Sharif Digital Repository

Data envelopment Analysis is a non parametric technique which estimates the efficiency of a decision making unit in compare with others. In correspondent literature this unit’s Inputs and outputs are often assumed to be deterministic, but in recent years different approaches which viewing the data as non deterministic are presented. In this study we propose an algorithm for determining the stability region of a DMU while we assume other DMUs’ data are fixed. This algorithm is based on changing the reference set of the under investigation DMU. In fact applying these changes make the DMU move toward other DMUs’ efficient frontiers and by using this fact it is possible to determine the... 

Long-term deactivation of a commercial K-promoted Fe2O3 catalyst used in the dehydrogenation of ethylbenzene to styrene monomer was studied using thirty months of operating data of three industrial SM radial fixed bed adiabatic reactors. The Langmuir-Hinshelwood, Hougen-Watson model (LHHW) was used for reaction kinetics modeling. The kinetics of coking from ethylbenzene and styrene and the short-term deactivation function due to the quick coke formation were also considered in the model. The kinetics of long-term deactivation of the catalyst for ethylbenzene dehydrogenation to styrene between 550 and 630 °C were determined by allowing the effects of temperature and time on the catalyst... 

The main goal in many fields in the empirical sciences is to discover causal relationships among a set of variables from observational data. PC algorithm is one of the promising solutions to learn underlying causal structure by performing a number of conditional independence tests. In this paper, we propose a novel GPU-based parallel algorithm, called cuPC, to execute an order-independent version of PC. The proposed solution has two variants, cuPC-E and cuPC-S, which parallelize PC in two different ways for multivariate normal distribution. Experimental results show the scalability of the proposed algorithms with respect to the number of variables, the number of samples, and different graph... 

In the communication systems, the raw signals of information are mainly encoded so as to prevent the detrimental effects of channel noises and distortions. After some processes, this encoded signal is passed through the channel. At the receiver side, the received signal has to be decoded to extract the information signal. In order to decode the received signal, the receiver require prior knowledge about the encoder parameters. The traditional approach is to send the encoder parameters along with the encoded signals. However, this transmission overhead might occupy a considerable amount of bandwidth since the type of coding may alter several times in a fraction of a second based on the... 

Positioning refers to the process of estimating the receiver coordinates aiming for an accurate understanding of the surrounding environment. This branch of science has attracted considerable attention in recent years. Today, the influence sphere of positioning is so expanded that encompasses applications in daily life (e.g., navigation) as well as commercial and even military fields. Global Positioning System (GPS) is the most widely used tool in real-time positioning. Because GPS imposes great measurement errors in challenging conditions (e.g., turbulent water environments), alternative methods such as methods based on Wi-Fi, Bluetooth, and visible light have been proposed. Benefiting... 

Cardiovascular diseases are the first leading cause of death in the world also in IRAN. Early detection of such problems can decrease the costs also can help to cure the patient but it needs continuous monitoring and automated classification of hearbeats. Mobile devices and wearable gadgets are good solutions which can help patients before visiting the doctor.In this research, an algorithm is introduced which with the help of ECG signal detects dangerous myocardial problems. Our approach is using deep learning method which were not considered much before. In the proposed algorithm ECG signal is processed in order to get features and with dimensionality reduction, input of the network gets... 

We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene on one of the variables in the system in each step and uses the results of the intervention to recover further causal relationships among the variables. The goal is to fully identify the causal structures with minimum number of interventions. We present the first deep reinforcement learning based solution for the problem of experiment design. In the proposed method, we embed input graphs to vectors using a graph neural network and feed them to another neural network which outputs a variable for performing... 

The thesis title is “Modeling of a vague problem (Floating Breakwater by BEM Analysed) using ANFIS (Adaptive Neuro-Fuzzy Inference System) and validation by Fuzzy Boundary Element Method”. In this set of material, more important definitions are described below. When some input data is linguistics, or we have lack of Information or Vagueness, Fuzzy toolbox can alleviate the problem. Fuzzy concept includes several fields and applications like; fuzzy logic, fuzzy sets, fuzzy control, fuzzy arithmetic and fuzzy inference, and the last two applications are used in this thesis. The Neural network is a black box, Neurons that can justify their actions and these artificial brains can grow. The... 

Lean manufacturing, was published as a research work named “the machine that changed the world” by James Womack and his assistants in MIT in 1990. Lean thinking can be presented in five principles: specifying what creates value, identifying value stream, creating value flow, make only what is pulled by the customer, and strive for perfection. In contrast with what is generally believed that lean manufacturing can only be used in production systems, lean tools and methods can be used in administrative departments of a factory or in a service firm. In such processes, not only hardware, but also service added values should be considered using information and the software service tools. In this... 

Tsunami, like many other natural disasters leaves people a short time for escape. When talking about Tsunami, the escape time is the period it takes for the wave to start moving from the epicenter, change into a giant wave gradually and reach to a cost. In order to minimize damages of this phenomenon, the escaped time has to be estimated without delay. For this purpose the first needed action is modeling the Tsunami waves. Analytical and numerical models and software that are designed based on them do exist. To have an efficient and rapid Tsunami alarming system all of these options are examined in this project. Then having a reliable model quite a few probable scenarios are propounded. The... 

The increasing need of processing power and low power computation in embedded systems is leading to the deployment of multi-core embedded systems. One important constraint in real-time embedded systems is their predictable behavior. To meet this constraint, scratchpad memory (SPM) is introduced. SPM as an on-chip SRAM memory is highly vulnerable to soft errors. As on-chip memories (SPM and cache) contain the most frequently used blocks of the program, hence errors in them can easily propagate in the system leading to erroneous results. Employing traditional mechanisms such as ECC to protect SPM incur significant power and performance overheads and therefore they are not efficient for many of... 

Investigation of transport and deposition of aerosol particles attracts interests in many fields of sciences. Various numerical and computational methods has been utilized in particulate flows studies. In recent relevant researches lattice Boltzmann method has been widely used and is reported to be a robust and efficient method. In present study, numerical investigation of dispersion and deposition of aerosol particles is performed in curved and bifurcating channels using LBM. Fluid flow simulations are performed using LBM while one-way coupling Lagrangian point of view is used for particle tracking. As the first showcase, transport and deposition of aerosol particles in channel flow with... 

Mesoporous silica nanoparticles have broad application in drud delivery systems due to their porous structure, functionalization, biocompatibility, high surface area and pore volume. Neverthless, pure mesoporous silica nanoparticles without functionality were not smart material and could not release drug in triggered and controlled manner. For this reason, using smart polymeric coating would be considered. Polymer shells also provide colloidal stability, improved blood circulation lifetime and reduced toxicity which are crucial for efficient in vivo drug delivery. Inflammatory and tumor tissue have low pH and high temperature as compared to health tissue. Therefore, using pH and... 

Final control elements usually have nonlinear dynamics which affect the stability of the closed- loop system. Four most common types of these nonlinearities are dead-zone, backlash, hysteresis and saturation. Because most of final control elements especially in chemical processes are subjected to saturation constraint and also due to lack of generaland practical control scheme to handle this limitation, our concentration will be focused on saturation nonlinearity. In this work, based on sliding mode control strategy, a control scheme for multi-input multi-state systems in the presence of input saturation is presented. Some numerical simulations are carried out to show the effectiveness of...