Two-Phase Optimization for Selecting Materialized Views in a Data Warehouse

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.

The Influence of Heat Treatment on Antimicrobial Proteins in Milk

the obligatory step during immunoglobulin and lysozyme concentration process is thermal treatment. The combination of temperature and time used in processing can affect the structure of the proteins and involve unfolding and aggregation. The aim of the present study was to evaluate the heat stability of total Igs, the particular immunoglobulin classes and lysozyme in milk. Milk samples were obtained from conventional dairy herd in Latvia. Raw milk samples were pasteurized in different regimes: 63 °C 30 min, 72 °C 15-20 s, 78 °C 15-20 s, 85 °C 15-20 s, 95 °C 15-20 s. The concentrations of Igs (IgA, IgG, IgM) and lysozyme were determined by turbodimetric method. During research was established, that activity of antimicrobial proteins decreases differently. Less concentration reduce was established in a case of lysozyme.

Evaluation of Urban Development Proposals An ANP Approach

In this paper a new approach to prioritize urban planning projects in an efficient and reliable way is presented. It is based on environmental pressure indices and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity of rank ordering urban development proposals according to their environmental pressure. The technique combines the use of Environmental Pressure Indicators, the aggregation of indicators in an Environmental Pressure Index by means of the Analytic Network Process method and interpreting the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts- judgments on each of the indicators into one Environmental Pressure Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts- estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The method has been applied to the proposal for urban development of La Carlota airport in Caracas (Venezuela). The Venezuelan Government would like to see a recreational project develop on the abandoned area and mean a significant improvement for the capital. There are currently three options on their table which are currently under evaluation. They include a Health Club, a Residential area and a Theme Park. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional techniques such as environmental impact studies, lifecycle analysis, etc. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods.

Sensing Characteristics to Acid Vapors of a TPPS Coated Fiber Optic: A Preliminary Analysis

In this work we report on preliminary analysis of a novel optoelectronic gas sensor based on an optical fiber integrated with a tetrakis(4-sulfonatophenyl)porphyrin (TPPS) thin film. The sensitive materials are selectively deposited on the core region of a fiber tip by UV light induced deposition technique. A simple and cheap process which can be easily extended to different porphyrin derivatives. When the TPPS film on the fiber tip is exposed to acid and/or base vapors, dramatic changes occur in the aggregation structure of the dye molecules in the film, from J- to H-type, resulting in a profound modification of their corresponding reflectance spectra. From the achieved experimental results it is evident that the presence of intense and narrow band peaks in the reflected spectra could be monitored to detect hazardous vapors.

Construction Of Decentralized Lifetime Maximizing Tree for Data Aggregation in Wireless Sensor Networks

To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside any given event region. In this paper , a novel technique to create one such tree is proposed .This tree preserves the energy and maximizes the lifetime of event sources while they are constantly transmitting for data aggregation. The term Decentralized Lifetime Maximizing Tree (DLMT) is used to denote this tree. DLMT features in nodes with higher energy tend to be chosen as data aggregating parents so that the time to detect the first broken tree link can be extended and less energy is involved in tree maintenance. By constructing the tree in such a way, the protocol is able to reduce the frequency of tree reconstruction, minimize the amount of data loss ,minimize the delay during data collection and preserves the energy.

Review of Trust Models in Wireless Sensor Networks

The major challenge faced by wireless sensor networks is security. Because of dynamic and collaborative nature of sensor networks the connected sensor devices makes the network unusable. To solve this issue, a trust model is required to find malicious, selfish and compromised insiders by evaluating trust worthiness sensors from the network. It supports the decision making processes in wireless sensor networks such as pre key-distribution, cluster head selection, data aggregation, routing and self reconfiguration of sensor nodes. This paper discussed the kinds of trust model, trust metrics used to address attacks by monitoring certain behavior of network. It describes the major design issues and their countermeasures of building trust model. It also discusses existing trust models used in various decision making process of wireless sensor networks.

