Sharif Digital Repository

Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

A major challenge organizations face when hosting or moving their data to the Cloud is how to support complex queries over outsourced data while preserving their confidentiality. In principle, encryption-based systems can support querying encrypted data, but their high complexity has severely limited their practical use. In this paper, we propose an efficient yet secure secret sharing-based approach for outsourcing relational data to honest-but-curious data servers. The problem with using secret sharing in a data outsourcing scenario is how to efficiently search within randomly generated shares. We present multiple partitioning methods that enable clients to efficiently search among shared... 

With the growing presence of computers in everyday life, communication improvement between human and machines is inevitable. Talking faces are the faces whose movements are synchronized to speech. They have an effective role in many applications. Lip is the most important part of a talking face. The main goal of this project is implementing a natural and human-like lip movement synthesis system for the Farsi language. For this purpose, a comprehensive audio visual database called SFAVD1 was designed and used. After extracting the sufficient features and designing a parallel Hidden Markov Model, the speech driven lip movement sequence generator system for Farsi input speech was implemented.... 

Recently XML has become a standard for data representation and the preferred method of encoding structured data for exchange over the Internet. Moreover it is frequently used as a logical format to store structured and semi-structured data in databases. We propose a model-driven and configurable approach for modeling hierarchical XML data using object role modeling (ORM) as a flat conceptual model. First a non-hierarchical conceptual schema of the problem domain is built using ORM and then different hierarchical views of the conceptual schema or parts of it are specified by the designer using transformation rules. A hierarchical modeling notation called H-ORM is proposed to show these... 

Identifying and measuring the impact and value of scientific output plays an important role in today's world of information overload. On one side, governments are trying to distribute research funds in ways that support research in strategically important fields, on the other side, researchers and scientists are seeking to access only relevant and quality information that have mainly worthy of their attention. Nowadays, countries are evaluated not only by their national products, military power, geographical area, etc., but also by such factors as the production and consumption of scientific information. Scientometric approaches are used to provide appropriate tools for evaluating scientific... 

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... 

In this study, we are proposing a novel nonlinear classification approach to discriminate between Alzheimer's Disease (AD) and a control group using T1-weighted and T2-weighted Magnetic Resonance Images (MRI's) of brain. Since T1-weighted images and T2-weighted images have inherent physical differences, obviously each of them has its own particular medical data and hence, we extracted some specific features from each. Then the variations of the relevant eigenvalues of the extracted features were tracked to pick up the most informative ones. The final features were assigned to two parallel systems to be nonlinearly categorized. Considering the fact that AD defects the white and gray regions... 

Supply Chain Operations Reference (SCOR) model is developed and maintained by the Supply Chain Council (SCC). The model is a reference model which can be used to map, benchmark and improve the supply chain operations. SCOR model provides companies with a basic process modeling tool, an extensive benchmark database and defines a set of supply chain metrics. Mobarakeh Steel Company (located in Isfahan, Iran) initiated the project of studying and analyzing its supply chain performance based on the SCOR model. This paper explains the steps and the results of the project. Interviews with the managers and considering the documents on the four major subjects of planning, logistics, information flow... 

Nowadays, due to the growing role that analytical, predictive and decision making activities perform in organizations, organizational data are very important. In order to utilizing organizational data, it should be transmitted from the operational and transactional environment to a dimensional or normal database. However, not only differences in platforms and data types are some issues that should be overcome, but also variety of data types such as non-structural and text format files should be considered. In this way, exploiting updated data storages is necessary for quick and accurate services and raising customers' satisfaction. Although real time data storages are frequently used in... 

There is a growing attention in subspace learning using tensor-based approaches in high dimensional spaces. In this paper we first indicate that these methods suffer from the Heteroscedastic problem and then propose a new approach called Heteroscedastic Multilinear Discriminant Analysis (HMDA). Our method can solve this problem by utilizing the pairwise chernoff distance between every pair of clusters with the same index in different classes. We also show that our method is a general form of Multilinear Discriminant Analysis (MDA) approach. Experimental results on CMU-PIE, AR and AT&T face databases demonstrate that the proposed method always perform better than MDA in term of classification... 

Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and domain of images are unknown, unsupervised methods provide better solutions. In this work, we use a hierarchical clustering scheme to group images in an unknown and large image database. In addition, the user should provide the current class assignment of a small number of images as a feedback to the system. The proposed method uses this feedback to guess the number of required clusters, and optimizes the weight vector in an iterative manner. In each step, after modification of the weight vector, the images are reclustered. We... 

Clustering is one of the most useful methods of data mining, in which a set of real or abstract objects are categorized into clusters. The DBSCAN clustering method, one of the most famous density based clustering methods, categorizes points in dense areas into same clusters. In DBSCAN a point is said to be dense if the ε-radius circular area around it contains at least MinPts points. To find such dense areas, region queries are fired. Two points are defined as density connected if the distance between them is less than ε and at least one of them is dense. Finally, density connected parts of the data set extracted as clusters. The significant issue of such a method is that its parameters (ε...