Sharif Digital Repository

In this investigation, a systematic sequential intelligent system is proposed to provide the surgeon with an estimation of the state of the tool-tissue interaction force in laparoscopic surgery. To train the proposed intelligent system, a 3D model of an in vivo porcine liver was built for different probing tasks. To capture the required knowledge, three different geometric features, i.e. Y displacement of the nodes on the upper surface and slopes on the closest node to the deforming area of the upper edge in both X-. Y and Z-. Y planes, were extracted experimentally. The numerical simulations are conducted in three independent successive stages. At the first step, a well-known... 

In this study, the self-adaptive evolutionary (SaE) agent is employed to structure the contributing elements to process the management of extreme learning machine (ELM) architecture based on a logical procedure. In fact, the SaE algorithm is utilized for possibility of enhancing the performance of the ELM to estimate daily soil temperature (ST) at 6 different depths of 5, 10, 20, 30, 50 and 100 cm. In the developed SaE-ELM model, the network hidden node parameters of the ELM are optimized using SaE algorithm. The precision of the SaE-ELM is then compared with the ELM model. Daily weather data sets including minimum, maximum and average air temperatures (Tmin, Tmax and Tavg), atmospheric... 

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,... 

The development of a multiple model-based identification algorithm is addressed in this paper for nonlinear modeling of a conventional aircraft in the entire flight envelope. The dynamic model of an aircraft varies significantly depending on changes in the flight condition of the air vehicle including the altitude and the equivalent air speed. Therefore, the conventional identification approaches for generating a single nonlinear model with time-invariant parameters cannot be used in the entire flight envelope of an aircraft. Accordingly, a multiple model-based approach using nonlinear autoregressive exogenous neural networks is introduced in this paper as a powerful tool in identifying... 

Extraction of fetal electrocardiogram (FECG) from the abdominal region of the mother’s skin is challenge task due to the high overlapping of maternal and fetal signals in this area. To overcome the problem, this paper proposes the utilization of extreme learning model (ELM) as the prediction algorithm to train on the FECG signal extracted by least mean square approach from the input abdominal and thoracic signals. The trained ELM model is used to model the FECG signal for the testing samples. Also, this paper investigates the firefly algorithm (FA) to tune the parameters of ELM and improve its performance. Due to the high complexity and too many parameters of FA, this paper embeds the... 

Secure operation of protective intelligent electronic devices (IEDs) has been recognized as a crucial issue for power grids. By gaining access to substation IEDs, intruders can severely disrupt the operation of protection systems. This paper develops an analytical reliability assessment framework for quantifying the impacts of the hypothesized integrity attacks against protection systems. Petri net models are used to simulate possible intrusion scenarios into substation networks. The cyber network model is constructed from firewall, intrusion prevention system (IPS), and password models, which are three types of defense mechanisms for protecting substation networks. In this paper, two main... 

It is widely recognized that knowledge is an essential strategic resource for a firm to achieve sustainable competitive advantage and Knowledge Management (KM) is a fundamental concept for those interested in the ever changing business world. However, KM has received little attention in Small and Medium sized Enterprises (SMEs). Unique characteristics of SMEs affect their approach in knowledge management, so different KM processes should be applied in these firms. SMEs have very simple structures, so they have less difficulty in managing their internal knowledge than large organizations. But this is not the case for external knowledge management, especially external knowledge acquisition... 

Clustering the web documents is one of the most important approaches for mining and extracting knowledge from the web. Recently, one of the most attractive trends in clustering the high dimensional web pages has been tilt toward the learning and optimization approaches. In this paper, we propose novel hybrid harmony search (HS) based algorithms for clustering the web documents that finds a globally optimal partition of them into a specified number of clusters. By modeling clustering as an optimization problem, first, we propose a pure harmony search-based clustering algorithm that finds near global optimal clusters within a reasonable time. Then, we hybridize K-means and harmony clustering... 

Clustering is one of the most important approaches for mining and extracting knowledge from the web. In this paper a method for clustering the web data is presented which using a Bayesian network, finds appropriate representatives for each of the clusters. Having those representatives, we can create more accurate clusters. Also the contents of the web pages are converted into vectors which firstly, the number of dimensions is reduced, and secondly the orthogonality problem is solved. Experimental results show about the high quality of the resultant clusters. © Springer-Verlag Berlin Heidelberg 2007  

Conventional features for speech recognition have not been evaluated in terms of importance in human speech recognition. In this paper a method for extracting important features in an interactive process has been introduced. This method can be used as an aid for experts in an ASR expert system. It has also been shown, as an application of our method, how an expert might find out the distinguishing features between "m" and "n". As another use, it has been illustrated that how our method could be used to check the sufficiency of information in the quantized filter-bank for speech recognition  

This paper presents UOWD-Sharif team's approach for XML information retrieval. This approach is an extension of PLIR which is an experimental knowledge-based information retrieval system. This system like PLIR utilizes plausible inferences to first infer the relevance of sentences in XML documents and then propagates the relevance to the other textual units in the document tree. Two approaches have been used for propagation of confidence. The first approach labeled "propagate-DS" first propagates the confidence from sentences to upper elements and then combines these evidences by applying Dempster-Shafer theory of evidence to estimate the confidence in that element. The second approach... 

Organisational commitment is suggested as a remarkable variable in shaping employees’ attitudes toward knowledge management practices. Customer trust in services is established during a long-time relationship with a firm and improves the accuracy of information shared with employees. To put it in other words, customer trust is what a service company needs to maintain its competitive advantage. On the other hand, high employee turnover reflects a substantial loss of knowledge. In the present study, the impact of organisational commitment on employees’ retention, knowledge acquisition, and sharing was examined regarding the moderating roles of leader-member exchange and innovation climate. The...