Sharif Digital Repository

With the increasing use of pervasive computing environments (PCEs), developing dynamic reconfigurable software in such environments becomes an important issue. The ability to change software components in running systems has advantages such as building adaptive, long-life, and self-reconfigurable software as well as increasing invisibility in PCEs. As dynamic reconfiguration is performed in error-prone wireless mobile systems frequently, it can threaten system safety. Therefore, a mechanism to support assured dynamic reconfiguration at run-time for PCEs is required. In this paper, we propose an Assured Dynamic Reconfiguration Framework (ADRF) with emphasis on assurance analysis. The... 

The production routing problem (PRP) merges the lot-sizing problem and the vehicle routing problem, two classical problems that have been the focus of comprehensive studies for over half a century. Solving the PRP is an effort to optimize decisions about the production, inventory, distribution, and routing in an integrated manner. In the literature of the recent decade, due to economic changes and regulatory issues, reverse logistics has become a focal point. Subsequently, the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) has drawn more and more attention for its considerable effect on the reverse logistics problem. In addition, one of the major arguments in supply... 

Continuous improvement and extension of pervasive computing environments, in which objects have high mobility and limited computing power, implies service migration to be considered as one of the main issues. On the other hand, context-awareness which is the most distinguishable feature of pervasive computing helps better serving of users. Accordingly, migration in the presence of context-awareness is considered as the underlying of our motivation. This improves the performance of migration, which is not easily achievable through traditional migration techniques. In this paper we introduce a model to support context-aware migration besides its migration process phases and framework. Our... 

High availability of software systems is an essential requirement for pervasive computing environments. In such systems self-adaptation, using dynamic reconfiguration is also a key feature. However, dynamic reconfiguration potentially decreases the system availability by making parts of the system temporary frozen, especially during incomplete or faulty execution of the reconfiguration process. In this paper, we propose Assured Dynamic Reconfiguration Framework (ADRF), consisting of run-time analysis phases, assuring the desired correctness and completeness of dynamic reconfiguration process. We also specify factors that affect availability of reconfigurable software in pervasive computing... 

Adaptive Reuse is a relatively new approach that aims to restore the relationship between humans and nature by providing a set of concepts and methods that lead to a sustainable interaction between the two. While the ecological approach is one of the most well-known sustainability sciences, it only considers the physical aspects of the relationship between humans and nature and does not account for its semantic dimensions. This research seeks to answer the question of which approach is most effective in establishing a stable relationship between humans and the environment. To achieve this, this article examines the theoretical foundations of Adaptive Reuse and the pathology of the... 

To improve the efficiency of electrochemical processes for environmental remediation, we present a new type of hybrid nanomaterials based on leaf-like copper-based quaternary transition metals and spongy monolayer graphene. To demonstrate the functionality of the hybrid electrocatalyst, fast and competent electrooxidation of water and glucose is shown. The mechanism of improved catalysis is ascribed to the synergetic catalytic effect of quaternary Cu-Ni-Fe-Co alloy with dendritic morphology along with the highly conductive and spongy structure of the graphene monolayer. It is shown that water oxidation can be performed at a low overpotential of 315 mV to reach a current denisty of 100 mA... 

Nowadays, the need for industrial processes with sufficient accuracy, efficiency, and flexibility to compete world markets is inevitable. On the other hand, the advent of control techniques and increased computation power of CPUs allow implementation of complex controllers using optimization techniques to provide higher efficiency and economic productivity. Model predictive control refers to a wide range of optimization-based control methods applying explicit models to predict its prospective use. These methods of control compute control signal by minimizing the cost function so that the process output becomes very close to the optimal path. In this paper, we use a new model predictive... 

Gasification of biomass in supercritical water is a successful technology for hydrogen production especially by using wet biomass. The whole process, from feeding to purification of hydrogen, consists of a lot of equipment, such as pumps, heat exchangers, heaters, reactors, etc. Because the main reactions take place in the gasification reactor, the gasifier is the most important equipment of the process. In this article, a thermodynamic model, including chemical equilibrium in the reactor that is based on Gibbs free energy minimization, is developed to estimate equilibrium composition for gasification of biomass in supercritical water for hydrogen production. For this analysis, we use three... 

Compared with fossil fuel, biomass is a clean energy with zero CO 2 emission, because CO 2 is fixed by photosynthesis during biomass growth and released again during utilization. Due to its low energy density, direct use of biomass is not convenient. Thus, it is necessary to convert biomass to fuel gas, such as hydrogen, which can be used cleanly and highly efficiently in fuel cell. Thermo-chemical gasification is likely to be the most cost-effective conversion process and it is promising technology for renewable hydrogen production by utilizing biomass. Biomass gasification produces a mixture of gases (mainly consisting of H 2, CO, CO 2, CH 4 and higher hydrocarbons), solids (char) and... 

