Sharif Digital Repository

In this paper we propose a content-based text and image retrieval architecture using Fuzzy Adaptive Resonance Theory neural network. This method is equipped with an unsupervised mechanism for dynamic data clustering to deal with incremental information without metadata such as in web environment. Results show noticeable average precision and recall over search results. © 2006 IEEE  

Recently, the tradeoff between energy consumption and fault-tolerance in real-time systems has been highlighted. These works have focused on dynamic voltage scaling (DVS) to reduce dynamic energy dissipation and on-time redundancy to achieve transient-fault tolerance. While the time redundancy technique exploits the available slack-time to increase the fault-tolerance by performing recovery executions, DVS exploits slack-time to save energy. Therefore, we believe there is a resource conflict between the time-redundancy technique and DVS. The first aim of this paper is to propose the use of information redundancy to solve this problem. We demonstrate through analytical and experimental... 

Temporal relation classification is one of the contemporary demanding tasks in natural language processing. This task can be used in various applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved algorithm for classifying temporal relations between events and times, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting useful syntactic features, which are automatically generated, to improve accuracy of the classification. Accordingly, a number of novel kernel functions are introduced and evaluated for temporal relation classification. The result... 

In this study, an inventory system consisting of a single product, one supplier, and multiple identical retailers is considered. Each retailer replenishes inventory from the supplier according to the well known (R,Q) policy. Transit times are constant and retailers face independent Poisson demand. The supplier utilizing the retailers' information in decision making for replenishment policy with a given order size starts with m initial batches (of size Q) and places an order in a batch of size Q to an outside source when a new order is placed. In this inventory system, excess demand is backordered, delayed orders are satisfied on a first-come first-serve basis, and no partial shipment is... 

In this paper the Multiple Relay Channels (MRC) with delays, with and without channel state information (CSI) are investigated from an information theoretic point of view. For the MRC with unlimited look ahead where the relays can use the whole received block to encode, upper and lower bounds on the capacity are derived which are tight for the degraded case. For the MRC without-delay where the relays have access to the present received symbols in addition to the past symbols, the capacity of the degraded channel is established using Shannon's strategy for the channels with side information. Then we introduce the state dependent MRC with unlimited look ahead and derive a lower bound on the... 

The ability to accurately classify temporal relations between events is an important task in a large number of natural language processing and text mining applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved way of classifying temporal relations, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting useful syntactic features, which are automatically generated, to improve accuracy of the SVM classification method. Accordingly, a number of novel kernel functions are introduced and evaluated for temporal relation classification. Our evaluations... 

Users in social networks whose posts stay at the top of their followers' feeds the longest time are more likely to be noticed. Can we design an online algorithm to help them decide when to post to stay at the top? In this paper, we address this question as a novel optimal control problem for jump stochastic differential equations. For a wide variety of feed dynamics, we show that the optimal broadcasting intensity for any user is surprisingly simple - it is given by the position of her most recent post on each of her follower's feeds. As a consequence, we are able to develop a simple and highly efficient online algorithm, RedQueen, to sample the optimal times for the user to post.... 

Cyber-physical systems contain networked embedded systems. Such systems may implement cryptographic algorithms for processing and/or communication. Therefore, they can be prone to side-channel attacks. Differential power analysis is one of such attacks, which is considered among the most serious threats against cryptographic devices. Various metrics have been proposed to evaluate the resistance of different implementations against these attacks. Some of these metrics need side-channel attacks to be conducted and depend on the considered power model. Due to the vast variety of proposed side-channel attacks and power models, comprehensively evaluating a design under these metrics is commonly... 

In this paper, we argue that in many basic algorithms for machine learning, including support vector machine (SVM) for classification, principal component analysis (PCA) for dimensionality reduction, and regression for dependency estimation, we need the inner products of the data samples, rather than the data samples themselves.Motivated by the above observation, we introduce the problem of private inner product retrieval for distributed machine learning, where we have a system including a database of some files, duplicated across some non-colluding servers. A user intends to retrieve a subset of specific size of the set of the inner product of every pair of data items in the database with... 

