Sharif Digital Repository

In this paper, a novel reinforcement learning method inspired by the way humans learn from others is presented. This method is developed based on cellular learning automata featuring a modular design and cooperation techniques. The modular design brings flexibility, reusability and applicability in a wide range of problems to the method. This paper focuses on analyzing sensitivity of the method's parameters and the applicability in optimization problems. Results of the experiments justify that the new method outperforms similar ones because of employing knowledge sharing technique, reasonable exploration logic, and learning rules based on the action trajectory  

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... 

An important reason to prefer dependency parsing over classical phrased based methods, especially for languages such as Persian, with the property of being “free word order”, is that this particular property has a negative impact on the accuracy of conventional parsing methods. In Persian, some words such as adverbs can freely be moved within a sentence without affecting its correctness or meaning. In this paper, we illustrate the robustness of dependency parsing against this particular problem by training two well-known dependency parsers, namely MST Parser and Malt Parser, using a Persian dependency corpus called Dadegan. We divided the corpus into two separate parts including only... 

Purpose – This paper aims to provide a criteria-based evaluation framework for assessing knowledgemanagement system (KMS) development methodologies. Design/methodology/approach – The evaluation criteria have been elicited based on the features expected from a successful KMS. Furthermore, a number of prominent KMS development methodologies have been scrutinized based on the proposed evaluation framework. Findings – It was demonstrated that the proposed evaluation framework is detailed and comprehensive enough to reveal the strengths and weaknesses of KMS development methodologies. It was also revealed that even though the evaluated methodologies possess certain strong features, they suffer... 

Currently, the main portion of knowledge is stored in electronic texts and documents and for transferring that knowledge effectively, we must use proper methods to gather and retrieve relevant information. Ontologies provide means to produce structured documents and use intelligent search instead of keyword search. Ontology defines the common words and concepts used to describe and represent an area of knowledge. However, developing ontologies is a time consuming and labor work. So, many ontology developers try to facilitate and speed up this process by reusing other resources. In fact, thesaurus contains semantic information and hierarchical structure that make it an appropriate resource... 

A phenolic-based ionic liquid (IL), 1-(2-hydroxyethyl)-2,3-dimethylimidazolium phenoxide has been introduced for 1.5 molar carbon dioxide (CO2) absorption at ambient conditions without using special methodologies or precautions. The structure of the IL was characterized by various methods such as FT-IR, 1H NMR, 13C NMR, elemental analysis (EA) and thermogravimetric analysis (TGA). The ability of this IL for CO2 uptake reaches to its maximum value after 2 h. The IL has been reused fr several times with constant efficiency. Density functional theory (DFT) calculations at the B3LYP/6-311++G∗∗ level of calculation have been carried out to gain more structural knowledge... 

The authors deal with the robust design of multiple-input-multiple-output (MIMO) space-time transmit code (STTC) and space-time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation... 

Retinal vessels tortuosity is one of the important signs of cardiovascular diseases such as diabetic retinopathy and hypertension. In this paper we present a simple and efficient algorithm to measure the grade of tortuosity in retinal images. This algorithm consists of four main steps,vessel detection, extracting vascular skeleton via thinning, detection of vessel crossovers and bifurcations and finally calculating local and global tortuosity. The last stage is based on a circular mask that is put on every skeleton point of retinal vessels. While the skeleton of vessel splits the circle in each position, the local tortuosity is considered to be the bigger to smaller area ratio. The proposed... 

A wide range of scheduling algorithms used in the data centers have traditionally concentrated on enhancement of performance metrics. Recently, with the rapid growth of data centers in terms of both size and number, the power consumption has become a major challenge for both industry and society. At the software level, energy-aware task scheduling is an effective technique for power reduction in the data centers. However, most of the currently proposed energy-aware scheduling approaches are only paying attention to computation cost. In the other words, they ignore the energy consumed by the network equipment, namely communication cost. In this paper, the problem of scheduling... 

Business process reengineering (BPR) can help organisations to identify and improve their business processes. A major problem is the high volume of business process datasets with characteristics such as high dimensionality, noise, uncertainty in process datasets and complicated interactions among process variables. Data mining (DM) techniques facilitate the identification and analysis of business processes, and improve their performance by extracting the hidden knowledge in business process datasets. In this paper, we present the application of DM to BPR, based on two novel approaches. By a literature review, the first approach proposes DMbBPR model, mainly focuses on the applications of... 

