Sharif Digital Repository

Clustering Web data is one important technique for extracting knowledge from the Web. In this paper, a novel method is presented to facilitate the clustering. The method determines the appropriate number of clusters and provides suitable representatives for each cluster by inference from a Bayesian network. Furthermore, by means of the Bayesian network, the contents of the Web pages are converted into vectors of lower dimensions. The method is also extended for hierarchical clustering, and a useful heuristic is developed to select a good hierarchy. The experimental results show that the clusters produced benefit from high quality  

A nano-based sensor array has been developed for identification and discrimination of catecholamine neurotransmitters based on optical properties of their oxidation products under alkaline conditions. To produce distinct fluorescence response patterns for individual catecholamine, quenching of thioglycolic acid functionalized cadmium telluride (CdTe) quantum dots, by oxidation products, were employed along with the variation of fluorescence spectra of oxidation products. The spectral changes were analyzed with hierarchical cluster analysis (HCA) and principal component analysis (PCA) to identify catecholamine patterns. The proposed sensor could efficiently discriminate the individual... 

Nanoparticles (NPs) are increasingly being used in different branches of science and in industrial applications; however, their rapid detection and characterization at low concentration levels have remained a challenge; more specifically, there is no single technique that can characterize the physicochemical properties of NPs (e.g. composition and size). In this work we have developed a colorimetric sensor array for defining the physicochemical properties of NPs in aqueous solution with ultra-low concentrations (e.g. 10-7g ml-1 for gold NPs). Various NPs were readily identified using a standard chemometric approach (i.e. hierarchical clustering analysis), with no misclassifications over 400... 

Developments of sensitive, rapid, and cheap systems for identification of a wide range of biomolecules have been recognized as a critical need in the biology field. Here, we introduce a simple colorimetric sensor array for detection of biological thiols, based on aggregation of three types of surface engineered gold nanoparticles (AuNPs). The low-molecular-weight biological thiols show high affinity to the surface of AuNPs; this causes replacement of AuNPs' shells with thiol containing target molecules leading to the aggregation of the AuNPs through intermolecular electrostatic interaction or hydrogen-bonding. As a result of the predetermined aggregation, color and UV-vis spectra of AuNPs... 

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... 

Supplier selection is a decision-making process to identify and evaluate suppliers for making contracts. Here, we use interval type-2 fuzzy values to show the decision makers' preferences and also introduce a new formula to compute the distance between two interval type-2 fuzzy sets. The performance of the proposed distance formula in comparison with the normalized Hamming, normalized Hamming based on the Hausdorff metric, normalized Euclidean and the signed distances is evaluated. The results show that the signed distance has the same trend as our method, but the other three methods are not appropriate for interval type-2 fuzzy sets. Using this approach, we propose a hierarchical... 

There is a growing interest in developing high-performance sensors monitoring organophosphate pesticides, primarily due to their broad usage and harmful effects on mammals. In the present study, a colorimetric sensor array consisting of citrate-capped 13 nm gold nanoparticles (AuNPs) has been proposed for the detection and discrimination of several organophosphate pesticides (OPs). The aggregation-induced spectral changes of AuNPs upon OP addition has been analyzed with pattern recognition techniques, including hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). In addition, the proposed sensor array has the capability to identify individual OPs or mixtures of them in... 

A nano-based sensor array has been developed for identification and discrimination of catecholamine neurotransmitters based on optical properties of their oxidation products under alkaline conditions. To produce distinct fluorescence response patterns for individual catecholamine, quenching of thioglycolic acid functionalized cadmium telluride (CdTe) quantum dots, by oxidation products, were employed along with the variation of fluorescence spectra of oxidation products. The spectral changes were analyzed with hierarchical cluster analysis (HCA) and principal component analysis (PCA) to identify catecholamine patterns. The proposed sensor could efficiently discriminate the individual... 