Thermodynamic Study for Aggregation Behavior of Hydrotropic Solution

Aggregation behavior of sodium salicylate and sodium cumene sulfonate was studied in aqueous solution at different temperature. Specific conductivity and relative viscosity were measured at different temperature to find minimum hydrotropic concentration. The thermodynamic parameters (free energy, enthalpy and entropy) were evaluated in the temperature range of 30°C-70°C. The free energy decreased with increase in temperature. The aggregation was found to be exothermic in nature and favored by positive value of entropy.

Reliable Capacitated Facility Location Problem Considering Maximal Covering

This paper provides a framework in order to incorporate reliability issue as a sign of disruption in distribution systems and partial covering theory as a response to limitation in coverage radios and economical preferences, simultaneously into the traditional literatures of capacitated facility location problems. As a result we develop a bi-objective model based on the discrete scenarios for expected cost minimization and demands coverage maximization through a three echelon supply chain network by facilitating multi-capacity levels for provider side layers and imposing gradual coverage function for distribution centers (DCs). Additionally, in spite of objectives aggregation for solving the model through LINGO software, a branch of LP-Metric method called Min- Max approach is proposed and different aspects of corresponds model will be explored.

Are PEG Molecules a Universal Protein Repellent?

Poly (ethylene glycol) (PEG) molecules attached to surfaces have shown high potential as a protein repellent due to their flexibility and highly water solubility. A quartz crystal microbalance recording frequency and dissipation changes (QCM-D) has been used to study the adsorption from aqueous solutions, of lysozyme and α-lactalbumin proteins (the last with and without calcium) onto modified stainless steel surfaces. Surfaces were coated with poly(ethylene imine) (PEI) and silicate before grafting on PEG molecules. Protein adsorption was also performed on the bare stainless steel surface as a control. All adsorptions were conducted at 23°C and pH 7.2. The results showed that the presence of PEG molecules significantly reduced the adsorption of lysozyme and α- lactalbumin (with calcium) onto the stainless steel surface. By contrast, and unexpected, PEG molecules enhanced the adsorption of α-lactalbumin (without calcium). It is suggested that the PEG -α- lactalbumin hydrophobic interaction plays a dominant role which leads to protein aggregation at the surface for this latter observation. The findings also lead to the general conclusion that PEG molecules are not a universal protein repellent. PEG-on-PEI surfaces were better at inhibiting the adsorption of lysozyme and α-lactalbumin (with calcium) than with PEG-on-silicate surfaces.

Fe3O4 and Fe3O4@Au Nanoparticles: Synthesis and Functionalisation for Biomolecular Attachment

The use of magnetic and magnetic/gold core/shell nanoparticles in biotechnology or medicine has shown good promise due to their hybrid nature which possesses superior magnetic and optical properties. Some of these potential applications include hyperthermia treatment, bio-separations, diagnostics, drug delivery and toxin removal. Synthesis refinement to control geometric and magnetic/optical properties, and finding functional surfactants for biomolecular attachment, are requirements to meet application specifics. Various high-temperature preparative methods were used for the synthesis of iron oxide and gold-coated iron oxide nanoparticles. Different surface functionalities, such as 11-aminoundecanoic and 11-mercaptoundecanoic acid, were introduced on the surface of the particles to facilitate further attachment of biomolecular functionality and drug-like molecules. Nanoparticle thermal stability, composition, state of aggregation, size and morphology were investigated and the results from techniques such as Fourier Transform-Infra Red spectroscopy (FT-IR), Ultraviolet visible spectroscopy (UV-vis), Transmission Electron Microscopy (TEM) and thermal analysis are discussed.

Photocatalytic and Sonophotocatalytic Degradation of Reactive Red 120 using Dye Sensitized TiO2 under Visible Light

The accelerated sonophotocatalytic degradation of Reactive Red (RR) 120 dye under visible light using dye sensitized TiO2 activated by ultrasound has been carried out. The effect of sonolysis, photocatalysis and sonophotocatalysis under visible light has been examined to study the influence on the degradation rates by varying the initial substrate concentration, pH and catalyst loading to ascertain the synergistic effect on the degradation techniques. Ultrasonic activation contributes degradation through cavitation leading to the splitting of H2O2 produced by both photocatalysis and sonolysis. This results in the formation of oxidative species, such as singlet oxygen (1O2) and superoxide (O2 -●) radicals in the presence of oxygen. The increase in the amount of reactive radical species which induce faster oxidation of the substrate and degradation of intermediates and also the deaggregation of the photocatalyst are responsible for the synergy observed under sonication. A comparative study of photocatalysis and sonophotocatalysis using TiO2, Hombikat UV 100 and ZnO was also carried out.

