaw that generates single or large ensembles of self-avoiding, flexible, semiflexible, rotationally isometric or helical chains in the bulk or subject to arbitrary confinement and tethering conditions, where we allow for arbitrary intramolecular bending and dihedral energy functions. The resulting configuration files are provided in various common formats and can be immediately used to do molecular simulations or statistical analysis. We work out analytic expressions for the mean squared end-to-end distance and gyration radius of the semiflexible, helical and rotational isomeric state models with a finite number of bonds and arbitrary interaction... 

Discrimination of chiral targets is generally achieved with chiral nanomaterials. However, the limited number of intrinsic chiral nanostructures as well as their complex synthesis procedure has led to the production of chirality-induced nanomaterials as alternatives. Chirality can be induced in nanomaterials by either chirality transfer or the formation of chiral assemblies. Using the latter approach, in this work, we have provided chiral supramolecular assemblies of CdTe quantum dots (QDs) from achiral starting materials. CTAB-QD assemblies showed chiroptical activities, and their orange emission in combination with the blue emission of carbon dots was utilized as a ratiometric chiral... 

Nowadays, data and information are recognized as a precious resource in an organization. Data quality indicators help organizations manage the quality of data quantitatively and improve organizational processes. Organizations manage data and information with the help of information systems and make decisions within the framework of data collected and analyzed. On the other hand, continuous evaluation of the quality of data flow in systems can lead to a preventive program to formulate strategies for improving performance. This can be done effectively and efficiently in the form of control charts. In this paper, control charts are employed to monitor the quality of data flow in information... 

Discrimination of chiral targets is generally achieved with chiral nanomaterials. However, the limited number of intrinsic chiral nanostructures as well as their complex synthesis procedure has led to the production of chirality-induced nanomaterials as alternatives. Chirality can be induced in nanomaterials by either chirality transfer or the formation of chiral assemblies. Using the latter approach, in this work, we have provided chiral supramolecular assemblies of CdTe quantum dots (QDs) from achiral starting materials. CTAB-QD assemblies showed chiroptical activities, and their orange emission in combination with the blue emission of carbon dots was utilized as a ratiometric chiral... 

Automatic image annotation is a mechanism to assign a list of appropriate tags that describe the visual content of a given image. Most methods only focus on the content of the images and ignore the relationship between the tags in vocabulary. In this work, we propose a new deep learning-based automatic image annotation architecture, which considers label dependencies in a graph convolution neural network structure and extracts tag descriptors to re-weight the output class scores based on their relationships. The proposed architecture has three main parts: feature extraction, graph convolutional network, and annotation. In graph convolutional network, we apply one layer convolution on... 

Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved a great success in challenging scenarios for visual tracking purposes. Although many of those trackers utilize the feature maps from pre-trained convolutional neural networks (CNNs), the effects of selecting different models and exploiting various combinations of their feature maps are still not compared completely. To the best of our knowledge, all those methods use a fixed number of convolutional feature maps without considering the scene attributes (e.g., occlusion, deformation, and fast motion) that might occur during tracking. As a...