Fuzzy C-means clustering (FCM) is proposed as a promising method for the clustering of chromatographic fingerprints of complex samples, such as essential oils. As an example, secondary metabolites of 14 citrus leaves samples are extracted and analyzed by gas chromatography-mass spectrometry (GC-MS). The obtained chromatographic fingerprints are divided to desired number of chromatographic regions. Owing to the fact that chromatographic problems, such as elution time shift and peak overlap can significantly affect the clustering results, therefore, each chromatographic region is analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to address these problems. Then,... 

World Wide Web is a huge information space, making it a valuable resource for decision making. However, it should be effectively managed for such a purpose. One important management technique is clustering the web data. In this paper, we propose some developments in clustering methods to achieve higher qualities. At first we study a new density based method adapted for hierarchical clustering of web documents. Then utilizing the hyperlink structure of web, we propose a new method that incorporates density concepts with web graph. These algorithms have the preference of low complexity and as experimental results reveal, the resultant clusters have high quality. © 2009 Elsevier B.V. All rights... 

Sample preparation for non-target analysis is challenging due to the difficulty in the extraction of polar and non-polar analytes simultaneously. Most commercial solid sorbents lack the proper comprehensiveness for extraction of analytes with different physiochemical properties. A possible key is the combination of hydrophobic polymer and hydrophilic surface functional groups in solid based extraction methods in order to generate the susceptibility for retaining both polar and non-polar analytes. To pursue this goal, in this study, four polar groups including [sbnd]NH 2 , [sbnd]NO 2 , [sbnd]COOH, and [sbnd]COCH 3 were chemically bound to Amberlite XAD-4 substrate in order to prepare a... 

Development of a convenient and inexpensive method for identification and detection of nanoparticles (NPs) is of great interest. In this work, we have developed a novel and simple chemiluminescence based sensor array, with its sensing mechanism mimicking that of olfactory and gustatory systems for discriminating a set of NPs. The proposed method is based on the enhancement effect of NPs on luminol–oxidant CL intensity by their catalytic effect. Three kinds of oxidant including H2O2, AgNO3, and K3Fe(CN)6 were used as sensor elements and NPs exhibited diverse enhancing responses to different oxidant-luminol CL systems producing unique response patterns that were identified through heat map and... 

A gradient derived base layer extractive phase was synthesized and applied for the determination of volatile organic compounds (VOCs) in saliva samples using the headspace cooled in–tube microextraction (HS–CITME) method. The base layers from three different sols of phenyltriethoxysilane (PTES), octyltrimethoxysilane (OTMS) and methyltrimethoxysilane (MTMS) as nonpolar precursors were individually dip coated on the stainless steel wires (SSW). Then, the hydrolyzed polar precursor aminopropyltriethoxysilane (APTES) reacted with the silanol groups already formed on the surface of SSWs via controlled rate infusion (CRI) method. The presence of polar and non–polar functional groups on the... 

Herein, some (modified) paper–based substrates were prepared and utilized as extractive phases in a microfluidic device and their extraction performances examined for analytes with different polarities. Reagents including hexadecyltrimethoxysilane (HDTMS), phenyltrimethoxysilane (PTES), (3-aminopropyl) triethoxysilane (APTES) and 3–(2,3–epoxypropoxy) propyltrimethoxysilane (EPPTMOS) were implemented for the modification process. Due to the induction of different silane functional groups, it was anticipated to have various interactions for the tested analytes. Eventually, the prepared paper sheets were used as extractive phases for solid–phase extraction within a microfluidic system. The... 

This paper presents an online portfolio selection algorithm based on pattern matching principle where it makes a decision on the optimal portfolio in each period and updates the optimal portfolio at the beginning of each period. The proposed method consists of two steps: i) sample selection, ii) portfolio optimization. First, in the sample selection, clustering algorithms including k-means, k-medoids, spectral and hierarchical clustering are applied to discover time windows (TW) similar to the recent time window. Then, after finding the similar time windows and predicting the market behavior of the next day, the optimum function along with the transaction cost is used in the portfolio...