Today, coordinated expansion planning is one of the key challenges for electricity systems including active distribution networks (ADNs) and transmission networks (TNs) hosting distributed renewable generation as well as large-scale wind energy generation. Accordingly, this study presents a decentralised hybrid robust and stochastic (HR&S) expansion planning optimisation method to determine a robust generation and transmission planning for a TN and stochastic expansion planning for ADNs. The proposed HR&S planning model is formulated with the objective of achieving an effective expansion of both TN&ADN while minimises the investment and operation costs of TN&ADN planning considering wind... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and... 

This paper presents a comprehensive operation model for micro-grids (MG) operating in the islanded mode. Various energy sources of a MG including diesel engine generator, micro-turbine, wind turbine and photovoltaic cell as well as battery storage and AC/DC rectifier/inverter are modeled in the proposed framework. Fuel costs, emission costs, and operation and maintenance (O&M) costs of these sources as well as their operating limits and characteristics are considered in the model. Furthermore, a new multi-cross learning-based chaotic differential evolution (MLCDE) algorithm is presented to solve the optimization problem of MG operation. The numerical results obtained from the proposed... 

A repeated inflation-unemployment game within the linear-quadratic frame-work of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

A repeated inflation-unemployment game within the linear-quadratic framework of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

This paper deals with the problem of multi-agent learning of a population of players, engaged in a repeated normal-form game. Assuming boundedly-rational agents, we propose a model of social learning based on trial and error, called "social reinforcement learning". This extension of well-known Q-learning algorithm, allows players within a population to communicate and share their experiences with each other. To illustrate the effectiveness of the proposed learning algorithm, a number of simulations on the benchmark game of "Battle of Sexes" has been carried out. Results show that supplementing communication to the classical form of Q-learning, significantly improves convergence speed towards... 

Highly dynamic nature of the applied loads on flexible and lightly damped offshore wind turbine (OWT) foundations affects the lifetime and serviceability of the system. In this study, the excessive vibration responses of OWTs are minimized using tuned mass dampers (TMD) and tuned liquid column dampers (TLCD). Due to high efficiency of TLCDs and TMDs for certain loading conditions, a combined TLCD-TMD is also utilized to improve the overall performance in a wide range of loading conditions. First, a parametric study was performed that highlights the sensitivity of these structural control devices. The effect of two devices on fixed offshore wind turbine foundations for the benchmark 5 MW NREL... 

In this research, a green solid catalyst of phosphomolybdic acid (HPA) prated on Chitosan was synthesized to produce biodiesel. The prepared catalyst was characterized using Fourier Transform Infrared spectroscopy (FTIR), Field Emission Scanning Electron Microscope (FESEM), Energy Dispersive X-Ray (EDX), X-ray diffraction (XRD), and XRF analyses. The catalyst was applied in microwave-assisted trans-esterification of Pomegranate oil, and the biodiesel production process was optimized by response surface methodology based on central composite design (RSM-CCD). The effect of influential reaction parameters, including time (33–142 min), catalyst weight (0.15–5.6 wt%), and methanol to oil molar... 

In the present paper, a practical thermal treatment process has been introduced to stress relieve the iron powders in a soft magnetic composite. The composites were pressed and treated at different pressures and temperatures. Also, some of the samples were treated for various periods of time at 200°C. Density, electrical resistivity and transverse rupture strength of the samples were measured and fracture surfaces were studied by SEM. A series of tests were performed to determine the DC magnetic properties of the samples. It has been shown that there are optimum amounts of resin content and compaction pressure and temperature, rather than time is the dominant factor in stress relief of the... 

In this study, internal microstrain of an iron-resin composite produced by powder metallurgy has been calculated using the Williamson-Hall method. The effects of microstrain evolution during different processing conditions on magnetic properties such as coercive force and hysteresis loss have been investigated. The results show that there are regular and similar changes of coercivity and hysteresis loss. Both of these properties are directly dependant on the pinning effect of the internal microstrain against the movement of magnetic domain walls during magnetization process. © 2006 Elsevier B.V. All rights reserved  

Cobalt-based catalysts were prepared on gamma alumina supports, and their behaviour for different Fischer-Tropsch synthesis (FTS) conditions was assessed. Although Co/γ-Al 2O 3 is a well-known FTS catalyst, its durability ought to be improved to make the industrial process economically feasible. The effect of lanthanum doping on the catalyst lifetime was examined utilising reactor tests and catalyst characterization techniques including TPR, ICP and N 2 porosimetry. Reactor test results revealed that an optimum amount of lanthanum improved catalyst activity and selectivity. Increasing amounts of lanthanum doping up to about 1.1wt% seemed to modify the chemical composition of the support...