Sharif Digital Repository

This paper utilizes IJA stochastic learning automaton for detecting noise and tuning value of alpha parameter which is used for image sharpening via gas diffusion model. The method has been applied to gray-scale images in an automatic and adaptive fashion. It is shown that the IJA automaton detects noise and can reform it appropriately. It glides the image to find the pattern of noise and replace it by the relevant characteristics of neighborhood to carry out the local restoration. Then, the automaton makes the image sharp with gas diffusion model by learning alpha parameter. The IJA automaton calculates appropriate local value for each pixel. Finally, experiments are presented and... 

In this correspondence, we focus on the performance analysis of the widely-used minimum description length (MDL) source enumeration technique in array processing. Unfortunately, available theoretical analysis exhibit deviation from the simulation results. We present an accurate and insightful performance analysis for the probability of missed detection.We also show that the statistical performance of the MDL is approximately the same under both deterministic and stochastic signal models. Simulation results show the superiority of the proposed analysis over available results  

A multi-product economic production quantity model with several real-world technical and physical constraints is developed in this paper. The cost function includes ordering, holding, backordering, lost sale, and the cost caused by unused space in the warehouse. The goal is to minimize the total inventory cost, where shortages are allowed and partially backordered with fixed and linear costs. The aim is to determine the length of the inventory cycle, the length of positive inventory period, and the backordering rates of the products during the shortage period in order to minimize the total inventory costs while satisfying all constraints. Due to complexity and non-linearity of the proposed... 

This paper presents a stochastic framework for day-ahead scheduling of microgrid energy storage systems (ESSs) in the context of multi-objective (MO) optimization. Operation cost of microgrid in normal conditions and load curtailment index in case of unscheduled islanding events (initiated by disturbances in the main grid) are chosen as main criteria of the proposed scheme. In practice, duration of disconnection from the upstream network is unknown in unscheduled islanding incidents and cannot be predicted with certainty. To properly handle the uncertainties associated with time and duration of such events as well as microgrid load and renewable power generation, stochastic models are... 

Caching has been widely considered an efficient way of reducing and balancing the growing traffic in communications networks in recent years. The cache network of interest consists of one content server connected via a shared link to a number of caching nodes, also known as a single bottleneck caching network. In this paper, for the first time, the stochastic requests traffic model in such networks is considered and a performance analysis is provided based on such a realistic assumption. In addition, we introduce new comprehensive performance metrics, which simultaneously take into account, the cache hit probability, load on the bottleneck link, and requests arrival rates. The main... 

A very simple and well-controlled procedure was employed to prepare CdS nanoparticle/few-layer MoS2 nanosheet/Indium tin oxide (ITO) thin film heterostructures. To tune and fabricate the CdS/MoS2(t)/ITO thin films with various surface topographies, first electrophoretic deposition (EPD) was used to deposit MoS2 nanosheets on the ITO substrate under an optimized applied potential difference (8 V) for different deposition times (t) of 30, 60, 120 and 240 s. Then, CdS nanoparticles were deposited via a successive ion layer adsorption and reaction (SILAR) technique. The highest photo-current density of 285 μA cm-2 was measured for the CdS/MoS2(60 s)/ITO sample, which was about 2.3 times higher... 

In diffusive molecular communication (DMC), the transmitter has to be able to control the release of signaling molecules for modulation of the information bits. In natural cells, pumping ions is an important control mechanism for releasing molecules which is carried out by ion pumps embedded in the membrane. The activity of the ion pumps is controlled by a driving parameter. In particular, light driven pumps are controlled by light intensity and enable a high degree of spatial and temporal control for modulation functionality. In this paper, a modulator based on ion pumps is proposed for DMC which controls the release rate of the molecules from the transmitter by modulating a light intensity... 

This paper addresses dynamic cell formation problem (DCFP) which has been explored vastly for several years. Although a considerable body of literature in this filed, two remarkable aspects have been significantly ignored so far, as uncertainty and human-related issues. In order to compensate such a shortage, this paper develops a bi-objective stochastic model. The first objective function of the developed model seeks to minimize total cost of machine procurement, machine relocation, inter-cell moves, overtime utilization, worker hiring/laying-off, and worker moves between cells; while the second objective function maximizes labor utilization of the cellular manufacturing system. In the... 

Online media play an important role in information societies by providing a convenient infrastructure for different processes. Information diffusion that is a fundamental process taking place on social and information networks has been investigated in many studies. Research on information diffusion in these networks faces two main challenges: (1) In most cases, diffusion takes place on an underlying network, which is latent and its structure is unknown. (2) This latent network is not fixed and changes over time. In this article, we investigate the diffusion network extraction (DNE) problem when the underlying network is dynamic and latent. We model the diffusion behavior (existence... 

