Tagging by Combining Rules- Based Method and Memory-Based Learning

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Markov Chain Monte Carlo Model Composition Search Strategy for Quantitative Trait Loci in a Bayesian Hierarchical Model

Quantitative trait loci (QTL) experiments have yielded important biological and biochemical information necessary for understanding the relationship between genetic markers and quantitative traits. For many years, most QTL algorithms only allowed one observation per genotype. Recently, there has been an increasing demand for QTL algorithms that can accommodate more than one observation per genotypic distribution. The Bayesian hierarchical model is very flexible and can easily incorporate this information into the model. Herein a methodology is presented that uses a Bayesian hierarchical model to capture the complexity of the data. Furthermore, the Markov chain Monte Carlo model composition (MC3) algorithm is used to search and identify important markers. An extensive simulation study illustrates that the method captures the true QTL, even under nonnormal noise and up to 6 QTL.

Enhanced Coagulation of Disinfection By-Products Precursors in Porsuk Water Resource, Eskisehir

Natural organic matter (NOM) is heterogeneous mixture of organic compounds that enter the water media from animal and plant remains, domestic and industrial wastes. Researches showed that NOM is likely precursor material for disinfection by products (DBPs). Chlorine very commenly used for disinfection purposes and NOM and chlorine reacts then Trihalomethane (THM) and Haloacetic acids (HAAs) which are cancerogenics for human health are produced. The aim of the study is to search NOM removal by enhanced coagulation from drinking water source of Eskisehir which is supplied from Porsuk Dam. Recently, Porsuk dam water is getting highly polluted and therefore NOM concentration is increasing. Enhanced coagulation studies were evaluated by measurement of Dissolved Organic Carbon (DOC), UV absorbance at 254 nm (UV254), and different trihalomethane formation potential (THMFP) tests. Results of jar test experiments showed that NOM can be removed from water about 40-50 % of efficiency by enhanced coagulation. Optimum coagulant type and coagulant dosages were determined using FeCl3 and Alum.

Bioleaching of Spent Catalyst using Moderate Thermophiles with Different Pulp Densities and Varying Size Fractions without Fe Supplemented Growth Medium

Bioleaching of spent catalyst using moderate thermophilic chemolithotrophic acidophiles in growth medium without Fe source was investigated with two different pulp densities and three different size fractions. All the experiments were conducted on shake flasks at a temperature of 65 °C. The leaching yield of Ni and Al was found to be promising with very high leaching yield of 92-96% followed by Al as 41-76%, which means both Ni and Al leaching were favored by the moderate thermophilic bioleaching compared to the mesophilic bioleaching. The acid consumption was comparatively higher for the 10% pulp density experiments. Comparatively minimal difference in the leaching yield with different size fractions and different pulp densities show no requirement of grinding and using low pulp density less than 10%. This process would rather be economical as well as eco-friendly process for future optimization of the recovery of metal values from spent catalyst.

DCBOR: A Density Clustering Based on Outlier Removal

Data clustering is an important data exploration technique with many applications in data mining. We present an enhanced version of the well known single link clustering algorithm. We will refer to this algorithm as DCBOR. The proposed algorithm alleviates the chain effect by removing the outliers from the given dataset. So this algorithm provides outlier detection and data clustering simultaneously. This algorithm does not need to update the distance matrix, since the algorithm depends on merging the most k-nearest objects in one step and the cluster continues grow as long as possible under specified condition. So the algorithm consists of two phases; at the first phase, it removes the outliers from the input dataset. At the second phase, it performs the clustering process. This algorithm discovers clusters of different shapes, sizes, densities and requires only one input parameter; this parameter represents a threshold for outlier points. The value of the input parameter is ranging from 0 to 1. The algorithm supports the user in determining an appropriate value for it. We have tested this algorithm on different datasets contain outlier and connecting clusters by chain of density points, and the algorithm discovers the correct clusters. The results of our experiments demonstrate the effectiveness and the efficiency of DCBOR.

Adsorption of Crystal Violet onto BTEA- and CTMA-bentonite from Aqueous Solutions

CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.

Study on Specific Energy in Grinding of DRACs: A Response Surface Methodology Approach

In this study, the effects of machining parameters on specific energy during surface grinding of 6061Al-SiC35P composites are investigated. Vol% of SiC, feed and depth of cut were chosen as process variables. The power needed for the calculation of the specific energy is measured from the two watt meter method. Experiments are conducted using standard RSM design called Central composite design (CCD). A second order response surface model was developed for specific energy. The results identify the significant influence factors to minimize the specific energy. The confirmation results demonstrate the practicability and effectiveness of the proposed approach.