E-business requires interoperability of information systems and, therefore, standardization of information sharing. Several XML-based e-business frameworks are developed to define standards for information sharing within and between companies. These frameworks only standardize structure of messages and aren't able to define semantics. The use of Semantic Web Service (SWS) technologies has been suggested to enable more dynamic B2B integration of heterogeneous systems and partners. We present a semantic B2B mediator based on the WSMX -a SWS execution environment, to tackle heterogeneities in RosettaNet messages. We develop a rich RosettaNet ontology and use the axiomatized knowledge and rules... 

The successful design and application of the ordered weighted averaging (OWA) method as a decision-making tool depend on the efficient computation of its order weights. The most popular methods for determining the order weights are the fuzzy linguistic quantifiers approach and the minimal variability method, which give different behavior patterns for the OWA. These two methods will be first analyzed in detail by using sensitivity analysis on the outputs of the OWA with respect to the optimism degree of the decision maker, and then the two methods will be compared. The fuzzy linguistic quantifiers approach gives more information about the behavior of the OWA outputs in comparison to the... 

Mandatory access control models have traditionally been employed as a robust security mechanism in multilevel security environments like military domains. In traditional mandatory models, the security classes associated with entities are context-insensitive. However, context-sensitivity of security classes may be required in some environments. Moreover, as computing technology becomes more pervasive, flexible access control mechanisms are needed. Unlike traditional approaches for access control, such access decisions depend on the combination of the required credentials of users and the context of the system. Incorporating context-awareness into mandatory access control models results in a... 

In this paper we propose a neuro-fuzzy architecture for Web content taxonomy using hybrid of Adaptive Resonance Theory (ART) neural networks and fuzzy logic concept. The search engine called Kavosh1 is equipped with unsupervised neural networks for dynamic data clustering. This model was designed for retrieving images without metadata and in estimating resemblance of multimedia documents; however, in this work only text mining method is implemented. Results show noticeable average precision and recall over search results. © 2007 IEEE  

Mining search engine query log is a new method for evaluating web site link structure and information architecture. In this paper we propose a new query-URL co-clustering for a web site useful to evaluate information architecture and link structure. Firstly, all queries and clicked URLs corresponding to particular web site are collected from a query log as bipartite graph, one side for queries and the other side for URLs. Then a new content free clustering is applied to cluster queries and URLs concurrently. Afterwards, based on information entropy, clusters of URLs and queries will be used for evaluating link structure and information architecture respectively. Data sets of different web... 

We consider a dyadic supply chain. Retailer applies (R,Q)-policy. Supplier starts with m initial batches of size Q and places an order of the same size to an outside source. The supplier can select one of the two following cases. Case 1, whenever the retailer places an order, the supplier will also place an order. Case 2, whenever the retailer's inventory position reaches R+s, the supplier will place an order. This paper derives the cost differential between these cases for any value of s, which enables the supply chain managers to decide whether to install an information sharing technology  

Adaptive scheduling schemes which consider channel conditions are examples of cross-layer design in wireless networks. Research work which has been done on optimizing the performance of scheduling systems have shown that in each time slot it is better to transmit to the users with the best channel condition. In order to realize such schemes, most of earlier works have considered perfect feedback channels to send Channel State Information (CSI) to the scheduler. However, in practical systems there are some sources of imperfectness in feedback channels such as delay and quantization error. In this paper, we consider the effect of CSI delay on the performance of such systems. A new delay-aware... 

The real-time availability of the Internet has engaged millions of users around the world. The usage of regional languages is being preferred for effective and ease of communication that is causing multilingual data on social networks and news channels. People share ideas, opinions, and events that are happening globally i.e., sports, inflation, protest, explosion, and sexual assault, etc. in regional (local) languages on social media. Extraction and classification of events from multilingual data have become bottlenecks because of resource lacking. In this research paper, we presented the event classification task for the Urdu language text existing on social media and the news channels by... 

The number of digital images uploaded in the virtual world is rapidly growing every day. Therefore, an automatic image annotation system that can retrieve information from these images seems to be in high demand. One of the challenges in this field is the imbalanced data sets and the difficulty of successfully learning tags from them. Even if a nearly balanced data set exists for image annotation, it is unlikely to find a single learner, which could learn all tags with the same accuracy. In this paper, we suggest a novel integration system that selects an elite group of models from all existing annotation models and then combines them to take the best advantage of each model’s learning...