Sharif Digital Repository

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... 

A web attack is an attack against a web server through the HTTP Protocol. By analyzing known web attacks, we find out that each one has its own behavior. Vestiges of their behavior could be detected in non-body parts of the HTTP Protocol. Such information can be used to verify web alerts generated by Web Application Firewalls (WAFs) and Web Intrusion Detection Systems (Web IDSs). In this paper, we propose a method to verify web alerts generated by mentioned sensors. The goal of the alert verification component is to eliminate or tag alerts that do not represent successful attacks. Our approach is based on analyzing HTTP Transaction metadata, including Request method, Request Headers, Status... 

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... 

In this paper, we address the problem of data description using a Bayesian framework. The goal of data description is to draw a boundary around objects of a certain class of interest to discriminate that class from the rest of the feature space. Data description is also known as one-class learning and has a wide range of applications. The proposed approach uses a Bayesian framework to precisely compute the class boundary and therefore can utilize domain information in form of prior knowledge in the framework. It can also operate in the kernel space and therefore recognize arbitrary boundary shapes. Moreover, the proposed method can utilize unlabeled data in order to improve accuracy of... 

Asphaltene deposition in the early stage of the oil reservoir life and later during any stimulation process emerges critical problems to the petroleum industry. Deposition of asphaltene aggregates raises strict problems in industries and demands markedly a practical and scientific knowledge of the mechanisms of aggregation and precipitation. Fluorescence emission spectroscopy has been widely used to illuminate the fundamental properties of crude oils and asphaltenes. It proposes analysis of some details of equilibrium, dynamic behavior, and aggregation composition of crude oil under specific condition. In this work, the fluorescence spectra of crude-oil extracted asphaltene samples were... 

The objective of this work is to create an analytical framework to study the problem of squeezed film damping in micromirrors considering the bending of the supporting torsion microbeams. Using mathematical and physical justifications, nonlinear Reynolds equation governing the behavior of the squeezed gas underneath the mirror is linearized. The resulting linearized equation is then nondimensionalized and analytically solved for two cases of the infinitesimal and finite tilting angle of the mirror. The obtained pressure distribution from the solution of the Reynolds equation is then utilized for finding the squeezed film damping force and torque applied to the mirror. The results show that... 

Based on content externalism, the question of whether self-knowledge is authoritative or not has launched a real controversy in the philosophy of mind. Boghossian proposed slow switching argument in defense of incompatibility of the two views. This argument has been criticized by some philosophers through different approaches. Vahid is one of them. He claimed that Boghossian's argument appeals to some controversial assumptions without which it cannot achieve its conclusion. In this article, I criticize Vahid's response to slow switching argument and show that self-knowledge in Vahid's response differs in having authority and therefore in function from that of Boghossian  

Accurate forecasting of outpatient visits aids in decision-making and planning for the future and is the foundation for greater and better utilization of resources and increased levels of outpatient care. It provides the ability to better manage the ways in which outpatient's needs and aspirations are planned and delivered. This study presents a hybrid artificial intelligence (AI) model to develop a Mamdani type fuzzy rule based system to forecast outpatient visits with high accuracy. The hybrid model uses genetic algorithm for evolving knowledge base of fuzzy system. Actually it extracts useful patterns of information with a descriptive rule induction approach based on Genetic Fuzzy Systems...