Sharif Digital Repository

In nature, most microorganisms have flexible micro/nanostructure tails, which help them create propulsion, reduce drag, or search for food. Previous studies investigated these flexible structures mostly from the propulsion creation perspective. However, the drag reduction and the underlying physical mechanisms of such tails are less known. This scientific gap is more significant when multi-polymeric/hierarchical structures are used. To fill the gap, we use the dissipative particle dynamics (DPD) method as a powerful fluid-polymer interaction technique to study the flexible tails' influences on drag reduction. Note that the flow regime for these microorganisms is in the range of laminar low... 

There has been a growing demand for materials with superior absorption capabilities, such as strong absorbing capacity, thin thickness, and light weight, to solve challenges related to EM radiation pollution. While the majority of the research is focused on optimizing material compositions, component microstructure and absorber structure are also critical factors for improving microwave absorption performance. In this research, we show how the microstructure of components and absorber design may increase dissipation features. Solvothermal and hydrothermal methods were utilized for synthesizing mesoporous CuS micro-particles with a 3D hierarchical structure as a dielectric component and... 

We propose a novel method for the clustering of point-cloud data that originate from single-molecule localization microscopy (SMLM). Our scheme has the ability to infer a hierarchical structure from the data. It takes a particular relevance when quantitatively analyzing the biological particles of interest at different scales. It assumes a prior neither on the shape of particles nor on the background noise. Our multiscale clustering pipeline is built upon graph theory. At each scale, we first construct a weighted graph that represents the SMLM data. Next, we find clusters using spectral clustering. We then use the output of this clustering algorithm to build the graph in the next scale; in... 

Apnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For... 

Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, and large silicon area provisioning. Prior work proposes hierarchical register file to reduce the register file power consumption by caching registers in a smaller register file cache. Unfortunately, this approach does not improve register access latency due to the low hit rate in the register file cache. In this article, we propose the Latency-Tolerant Register File (LTRF) architecture to achieve low latency in a two-level hierarchical... 

The cost-effective, robust, and efficient electrocatalysts for photoelectrochemical (PEC) water-splitting has been extensively studied over the past decade to address a solution for the energy crisis. The interesting physicochemical properties of CuO have introduced this promising photocathodic material among the few photocatalysts with a narrow bandgap. This photocatalyst has a high activity for the PEC hydrogen evolution reaction (HER) under simulated sunlight irradiation. Here, the recent advancements of CuO-based photoelectrodes, including undoped CuO, doped CuO, and CuO composites, in the PEC water-splitting field, are comprehensively studied. Moreover, the synthesis methods,... 

A surface to separate oil–water mixtures is a global concern and highly needed particularly in oil industries. The present study was conducted to create a novel superhydrophilic/superoleophobic nanocomposite coating on the stainless-steel mesh for the aim of oil/water separation. Different hydrophilic resins along with PFOA as oleophobic agent with 15 flours in its chemical structure and various oxide nanoparticles containing SiO2 and TiO2 at different concentrations were studied to achieve superhydrophilic/superoleophobic surface. The fabricated nanocomposites were fully characterized via field-emission scanning microscopy (FESEM), atomic force microscopy (AFM) and Fourier-transform... 

Here, an excellent superhydrophobic and highly oleophobic nanocomposite coating composed of fluoroethylene-vinyl ether (FEVE) resin as a matrix for modified SiO2 nanoparticles was synthesized on a stainless-steel wire mesh substrate via a facile sol-gel method. The surface morphology, microstructure, composition, and roughness of the coatings were investigated by field emission scanning electron microscopy (FESEM) equipped with energy-dispersive spectroscopy (EDS) and atomic force microscopy (AFM). The most efficient coating with superhydrophobicity and high oleophobicity feature indicates the water and oil repellency with contact angles (CAs) of 152° and 141°, respectively, with the high... 

Drop motion on different types of new proposed micro-structure surfaces has been numerically investigated to find the optimum structure in view point of ice formation delaying. The droplet automatically moves on the inclined surfaces due to gravity forces. To validate the numerical algorithm, three different bench mark problems have been considered. The results indicate that the present algorithm is trustable for the presented numerical simulations. Then the validated numerical approach has been used to simulate droplet motion on nine proposed superhydrophobic surfaces in the same conditions. Comparison the drop motion on different micro-structure surfaces at different time indicate that... 

Skeletal muscle tissue engineering aims to fabricate tissue constructs to replace or restore diseased or injured skeletal muscle tissues in the body. Several biomaterials and microscale technologies have been used in muscle tissue engineering. However, it is still challenging to mimic the function and structure of the native muscle tissues. Three-dimensional (3D) bioprinting is a powerful tool to mimic the hierarchical structure of native tissues. Here, 3D bioprinting was used to fabricate tissue constructs using gelatin methacryloyl (GelMA)-alginate bioinks. Mechanical and rheological properties of GelMA-alginate hydrogels were characterized. C2C12 myoblasts at the density 8 × 106 cells/mL... 