This paper presents a new Compressive Sensing (CS) scheme for detecting network congested links. We focus on decreasing the required number of measurements to detect all congested links in the context of network tomography. We have expanded the LASSO objective function by adding a new term corresponding to the prior knowledge based on the relationship between the congested links and the corresponding link Betweenness Centrality (BC). The accuracy of the proposed model is verified by simulations on two real datasets. The results demonstrate that our model outperformed the state-of-the-art CS based method with significant improvements in terms of F-Score  

Demand response (DR) as a state-of-the-art program is accommodated in the energy efficiency contexts of the smart grid. Lack of the customer knowledge about how to respond to the time-differentiated tariffs and offered controlling signals is the major obstacle in the way of broad DR implementing. As a solution, an optimization method, namely load control (LC), is proposed to automatically control the on/off status of the responsive appliances in a smart home. This paper focuses on the direct load control (DLC) program in the category of incentive-based DR programs. LC is extended to consider inconvenience cost of the DLC implementation for DLC program participants. Outputs of the extended LC... 

In this study, the average throughput maximisation of a secondary user (SU) by optimising its spectrum sensing time is formulated, assuming that a priori knowledge of the presence and absence probabilities of the primary users (PUs) is available. The energy consumed to find a transmission opportunity is evaluated, and a discussion on the impacts of the number of PUs on SU throughput and consumed energy are presented. To avoid the challenges associated with the analytical method, as a second solution, a systematic adaptive neural network-based sensing time optimisation approach is also proposed. The proposed scheme is able to find the optimum value of the channel sensing time without any... 

Partially-observed network data collected by link-tracing based sampling methods is often being studied to obtain the characteristics of a large complex network. However, little attention has been paid to sampling from directed networks such as WWW and Peer-to-Peer networks. In this paper, we propose a novel two-step (sampling/estimation) framework to measure nodal characteristics which can be defined by an average target function in an arbitrary directed network. To this end, we propose a personalized PageRank-based algorithm to visit and sample nodes. This algorithm only uses already visited nodes as local information without any prior knowledge about the latent structure of the network.... 

Creativity is a promoting factor in organizations. Having employees in structured and organized configurations in a creative manner, helps in improving the productivity. We investigate different structural aspects of teams' network organization and the creativity within a knowledge development program (KDP). The proposed methodology being equipped with a heuristic clustering technique, classifies the employees with respect to creativity parameters and configures a creativity matrix. Applying the creativity matrix, clustering is performed via mathematical programming. For large problems, a genetic algorithm (GA) is developed to solve the mathematical model. We also employ the Taguchi method... 

In pseudonym systems, users by means of pseudonyms anonymously interact with organizations to obtain credentials. The credential scheme constructed by Lysyanskaya and Camenisch is among the most complete credential systems, in which "all-or-nothing" sharing scheme is used to prevent users sharing their credentials. If a user cannot directly show a credential issued by an organization, she or he has to give her or his own secret key to someone else as a proxy; afterward, the proxy can show the credential on behalf of the user. Thus, according to the all-or-nothing property of the system, having the user's secret key, the proxy can use all credentials of the user for itself. To solve this... 

Strong designated verifier signature (SDVS) is characterized by two properties; namely the nontransferability and the privacy of the signer's identity (PSI). Non-transferability prevents anyone else other than the designated verifier to verify the signature, while PSI prevents a third party to distinguish between two different signers. In this paper, we propose a non-delegatable SDVS which uses a trusted third party for the key generation. Our signature scheme does not use bilinear pairings which makes it suitable for the resource constraint applications. Using one-way homomorphic functions, our scheme is presented at an abstract level, the unification of which was noticed by Maurer in the... 

Context-awareness is an essential requirement of modern access control models. Organization-Based Access Control (OrBAC) model is a powerful context-aware access control model defined by first-order logic. However, due to the monotonicity nature of the first-order logic, OrBAC suffers from the incapability of making decision based on incomplete context information as well as the definition of default and exception policy rules. This paper proposes augmenting non-monotonicity features to OrBAC using MKNF+ logic, which is a combination of Description Logic (DL) and Answer Set Programming (ASP). Along with the use of DL to define ontology for main entities and context information in OrBAC;... 

The objective of this work is to create an analytical framework to study the non-linear dynamics of beam flexures with a tip mass undergoing large deflections. Hamilton's principal is utilized to derive the equations governing the nonlinear vibrations of the cantilever beam and the associated boundary conditions. Then, using a single mode approximation, these non-linear partial differential equations are reduced to two coupled non-linear ordinary differential equations. These equations are solved analytically using combination of the method of multiple time scales and homotopy perturbation analysis. Closed-form, parametric analytical expressions are presented for the time domain response of...