Surfactant Stabilized Nanoemulsion: Characterization and Application in Enhanced Oil Recovery

Nanoemulsions are a class of emulsions with a droplet size in the range of 50–500 nm and have attracted a great deal of attention in recent years because it is unique characteristics. The physicochemical properties of nanoemulsion suggests that it can be successfully used to recover the residual oil which is trapped in the fine pore of reservoir rock by capillary forces after primary and secondary recovery. Oil-in-water nanoemulsion which can be formed by high-energy emulsification techniques using specific surfactants can reduce oil-water interfacial tension (IFT) by 3-4 orders of magnitude. The present work is aimed on characterization of oil-inwater nanoemulsion in terms of its phase behavior, morphological studies; interfacial energy; ability to reduce the interfacial tension and understanding the mechanisms of mobilization and displacement of entrapped oil blobs by lowering interfacial tension both at the macroscopic and microscopic level. In order to investigate the efficiency of oil-water nanoemulsion in enhanced oil recovery (EOR), experiments were performed to characterize the emulsion in terms of their physicochemical properties and size distribution of the dispersed oil droplet in water phase. Synthetic mineral oil and a series of surfactants were used to prepare oil-in-water emulsions. Characterization of emulsion shows that it follows pseudo-plastic behaviour and drop size of dispersed oil phase follows lognormal distribution. Flooding experiments were also carried out in a sandpack system to evaluate the effectiveness of the nanoemulsion as displacing fluid for enhanced oil recovery. Substantial additional recoveries (more than 25% of original oil in place) over conventional water flooding were obtained in the present investigation.

Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform

A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.

A Comparative Study of Rigid and Modified Simplex Methods for Optimal Parameter Settings of ACO for Noisy Non-Linear Surfaces

There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.

Full Potential Study of Electronic and Optical Properties of NdF3

We report the electronic structure and optical properties of NdF3 compound. Our calculations are based on density functional theory (DFT) using the full potential linearized augmented plane wave (FPLAPW) method with the inclusion of spin orbit coupling. We employed the local spin density approximation (LSDA) and Coulomb-corrected local spin density approximation, known for treating the highly correlated 4f electrons properly, is able to reproduce the correct insulating ground state. We find that the standard LSDA approach is incapable of correctly describing the electronic properties of such materials since it positions the f-bands incorrectly resulting in an incorrect metallic ground state. On the other hand, LSDA + U approximation, known for treating the highly correlated 4f electrons properly, is able to reproduce the correct insulating ground state. Interestingly, however, we do not find any significant differences in the optical properties calculated using LSDA, and LSDA + U suggesting that the 4f electrons do not play a decisive role in the optical properties of these compounds. The reflectivity for NdF3 compound stays low till 7 eV which is consistent with their large energy gaps. The calculated energy gaps are in good agreement with experiments. Our calculated reflectivity compares well with the experimental data and the results are analyzed in the light of band to band transitions.

Regional Differences in the Effect of Immigration on Poverty Rates in Spain

This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.

CASTE: a Cloud-Based Automatic Software Test Environment

This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.

Pipelined Control-Path Effects on Area and Performance of a Wormhole-Switched Network-on-Chip

This paper presents design trade-off and performance impacts of the amount of pipeline phase of control path signals in a wormhole-switched network-on-chip (NoC). The numbers of the pipeline phase of the control path vary between two- and one-cycle pipeline phase. The control paths consist of the routing request paths for output selection and the arbitration paths for input selection. Data communications between on-chip routers are implemented synchronously and for quality of service, the inter-router data transports are controlled by using a link-level congestion control to avoid lose of data because of an overflow. The trade-off between the area (logic cell area) and the performance (bandwidth gain) of two proposed NoC router microarchitectures are presented in this paper. The performance evaluation is made by using a traffic scenario with different number of workloads under 2D mesh NoC topology using a static routing algorithm. By using a 130-nm CMOS standard-cell technology, our NoC routers can be clocked at 1 GHz, resulting in a high speed network link and high router bandwidth capacity of about 320 Gbit/s. Based on our experiments, the amount of control path pipeline stages gives more significant impact on the NoC performance than the impact on the logic area of the NoC router.