The Internet of Things (IoT) technology enables numerous things with different processing power and storage capacity to communicate and share data with each other. Considering the constrained devices of the IoT network in terms of processing and storage, designing a lightweight authentication scheme is quite important. So in this paper, we propose a lightweight authentication scheme based on Chebyshev Chaotic Maps. In the proposed scheme we apply a hierarchical structure to define different access controls for various entities. We then provide a formal analysis via the BAN logic to show the security of our scheme. Moreover, we compare our proposed scheme with previous ones in terms of... 

Hierarchical reinforcement learning facilitates learning in large and complex domains by exploiting subtasks and creating hierarchical structures using these subtasks. Subtasks are usually defined through finding subgoals of the problem. Providing mechanisms for autonomous subgoal discovery and skill acquisition is a challenging issue in reinforcement learning. Among the proposed algorithms, a few of them are successful both in performance and also efficiency in terms of the running time of the algorithm. In this paper, we study four methods for subgoal discovery which are based on graph partitioning. The idea behind the methods proposed in this paper is that if we partition the transition... 

The Internet of Things (IoT) technology enables numerous things with different processing power and storage capacity to communicate and share data with each other. Considering the constrained devices of the IoT network in terms of processing and storage, designing a lightweight authentication scheme is quite important. So in this paper, we propose a lightweight authentication scheme based on Chebyshev Chaotic Maps. In the proposed scheme we apply a hierarchical structure to define different access controls for various entities. We then provide a formal analysis via the BAN logic to show the security of our scheme. Moreover, we compare our proposed scheme with previous ones in terms of... 

Human motion planning studies are of considerable importance in producing human-like trajectories for various industrial or clinical applications (e.g. assistive robots). In this case, the capability of Central Nervous System (CNS) in generating a large repertoire of actions can be inspirational to develop more efficient motion planning approaches. Here, inspired by structural and functional modularity in the CNS, a novel modular and hierarchical model is developed to plan the sit-to-stand (STS) transfer under varying environmental conditions. In this model, the planning process is distributed among several functionally simple modules. The cooperation of modules enables the model to plan the... 

In large-scale power systems, classical centralized control approaches may fail due to geographically distribution of information and decentralized controllers result in sub-optimal solution for load-frequency control (LFC) problems. In this paper, a two-level structure is presented to obtain optimal solution for LFC problems and also reduce the computational complexity of centralized controllers. In this approach, an interconnected multi-area power system is decomposed into several sub-systems (areas) at the first-level. Then an optimization problem in each area is solved separately, with respect to its local information and interaction signals coming from other areas. At the second-level,... 

Recently, there has been a growing attention in frequent itemset mining in distributed systems. In this paper, we present an algorithm to extract frequent itemsets from large distributed datasets. Our algorithm uses gossip as the communication mechanism and does not rely on any central node. In gossip based communication, nodes repeatedly select other random nodes in the system, and exchange information with them. Our algorithm proceeds in rounds and provides all nodes with the required support counts of itemsets, such that each node is able to extract the global frequent itemsets. For local iteration and generation of candidate itemsets, a trie data structure is used, which facilitates the... 

A set of recursive equations are introduced for optimum design of a wide range of hierarchical truss beams to satisfy a minimum required natural frequency. The design equations are based on a general analytical solution, which are derived based on a critical dimensional analysis. A practical example is examined in both 2D and 3D spaces, which promises substantial mass reduction, as much as 99%, when using high order hierarchical truss beams. The results are verified by numerical evaluation of three case studies. The approach looks also very promising to design nanostructures when it comes to the problems associated with vibration  

This paper addresses the issue of finding and accessing desired items when a large amount of data items are concerned, by proposing some concepts based on Tree Search Structure -a hierarchical structure for information retrieval. The proposed concepts are applicable to several environments such as File Managers on PCs, help tree views, site maps, taxonomies, and cell phones. A software tool, FTS (File Tree Search), that is developed to utilize the proposed concepts is also presented  

The hierarchical structure of real-world problems has resulted in a focus on hierarchical frameworks in the reinforcement learning paradigm. Preparing mechanisms for automatic discovery of macro-actions has mainly concentrated on subgoal discovery methods. Among the proposed algorithms, those based on graph partitioning have achieved precise results. However, few methods have been shown to be successful both in performance and also efficiency in terms of time complexity of the algorithm. In this paper, we present a SCC-based subgoal discovery algorithm; a graph theoretic approach for automatic detection of subgoals in linear time. Meanwhile a parameter tuning method is proposed to find the... 

In this research, an adaptive control system is designed for a safe touchdown of an unmanned helicopter during its landing phase on a 6DOF moving platform. In this paper the landing phase is divided into the approach and touchdown stages. In the first stage, the helicopter tries to attenuate the initial position and direction errors and in the next stage, the platform's attitude is tracked for a safe touchdown. The hierarchical structure of the proposed control system includes supervisory and tracking levels. The supervisory level recognizes the landing stage and the tracking level controls and compensates the errors based on SDRE (State Dependent Riccati Equation) method. The robustness and...