A novel approach to design optimal 2-D digital differentiator using vortex search optimization algorithm

Multimedia Tools and Applications - The designing of 2-D digital differentiator is multimodal and high dimensional problem which requires large number of differentiator coefficients to be...     

Security Functional Components for Building a Secure Network Computing Environment

ABSTRACT

It is difficult to define reliable security policy components that should be applied to validate a secure computing environment. The job gets further complicated when one has to deal with multiple policies in single computing environment. This paper demonstrates how we can overcome the difficulties of defining reliable security components by using evaluation criteria. In this paper we use common criteria to derive the security functional components for a multipolicy-based network computing environment. In the verification process, the derived policy components are related to the specific security objectives of the network communication environment. The evidence listed in the case study supports the claims that the proposed network security policy interpretation framework is a complete and cohesive set of requirements.     

Non-negative matrix factorization for semi-supervised data clustering

Traditional clustering algorithms are inapplicable to many real-world problems where limited knowledge from domain experts is available. Incorporating the domain knowledge can guide a clustering algorithm, consequently improving the quality of clustering. In this paper, we propose SS-NMF: a semi-supervised non-negative matrix factorization framework for data clustering. In SS-NMF, users are able to provide supervision for clustering in terms of pairwise constraints on a few data objects specifying whether they “must” or “cannot” be clustered together. Through an iterative algorithm, we perform symmetric tri-factorization of the data similarity matrix to infer the clusters. Theoretically, we show the correctness and convergence of SS-NMF. Moveover, we show that SS-NMF provides a general framework for semi-supervised clustering. Existing approaches can be considered as special cases of it. Through extensive experiments conducted on publicly available datasets, we demonstrate the superior performance of SS-NMF for clustering.

A two-phase framework for quality-aware Web service selection

Service-oriented computing is gaining momentum as the next technological tool to leverage the huge investments in Web application development. The expected large number of Web services poses a set of new challenges for efficiently accessing these services. We propose an integrated service query framework that facilitates users in accessing their desired services. The framework incorporates a service query model and a two-phase optimization strategy. The query model defines service communities that are used to organize the large and heterogeneous service space. The service communities allow users to use declarative queries to retrieve their desired services without worrying about the underlying technical details. The two-phase optimization strategy automatically generates feasible service execution plans and selects the plan with the best user-desired quality. In particular, we present an evolutionary algorithm that is able to “co-evolve” multiple feasible execution plans simultaneously and allows them to compete with each other to generate the best plan. We conduct a set of experiments to assess the performance of the proposed algorithms.     

Bipartite isoperimetric graph partitioning for data co-clustering

Data co-clustering refers to the problem of simultaneous clustering of two data types. Typically, the data is stored in a contingency or co-occurrence matrix C where rows and columns of the matrix represent the data types to be co-clustered. An entry C _ij of the matrix signifies the relation between the data type represented by row i and column j. Co-clustering is the problem of deriving sub-matrices from the larger data matrix by simultaneously clustering rows and columns of the data matrix. In this paper, we present a novel graph theoretic approach to data co-clustering. The two data types are modeled as the two sets of vertices of a weighted bipartite graph. We then propose Isoperimetric Co-clustering Algorithm (ICA)—a new method for partitioning the bipartite graph. ICA requires a simple solution to a sparse system of linear equations instead of the eigenvalue or SVD problem in the popular spectral co-clustering approach. Our theoretical analysis and extensive experiments performed on publicly available datasets demonstrate the advantages of ICA over other approaches in terms of the quality, efficiency and stability in partitioning the bipartite graph.     

Cuckoo Search Based Optimization of Multiuser Cognitive Radio System Under the Effect of Shadowing

Shadow fading is one of the least investigated factors of received signal power in a typical wireless communication system. Variations in the received power caused by shadowing events can impose some serious changes in the communication. This paper, proposes a new multiuser cognitive radio system in shadowing environment and its design optimization using cuckoo search algorithm. The transmission parameters of multiple secondary users in the purposed CR model are considered on the basis of IEEE 802.22 WRAN standard. An attempt to optimize these parameters in shadowing environment to achieve multiple objectives for desired quality of service have been made using a relatively newer and simpler cuckoo search algorithm. The optimization results have been compared with another efficient biogeography based optimization technique and the traditional simulated annealing.     