Plastic Flow through Taper Dies: A Threedimensional Analysis

The plastic flow of metal in the extrusion process is an important factor in controlling the mechanical properties of the extruded products. It is, however, difficult to predict the metal flow in three dimensional extrusions of sections due to the involvement of re-entrant corners. The present study is to find an upper bound solution for the extrusion of triangular sectioned through taper dies from round sectioned billet. A discontinuous kinematically admissible velocity field (KAVF) is proposed. From the proposed KAVF, the upper bound solution on non-dimensional extrusion pressure is determined with respect to the chosen process parameters. The theoretical results are compared with experimental results to check the validity of the proposed velocity field. An extrusion setup is designed and fabricated for the said purpose, and all extrusions are carried out using circular billets. Experiments are carried out with commercially available lead at room temperature.

Experimental and Statistical Study of Nonlinear Effect of Carbon Nanotube on Mechanical Properties of Polypropylene Composites

In this study concept of experimental design is successfully applied for the determination of optimum condition to produce PP/SWCNT (Polypropylene/Single wall carbon nanotube) nanocomposite. Central composite design as one of experimental design techniques is employed for the optimization and statistical determination of the significant factors influencing on the tensile modulus and yield stress as mechanical properties of this nanocomposite. The significant factors are SWCNT weight fraction and acid treatment time for functionalizing the nanoparticles. Optimum conditions are in 0.7 % of SWCNT weight fraction and 210 min as acid treatment time for 1112.75 ± 28 MPa as maximum tensile modulus and in 216 min and 0.65 % as acid treatment time and SWCNT weight fraction respectively for 40.26 ± 0.3 MPa as maximum yield stress. Also after setting new experiments for test these optimum conditions, found excelent agreement with predicted values.

Influence of Ambiguity Cluster on Quality Improvement in Image Compression

Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.

Life Time Based Analysis of MAC Protocols of Wireless Ad Hoc Networks in WSN Applications

Wireless Sensor Networks (WSN) are emerging because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure, motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the MAC protocols used in wireless Adhoc networks to WSN, simulation experiments were conducted in Global Mobile Simulator (GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.

Sulphur-Mediated Precipitation of Pt/Fe/Co/CrIons in Liquid-Liquid and Gas-Liquid Chloride Systems

The proof of concept experiments were conducted to determine the feasibility of using small amounts of Dissolved Sulphur (DS) from the gaseous phase to precipitate platinum ions in chloride media. Two sets of precipitation experiments were performed in which the source of sulphur atoms was either a thiosulphate solution (Na2S2O3) or a sulphur dioxide gas (SO2). In liquid-liquid (L-L) system, complete precipitation of Pt was achieved at small dosages of Na2S2O3 (0.01 – 1.0 M) in a time interval of 3-5 minutes. On the basis of this result, gas absorption tests were carried out mainly to achieve sulphur solubility equivalent to 0.018 M. The idea that huge amounts of precious metals could be recovered selectively from their dilute solutions by utilizing the waste SO2 streams at low pressure seemed attractive from the economic and environmental point of views. Therefore, mass transfer characteristics of SO2 gas associated with reactive absorption across the gas-liquid (G-L) interface were evaluated under different conditions of pressure (0.5 – 2 bar), solution temperature ranges from 20 – 50 oC and acid strength (1 – 4 M, HCl). This paper concludes with information about selective precipitation of Pt in the presence of cations (Fe2+, Co2+, and Cr3+) in a CSTR and recommendation to scale up laboratory data to industrial pilot scale operations.

Chelate Enhanced Modified Fenton Treatment for Polycyclic Aromatic Hydrocarbons Contaminated Soils

This work focuses on the remediation of polycyclic aromatic hydrocarbons (PAHs)-contaminated soil via Fenton treatment coupled with novel chelating agent (CA). The feasibility of chelated modified Fenton (MF) treatment to promote PAH oxidation in artificially contaminated soils was investigated in laboratory scale batch experiments at natural pH. The effects of adding inorganic and organic CA are discussed. Experiments using different iron catalyst to CA ratios were conducted, resulting in hydrogen peroxide: soil: iron: CA weight ratios that varied from 0.049: 1: 0.072: 0.008 to 0.049: 1: 0.072: 0.067. The results revealed that (1) inorganic CA could provide much higher PAH removal efficiency and (2) most of the proposed CAs were more efficient than commonly utilised CAs even at mild ratio. This work highlights the potential of novel chelating agents in maintaining a suitable environment throughout the Fenton treatment, particularly in soils with high buffer capacity.