In this paper, we consider a dual-sourcing model with constant demand and stochastic lead times. Two suppliers may be different in terms of purchasing prices and lead-time parameters. The ordering takes place when the inventory level depletes to a reorder level, and the order is split among two suppliers. Unlike previous works in the order splitting literature, the supply lead time between vendor and buyer as well as unit purchasing prices is considered to be order quantity dependent. The proposed model finds out the optimal reorder point, order quantity and splitting proportion, using a solution procedure. Numerical results show that neglecting the relationship between ordering batch size... 

Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two-stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average... 

Outpatient appointment scheduling problems have recently gained increasing attention. This paper provides a comprehensive review of recent analytical and numerical optimization studies that present decision-support tools for designing and planning outpatient appointment systems (OASs). A structure for organizing the recent literature according to various criteria is provided, including a framework that classifies decisions at the strategic, tactical, and operational levels. The OAS literature is evaluated from four perspectives: problem settings, environmental factors, modeling approaches, and solution methods. In addition, research gaps and areas of opportunity for future research are... 

Proliferation of distributed generations (DGs) and power-electronics-based loads is bringing about more harmonic-polluted power signals. While some failures may occur as a consequence of nonsinusoidal current or voltage waveforms, existing reliability models of protection relays have not taken the harmonic-related failures into consideration. This paper develops a comprehensive Markov reliability model to categorize the possible functional states of a component, say a transmission line, protected by a relay, operating in a harmonic-polluted environment. In order to make the proposed model practically tractable, it is further simplified in two ways, through merging the states of the same... 

Integrating independent dispatchable and non-dispatchable resources into a micro-grid platform enables the main power systems to benefit from the economic and environmental advantages of distributed generation while facilitating local, clean, and inexhaustible renewable energy production. Moreover, it makes the integrated components more visible and controllable for the whole power system. On the other hand, to properly handle multiple uncertainties inherent in the micro-grids, probabilistic energy management techniques are deployed. However, utilization of stochastic modeling and optimization tools for efficient, reliable, and cost-effective planning, operation, and control of micro-grids... 

A bi-objective stochastic capacitated multi-facility location–allocation problem is presented where the customer demands have Bernoulli distributions. The capacity of a facility for accepting customers is limited so that if the number of allocated customers to the facility is more than its capacity, a shortage will occur. The problem is formulated as a bi-objective mathematical programming model. The first objective is to find optimal locations of facilities among potential locations and optimal allocations of stochastic customers to the facilities so that the total sum of fixed costs of establishment of the facilities and the expected values of servicing and shortage costs is minimized. The... 

In this research, we employ Bayesian inference and stochastic dynamic programming approaches to select the binomial population with the largest probability of success from n independent Bernoulli populations based upon the sample information. To do this, we first define a probability measure called belief for the event of selecting the best population. Second, we explain the way to model the selection problem using Bayesian inference. Third, we clarify the model by which we improve the beliefs and prove that it converges to select the best population. In this iterative approach, we update the beliefs by taking new observations on the populations under study. This is performed using Bayesian... 

This paper presents a single-vendor, single-buyer integrated inventory model. We relax the assumption of deterministic lead-time in the hitherto existing joint economic lot sizing (JELS) models and analyze the problem where the buyer lead-time is a stochastic variable. Moreover, we consider the situation in which shortage is allowed. The vendor produces the product in batches and periodically delivers final goods at a fixed lot size to the customer, who has a constant demand rate. The proposed model, based on the integrated expected total relevant costs of both buyer and vendor finds out optimal values of reorder point, order quantity, and number of shipments, using a solution procedure.... 

A bi-objective stochastic capacitated multi-facility location–allocation problem is presented where the customer demands have Bernoulli distributions. The capacity of a facility for accepting customers is limited so that if the number of allocated customers to the facility is more than its capacity, a shortage will occur. The problem is formulated as a bi-objective mathematical programming model. The first objective is to find optimal locations of facilities among potential locations and optimal allocations of stochastic customers to the facilities so that the total sum of fixed costs of establishment of the facilities and the expected values of servicing and shortage costs is minimized. The... 

In some applicable scenarios, such as community patrolling, mobile nodes are restricted to move only in their own communities. Exploiting the meetings of the nodes within the same community and the nodes within the neighboring communities, a delay tolerant network (DTN) can provide communication between any two nodes. In this paper, two analytical models based on stochastic reward nets (SRNs) are proposed to evaluate the performance of the epidemic content retrieval in such multi-community DTNs. Performance measures computed by the proposed models are the average retrieval delay and the average number of transmissions. The monolithic SRN model proposed in the first step is not scalable, in... 

Single-molecule experiments have found near-perfect thermodynamic efficiency in the rotary motor F1-ATP synthase. To help elucidate the principles underlying nonequilibrium energetic efficiency in such stochastic machines, we investigate driving protocols that minimize dissipation near equilibrium in a simple model rotary mechanochemical motor, as determined by a generalized friction coefficient. Our simple model has a periodic friction coefficient that peaks near system energy barriers. This implies a minimum-dissipation protocol that proceeds rapidly when the system is overwhelmingly in a single macrostate but slows significantly near energy barriers, thereby harnessing thermal...