Sharif Digital Repository

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... 

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... 

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  

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... 

One of the security issues in data outsourcing scenario is the enforcement of data owner's access control policies. This includes some challenges; namely, the number of keys required to access authorized resources, efficient policy updating, write access control enforcement, user and data owner overhead, and preserving confidentiality of data and policies. Most of the existing solutions address only some of the challenges, while they impose high overhead on both the data owner and users. Though, policy management in the Role-Based Access Control (RBAC) model is easier and more efficient due to the existence of role hierarchical structure and role inheritance; most of the existing solutions... 

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  

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... 

In this article, a universal collaborative and competitive approach is introduced for deployment of digital collections in an ideal Digital Library for future's educational system. A hierarchical structure is proposed to be used for browsing and searching within mass of digital contents provided for union of curriculums worldwide. The collaborative and open-source aspects of the system guarantee the growth of the Digital Library. On the other hand, the competitive and reviewing aspects guarantee the accuracy of the novel library contents. Two experiments confirm the need for such a universal Digital Library worldwide to enhance learning capabilities, increase accessibility, avoid redundancy... 

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... 

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... 

Successful design and implementation of knowledge management systems have been the main concern of many researchers. It has been reported that more than 50% of knowledge management systems have failed, therefore, it is required to seek for a new and comprehensive scientific approach to design and implement it. In the design and implementation of a knowledge management system, it is required to know 'what we want to achieve' and 'how and by what processes we will achieve it'. A literature review conducted and axiomatic design theory selected for this purpose. For the first time, this paper develops a conceptual design of knowledge management systems by means of a hierarchical structure,... 

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... 

A modular hierarchical structure is developed to describe human movement planning level. The modular feature of the proposed model enables it to generalize planning a task. The movements are planned based on decomposing a task into its corresponding subtasks (motion phases). There is a module responsible for one condition. The final plan is constructed using soft computing of the plans proposed by different modules. Each module estimates the kinematics of the joints at the end of each subtask; we call them kinematic estimator modules (KEMs). A timing module estimates the duration of motion and a gating module determines the responsibility of each KEM under different conditions. To evaluate... 

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... 

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... 

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...