Sharif Digital Repository

Alluring optical and electronic properties have made organometallic halide perovskites attractive candidates for optoelectronics. Among all perovskite materials, inorganic CsPbX3 (X is halide) in black cubic phase has triggered enormous attention recently owing to its comparable photovoltaic performance and high stability as compared to organic and hybrid perovskites. However, cubic phase stabilization at room temperature for CsPbI3 still survives as a challenge. Herein we report all inorganic three-dimensional vertical CsPbI3 perovskite nanowires (NWs) synthesized inside anodic alumina membrane (AAM) by chemical vapor deposition (CVD) method. It was discovered that the as-grown NWs have... 

We propose two nonlinear regression methods, namely, Adversarial Orthogonal Regression (AdOR) for additive noise models and Adversarial Orthogonal Structural Equation Model (AdOSE) for the general case of structural equation models. Both methods try to make the residual of regression independent from regressors, while putting no assumption on noise distribution. In both methods, two adversarial networks are trained simultaneously where a regression network outputs predictions and a loss network that estimates mutual information (in AdOR) and KL-divergence (in AdOSE). These methods can be formulated as a minimax two-player game; at equilibrium, AdOR finds a deterministic map between inputs... 

Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. On the other hand, electrical load prediction is one of the important concerns of power systems so development of intelligent prediction tools for performing accurate predictions is essential. This study presents an intelligent hybrid approach called ACO-SA by hybridization of Ant Colony Optimization (ACO) and Simulated Annealing (SA). The hybrid approach consists of two general stages. At the first stage time series inputs will be fed into ACO and it performs a global search to find a globally optimum solution.... 

Online social networks, World Wide Web, media, and technological networks, and other types of so-called information networks are ubiquitous nowadays. These information networks are inherently heterogeneous and dynamic. They are heterogeneous as they consist of multi-Typed objects and relations, and they are dynamic as they are constantly evolving over time. One of the challenging issues in such heterogeneous and dynamic environments is to forecast those relationships in the network that will appear in the future. In this article, we try to solve the problem of continuous-Time relationship prediction in dynamic and heterogeneous information networks. This implies predicting the time it takes... 

This research explored the influences of shielding gases on the appearance of weld beads and the microstructures and mechanical properties of thin-wall samples using conventional gas metal arc welding as the heat source by using 5356 aluminium alloy welding wire as the raw materials and nitrogen (N2) and argon (Ar) as the shielding gases. The results showed that under the same parameters and after mono-layer single-bead welding was performed using N2 as the shielding gas, the bead height was higher, the bead width was narrower, and the penetration depth was shallower. The grain size of the thin-wall sample protected by N2 was 43.5–47.8 % smaller than that obtained under Ar protection.... 

Federated learning (FL) and split learning (SL) are state-of-the-art distributed machine learning techniques to enable machine learning without accessing raw data on clients or end devices. However, their comparative training performance under real-world resource-restricted Internet of Things (IoT) device settings, e.g., Raspberry Pi, remains barely studied, which, to our knowledge, have not yet been evaluated and compared, rendering inconvenient reference for practitioner. This work firstly provides empirical comparisons of FL and SL in real-world IoT settings regarding learning performance and on-device execution overhead. Our analyses demonstrate that the learning performance of SL is... 

We report the development of a metastasis-on-a-chip platform to model and track hepatocellular carcinoma (HCC)–bone metastasis and to analyze the inhibitory effect of an herb-based compound, thymoquinone (TQ), in hindering the migration of liver cancer cells into the bone compartment. The bioreactor consisted of two chambers, one accommodating encapsulated HepG2 cells and one bone-mimetic niche containing hydroxyapatite (HAp). Above these chambers, a microporous membrane was placed to resemble the vascular barrier, where medium was circulated over the membrane. It was observed that the liver cancer cells proliferated inside the tumor microtissue and disseminated from the HCC chamber to the... 

In this letter, we study the resource allocation for a multiuser intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits energy and information signals simultaneously to multiple energy harvesting receivers (EHRs) and information decoding receivers (IDRs) assisted by an IRS. Under this setup, we introduce a multi-objective optimization (MOOP) framework to investigate the fundamental trade-off between the data sum-rate maximization and the total harvested energy maximization, by jointly optimizing the energy/information beamforming vectors at the BS and the phase shifts at the... 

In this research, microstructure evaluation, mechanical properties and thermal conductivity of the Mg-SiCw/Cu composite with laminar structure were investigated. For this purpose, SiC whiskers were added to magnesium alloy by using stir-casting, then the Mg-SiCw composite was bonded to copper layers by warm accumulative roll bonding (ARB). Based on the results of optical microscopy (OM) and scanning electron microscopy (SEM), SiC whiskers were well distributed in the magnesium matrix and they were aligned parallelly when the composites were plastically deformed at higher rolling passes. Furthermore, all layers remained continuous with localized necking sites. Also, no intermetallic compounds... 

Branched hierarchical zinc oxide nanowires (BH-ZnO NWs) were fabricated successfully by a facile and rapid synthesis using two-step growth process. Initially, ZnO NWs have been prepared by anodizing zinc foil at room temperature and followed by annealing treatment. Then, the BH- ZnO NWs were grown on the ZnO NWs by a solution based method at very low temperature (31 oC). The BH- ZnO NWs with different aspect ratio were obtained by varying reaction time (0.5, 2, 5, 10 h). Photocatalytic activity of the samples was studied under both UV and visible light. The results indicated that the optimized BH-ZnO NWs (5 h) as a photocatalyst exhibited the highest photoactivity with about 3 times higher... 