Synthesis,characterization, and rheological studies of methacrylic acid–ethyl acrylate–diallyl phthalate copolymers

Copolymerization of methacrylic acid (MAA) and ethyl acrylate (EA) was performed by the emulsion polymerization technique in the presence of a mixture of ionic and nonionic emulsifiers, at 85°C, using potassium persulfate as initiator (0.16 wt % of monomer). The molar ratio of MAA : EA varied between 44 : 56 and 54 : 46 in the monomer feed. Copolymers of MAA and EA were synthesized by incorporating diallyl phthalate (DAP) with varying concentrations (0–1.7 mol % of total monomer) in the feed. A copolymer latex of MAA, EA, and DAP was also prepared by the variable feed process. The intrinsic viscosity and gel content were determined. Copolymers were characterized by IR and NMR spectroscopic techniques. The composition of copolymers was determined by ¹H‐NMR spectra and sequential distribution from ¹³C{¹H}‐NMR spectra. The pH of the copolymer emulsion varied between 3 and 10 by addition of aqueous ammonia (23% w/w) and its effect on Brookfield viscosity was studied. The effects of copolymer composition, crosslinking agent concentration in the feed, monomer feed process, polymer solid contents, and shear rate on Brookfield viscosity were studied at pH ～ 8. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 1430–1441, 2003     

Thermal properties of cowpea flour: a study by differential scanning calorimetry

The thermal properties of 12 varieties of cowpea flour were studied by differential scanning calorimetry (DSC). Flour samples were prepared to a paste of 60% moisture content and sealed in standard DSC pans. Samples were scanned at a heating rate of 5 degrees C/min over a scan range of 40- 130 degrees C. Samples exhibited single major endotherms, which occurred over varied temperatures. The transition enthalpy (deltaH) ranged between 1.4 J/g and 4.7 J/g. Transition onset (T(o)) and transition peak (T(p)) temperatures ranged between 75-78 degrees C and 78-82 degrees C,respectively. All the DSC parameters measured varied significantly among the varieties. The transition enthalpy (deltaH) was the most discriminating parameter and accounted for 80% of the total variance. The major chemical components of cowpea flour, starch amylose and protein are significant predictors of deltaH. Protein denaturation appears to be a significant modification which occurs during processing of cowpea seeds to flour. The transition enthalpy deltaH could become an important functional index of cowpea flour when related to some quality parameters in products that contain the flour.     

Core content and stability of n‐octadecane‐containing polyurea microencapsules produced by interfacial polymerization

Microencapsulation of phase change material (PCM) n‐octadecane was carried out by interfacial polymerization technique using core and bulk monomers as toluene‐2,4‐diisocyanate (TDI) and diethylene triamine (DETA), respectively. Cyclohexane was used as the solvent for TDI and n‐octadecane, which formed the oil phase. The effect of encapsulation procedure, core‐to‐monomer ratio (CM ratio) and PCM‐to‐cyclohexane (PC) ratio was investigated on core content, encapsulation efficiency, and stability of microcapsules. Using a modified procedure, the core content was found to increase with the increasing CM ratio and reached a maximum at 3.7, while the encapsulation efficiency continuously decreased with the increasing CM ratio. Also the encapsulation efficiency was found to have a strong dependence on PC ratio and a maximum encapsulation efficiency of 92%, along with the core content of 70% was obtained with CM ratio of 3.7 along with the PC ratio of 6. The microcapsules were well shaped, i.e., round and regular, with narrow size distribution at these conditions. The PCM microcapsules were found to be stable to heat treatment at 150°C for 8 h. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Properties of a thermal-processed beverage prepared from roasted partially defatted peanuts

The effects of two thermal processing methods on physical and sensory properties of a beverage prepared from finely ground, partially defatted roasted peanuts ( Arachis hypogaea ) were determined. Samples were either bottle-processed at 72 °C for 2 min or 111 °C for 8 min after homogenizing at 72 °C, or kettle-pasteurized for 2 min at 72, 77 or 82 °C before homogenizing at 72, 77 or 82 °C, respectively. Harsher thermal processing parameters increased the suspension stability and viscosity of bottle-processed beverage by 175 and 87%, respectively, but had no influence on kettle-pasteurized beverage. Total solids (%) and colour were not adversely affected by thermal processing. Beverage which was kettle-pasteurized and homogenized at 72 °C had low viscosity (6.1–8.4 cps), typical roasted peanut flavour and little or no chalky mouthfeel, irrespective of whether carrageenan (stabilizer) or mono-diglyceride (emulsifier) were added to the formulation. Kettle-pasteurizing before homogenizing (20.7 × 10⁶ Pa) showed potential for producing beverages with physical and sensory attributes similar to commercial cow milk products.