Sharif Digital Repository

The Gnutella protocol requires peers to broadcast messages to their neighbors when they search files. The message passing generates a lot of traffic in the network, which degrades the quality of service. We propose the new method to optimize the speed of search and to improve the quality of service in a Gnutella based peer-to-peer environment with using semantic routing and priority of nodes. Once peers generate their "friends lists", they use these lists to route queries in the network. This helps to reduce the search time and to decrease the network traffic by minimizing the number of messages circulating in the system as compared to standard Gnutella  

In order to monitor auto-correlated processes, many kinds of model-free control charts have been recently proposed based on the methods used in simulation output analysis. However, these control charts always have a restricting assumption that a large volume of observations is available while defects within them are scarce (zero-defect or high-quality processes). In this paper, we develop a new type of model-free unweighted batch means control charts, called grouped batch means (GBM) to monitor autocorrelated processes. In addition to its better performance in some cases, the GBM control chart can be applied not only to high-quality processes but also to all kinds of auto-correlated... 

Since the product quality of many industrial processes depends upon more than one dependent variable or attribute, they are either multivariate or multi-attribute in nature. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In this article, we develop a new methodology to monitor multi-attribute processes. To do this, first we transform multi-attribute data in a way that their marginal probability distributions have almost zero skewness. Then, we estimate the transformed covariance matrix and apply the well-known T2 control chart. In order to illustrate the proposed method... 

On-line optimization for the base case of the Tennessee Eastman (TE) challenge problem is presented; furthermore, an interesting operating condition near base case has been obtained, which results in a lower cost function. The proposed method is based on the estimation of the internal states and the time varying parameters of the process model based on an Extended Kalman filter. The sequential quadratic programming method has been used to accomplish the non-linear programming (NLP) task. The objective function is the operational cost while the constraints are the reactor mass balance, safe operation of the process equipment, and the conditions that satisfy the product quality and flow. The... 

The earned value is a leading technique in monitoring and analyzing project performance and project progress. Although, it allows exact measurement of project progress, and can uncover any time and cost deviations from the plan, its capability in reporting accepted level of deviation is not well studied. This study presented an approach to overcome this limitation by applying statistical quality control charts to monitor earned value indices. For this purpose, project time and cost performance indices of a real construction project were monitored regularly on individual control charts. The results were quite promising, and not only competed well against traditional approaches, but also... 

knowing the time of a process change would simplify the search, identification, and removal of the special causes that disturbed the process. Since, in many real world manufacturing systems, the production of goods comprises several autocorrelated stages; in this paper, the problem of the change point estimation for such processes is addressed. A first order autoregressive model (AR(1)) is used to model a multistage process observations, where a X -chart is established for monitoring its mean. A step change is assumed for the location parameter of the model. After receiving an out-of-control signal, in order to determine the stage and the sample that caused the change (hence finding the time... 

Statistical process control methods for monitoring processes with univariate or multivariate measurements are used widely when the quality variables fit to known probability distributions. Some processes, however, are better characterized by a profile or a function of quality variables. For each profile, it is assumed that a collection of data on the response variable along with the values of the corresponding quality variables is measured. While the linear function is the simplest, it occurs frequently that many of the nonlinear functions may be transferred to linear functions easily. This paper proposes a control chart based on the generalized linear test (GLT) to monitor coefficients of... 

This paper introduces the concept of mapping of Artificially Intelligent (AI) computational systems. The concept of homunculus from human neurophysiology is extended to AI systems. It is assumed that an AI system behaves similarly to a mini-column or ganglion in the natural animal brain that comprises a layer of afferent (input) neurons, a number of interconnecting processing cells, and a layer of efferent (output) neurons or organs. The objective of the present study was to identify the correlation between the stimulus to each afferent neuron and the corresponding response from each efferent organ when the intelligent system is subjected to certain stimuli. To clarify the general concept, a... 

Many actions have been taken by researchers to design an appropriate controller for a quadruped robot. These efforts can be divided into two main categories: analytical and intelligent methods. The analytical method is based on the motion equations of the robot which are mostly complicated. These complication leads to difficulty in implementation. In contrast, there exists intelligent method which is based on the learning algorithms. Despite lots of improvements in the controlling of the quadruped robots, their ability of walking is still far less from the four legged animals' capability. Many researchers believe that four legged animals owe this priority to the learning attribute. Therefore... 

Object-oriented frameworks are widely used to develop new applications. They provide reusable concepts that are instantiated in application code through potentially complex implementation steps such as subclassing, implementing interfaces, and calling framework operations. Unfortunately, many modern frameworks are difficult to use because of their large and complex APIs and frequently incomplete user documentation. To cope with these problems, developers often use existing framework applications as a guide. However, locating concept implementations in those sample applications is typically challenging due to code tangling and scattering. To address this challenge, we introduce the notion of... 

Efficient control of gas metal arc welding process enables us to have high quality products in consequence of achieving high quality weld. In this paper, an extended dynamic matrix controller is designed and applied on the gas metal arc welding process, which is considered as a nonlinear multi-inputs multi-outputs system. In order to reach a high quality weld, the outputs, welding current and arc length, are effectively controlled by open circuit voltage and wire feed speed. The structure and performance of the proposed controller are discussed in detail, and then a set of simulation results is presented to verify its efficiencies  

Recently, data stream has become popular in many contexts of data mining. Due to the high amount of incoming data, traditional clustering algorithms are not suitable for this family of problems. Many data stream clustering algorithms proposed in recent years considered the scalability of data, but most of them did not attend the following issues: (1) The quality of clustering can be dramatically low over the time. (2) Some of the algorithms cannot handle arbitrary shapes of data stream and consequently the results are limited to specific regions. (3) Most of the algorithms have not been evaluated in multi-density environments. Identifying appropriate clusters for data stream by handling the... 

Processing time and segmentation quality are two main factors in evaluation of image segmentation methods. Oversegmentation is one of the most challenging problems that significantly degrade the segmentation quality. This paper presents a framework for decreasing the oversegmentation rate and improving the processing time. Significant variations in both color and texture spaces are the main reasons that lead to oversegmentation. We exploit Affine Invariant Region Detectors to mark regions with high variations in both color and texture spaces. The results are then utilized to reduce the oversegmentation rate of image segmentation algorithms. The performance of the proposed framework is... 

In this research, Repetitive Group Sampling (RGS) plans are developed for the Weibull and generalized exponential distributions. To design the proposed plans, the median of a life-time is first used as the quality parameter. Then, a decision-making framework is developed, based on first and second type errors. Next, based on acceptable and limiting quality level criteria, tables are obtained to select the parameters of the proposed decision-making framework. The advantages of the proposed method over single sampling plans are discussed at the end  

Control charts are the best tools to monitor main process parameters, and the Multivariate Exponentially Weighted Moving Average, MEWMA, type of this tool is used when there are several correlated quality characteristics to be monitored simultaneously where detecting small deviations of the characteristics is desired. In this paper, the models of both the economic and the economic-statistical design problems of MEWMA control charts are solved by a Particle Swarm Optimization (PSO) approach. The comparison study between the economic and the economic-statistical designs shows better statistical performances of the economic-statistical design with negligible increase in cost. Furthermore, in...