We report the development of an efficient, customized spherical indentation-based testing method to systematically estimate the hydraulic permeability of gelatin methacryloyl (GelMA) hydrogels fabricated in a wide range of mass concentrations and photocrosslinking conditions. Numerical simulations and Biot's theory of poroelasticity were implemented to calibrate our experimental data. We correlated elastic moduli and permeability coefficients with different GelMA concentrations and crosslinking densities. Our model could also predict drug release rates from the GelMA hydrogels and diffusion of biomolecules into the three-dimensional GelMA hydrogels. The results potentially provide a design... 

Cloud computing environments provide users with Internet-based services and one of their main challenges is security issues. Hence, using Intrusion Detection Systems (IDSs) as a defensive strategy in such environments is essential. Multiple parameters are used to evaluate the IDSs, the most important aspect of which is the feature selection method used for classifying the malicious and legitimate activities. We have organized this research to determine an effective feature selection method to increase the accuracy of the classifiers in detecting intrusion. A Hybrid Ant-Bee Colony Optimization (HABCO) method is proposed to convert the feature selection problem into an optimization problem. We... 

Cloud computing environments provide users with Internet-based services and one of their main challenges is security issues. Hence, using Intrusion Detection Systems (IDSs) as a defensive strategy in such environments is essential. Multiple parameters are used to evaluate the IDSs, the most important aspect of which is the feature selection method used for classifying the malicious and legitimate activities. We have organized this research to determine an effective feature selection method to increase the accuracy of the classifiers in detecting intrusion. A Hybrid Ant-Bee Colony Optimization (HABCO) method is proposed to convert the feature selection problem into an optimization problem. We... 

In a photoacoustic (PA) imaging system, the detectors are bandwidth-limited. Therefore, they capture PA signals with some unwanted ripples. This limitation degrades the resolution/contrast and induces sidelobes and artifacts in the reconstructed images along the axial direction. To compensate for the limited bandwidth effect, we present a PA signal restoration algorithm, where a mask is designed to extract the signals at the absorber positions and remove the unwanted ripples. This restoration improves the axial resolution and contrast in the reconstructed image. The restored PA signals can be considered as the input of the conventional reconstruction algorithms (e.g., Delay-and-sum (DAS) and... 

Lightweight shell-based lattice structures with various multifunctional applications can be fabricated with limited manufacturing constraints, thanks to the advancements of additive manufacturing technologies. However, there is always a geometric deviation between the 3D digital model and the additively manufactured lattice structure. In some cases, the geometric deviations may be as small as the machine accuracy, but they would cause a significant decrease in the strength of the lattice. In other cases, the lattice may not be so sensitive to geometric deviations. The sensitivity of lattice structures to the geometric deviations depends on their constituent material, loading condition,... 

Group 6 transition metal dichalcogenides (G6-TMDs), most notably MoS2, MoSe2, MoTe2, WS2 and WSe2, constitute an important class of materials with a layered crystal structure. Various types of G6-TMD nanomaterials, such as nanosheets, nanotubes and quantum dot nano-objects and flower-like nanostructures, have been synthesized. High thermodynamic stability under ambient conditions, even in atomically thin form, made nanosheets of these inorganic semiconductors a valuable asset in the existing library of two-dimensional (2D) materials, along with the well-known semimetallic graphene and insulating hexagonal boron nitride. G6-TMDs generally possess an appropriate bandgap (1-2 eV) which is... 

Curcumin incorporated polyurethanes (CPU) are gaining much attention as a biomaterial. However, challenges are still remained due to hydrophobicity and low mechanical strength of CPU. Herein, we synthesized the CPU/ZnO nanocomposites with good mechanical and improved hydrophilic properties via in-situ polymerization. A series of curcumin incorporated polyurethane with different concentrations of ZnO nanoparticles (ZnCPU) are synthesized by using the curcumin, polyethylene glycol (PEG) as the soft segment, hexamethylene diisocyanate (HDI) as the hard segment, and 1,4-butanediol (BDO) as the chain extender. The addition of ZnO nanoparticles (NPs) facilitated the soft domain of PU which is... 

One of the technologies based on information technology used today is the VANET network used for inter-road communication. Today, many developed countries use this technology to optimize travel times, queue lengths, number of vehicle stops, and overall traffic network efficiency. In this research, we investigate the critical and necessary factors to increase the quality of VANET networks. This paper focuses on increasing the quality of service using multi-agent learning methods. The innovation of this study is using artificial intelligence to improve the network's quality of service, which uses a mechanism and algorithm to find the optimal behavior of agents in the VANET. The result... 

In this paper, the problem of content caching in 5G cellular networks relying on social-aware device-to-device (D2D) communications is investigated. Our focus is on how to efficiently select important users (IUs) and how to allocate content files to the storage of these selected IUs to form a distributed caching system. We aim at proposing a novel approach for minimizing the downloading latency and maximizing the social welfare simultaneously. In particular, we first model the problem of maximizing the social welfare as a many-to-one matching game based on the social property of mobile users. We study this game by exploiting users’ social properties to generate the utility functions of the... 

In this paper, the problem of content caching in 5G cellular networks relying on social-aware device-to-device communications (DTD) is investigated. Our focus is on how to efficiently select important users (IUs) and how to allocate content files to the storage of these selected IUs to form a distributed caching system. We aim at proposing a novel approach for minimizing the downloading latency and maximizing the social welfare simultaneously. In particular, we first model the problem of maximizing the social welfare as a many-to-one matching game based on the social property of mobile users. We study this game by exploiting users' social properties to generate the utility functions of the...