The Study of the Interaction between Catanionic Surface Micelle SDS-CTAB and Insulin at Air/Water Interface

Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Change Detector Combination in Remotely Sensed Images Using Fuzzy Integral

Decision fusion is one of hot research topics in classification area, which aims to achieve the best possible performance for the task at hand. In this paper, we investigate the usefulness of this concept to improve change detection accuracy in remote sensing. Thereby, outputs of two fuzzy change detectors based respectively on simultaneous and comparative analysis of multitemporal data are fused by using fuzzy integral operators. This method fuses the objective evidences produced by the change detectors with respect to fuzzy measures that express the difference of performance between them. The proposed fusion framework is evaluated in comparison with some ordinary fuzzy aggregation operators. Experiments carried out on two SPOT images showed that the fuzzy integral was the best performing. It improves the change detection accuracy while attempting to equalize the accuracy rate in both change and no change classes.

Blood Cell Dynamics in a Simple Shear Flow using an Implicit Fluid-Structure Interaction Method Based on the ALE Approach

A numerical method is developed for simulating the motion of particles with arbitrary shapes in an effectively infinite or bounded viscous flow. The particle translational and angular motions are numerically investigated using a fluid-structure interaction (FSI) method based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (smoothing and remeshing) in FLUENT ( ANSYS Inc., USA). Also, the effects of arbitrary shapes on the dynamics are studied using the FSI method which could be applied to the motions and deformations of a single blood cell and multiple blood cells, and the primary thrombogenesis caused by platelet aggregation. It is expected that, combined with a sophisticated large-scale computational technique, the simulation method will be useful for understanding the overall properties of blood flow from blood cellular level (microscopic) to the resulting rheological properties of blood as a mass (macroscopic).

Performance Assessment of Computational Gridon Weather Indices from HOAPS Data

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Simulated Annealing Algorithm for Data Aggregation Trees in Wireless Sensor Networks and Comparison with Genetic Algorithm

In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.

Evaluation of the Immunoregulatory Activity of rFip-gts Purified from Baculovirus-infected Insect Cells

Fip-gts, an immunomodulatory protein purified from Ganoderma tsugae, has been reported to possess therapeutic effects in the treatment of cancer and autoimmune disease. For medicinal application, a recombinant Fip-gts was successfully expressed and purified in Sf21 insect cells by our previously work. It is important to evaluate the immunomodulatory activity of the rFip-gts. To assess the immunomodulatory potential of rFip-gts, the T lymphocytes of murine splenocytes were used in the present study. Results revealed that rFip-gts induced cellular aggregation formation. Additionally, the expression of IL-2 and IFN-r were up-regulated after the treatment of rFip-gts, and a corresponding increased production of IL-2 and IFN-r in a dose-dependent manner. The results showed that rFip-gts has an immunomodulatory activity in inducing Th1 lymphocytes from murine splenocytes released IL-2 and IFN-γ, thus suggest that rFip-gts may have therapeutic potential in vivo as an immune modulator.

On Combining Support Vector Machines and Fuzzy K-Means in Vision-based Precision Agriculture

One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

A Fuzzy Approach for Delay Proportion Differentiated Service

There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.

Energy Efficient In-Network Data Processing in Sensor Networks

The Sensor Network consists of densely deployed sensor nodes. Energy optimization is one of the most important aspects of sensor application design. Data acquisition and aggregation techniques for processing data in-network should be energy efficient. Due to the cross-layer design, resource-limited and noisy nature of Wireless Sensor Networks(WSNs), it is challenging to study the performance of these systems in a realistic setting. In this paper, we propose optimizing queries by aggregation of data and data redundancy to reduce energy consumption without requiring all sensed data and directed diffusion communication paradigm to achieve power savings, robust communication and processing data in-network. To estimate the per-node power consumption POWERTossim mica2 energy model is used, which provides scalable and accurate results. The performance analysis shows that the proposed methods overcomes the existing methods in the aspects of energy consumption in wireless sensor networks.