Multiple responses analysis and modeling of Fenton process for treatment of high strength landfill leachate

Landfill leachate is one of the most recalcitrant wastes for biotreatment and can be considered a potential source of contamination to surface and groundwater ecosystems. In the present study, Fenton oxidation was employed for degradation of stabilized landfill leachate. Response surface methodology was applied to analyze, model and optimize the process parameters, i.e. pH and reaction time as well as the initial concentrations of hydrogen peroxide and ferrous ion. Analysis of variance showed that good coefficients of determination were obtained (R2 > 0.99), thus ensuring satisfactory agreement of the second-order regression model with the experimental data. The results indicated that, pH and its quadratic effects were the main factors influencing Fenton oxidation. Furthermore, antagonistic effects between pH and other variables were observed. The optimum H2O2 concentration, Fe(II) concentration, pH and reaction time were 0.033 mol/L, 0.011 mol/L, 3 and 145 min, respectively, with 58.3% COD, 79.0% color and 82.1% iron removals.     

A multi-objective strategy in genetic algorithms for gene selection of gene expression data

A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach that used a single-objective strategy in a genetic algorithm. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Selecting informative genes from microarray data by using hybrid methods for cancer classification

Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

IP address allocation protocols in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), communication takes place between vehicles to vehicles, the vehicles to the road side units, and vice-versa. The basic purpose of these communications is to share and exchange tremendous amount of data and information. For efficient information sharing, a systematic and structured connection establishment algorithm is needed. In VANETs, each connected node of the network need to be assigned a unique address. Hence, an algorithm is needed for the proper assignment of unique address to all nodes in the network. This paper explains different types of IP address protocols in VANETs. We have also explained advantage and disadvantage of existing IP address allocation protocols in VANETs.     

An Efficient Schema Transformation Technique for Data Migration from Relational to Column-Oriented Databases

Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However, there is no standard guideline for data transformation from relational database to NoSQL database. A number of schema transformation techniques have been proposed to improve data transformation process and resulted better query processing time when compared to the relational database query processing time. However, these approaches produced redundant tables in the resulted schema that in turn consume large unnecessary storage size and produce high query processing time due to the generated schema with redundant column families in the transformed column-oriented database. In this paper, an efficient data transformation technique from relational database to column-oriented database is proposed. The proposed schema transformation technique is based on the combination of denormalization approach, data access pattern and multiple-nested schema. In order to validate the proposed work, the proposed technique is implemented by transforming data from MySQL database to HBase database. A benchmark transformation technique is also performed in which the query processing time and the storage size are compared. Based on the experimental results, the proposed transformation technique showed significant improvement in terms query processing time and storage space usage due to the reduced number of column families in the column-oriented database.     

Phase Distribution and Magnetic Properties of Mechanically Alloyed Hard/Soft Ferrite Nanocomposites

Improvement in the magnetic properties of hard/ soft ferrite nanocomposites was studied by varying the composition of the soft phase in SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites. The SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites were prepared using the mechanical alloying method. The samples were prepared by varying the amount of the soft phase from 10 to 50 wt% while the amount of the hard phase remained 100 wt% in the ferrite nanocomposites. X-ray diffraction (XRD), a vibrating sample magnetometer (VSM), and a transmission electron microscope (TEM) were used to characterize the samples. From the result, it was found that the nanocomposite magnet with 10 wt% of soft phase content had the highest remanence ratio, M _r / M _s , which was 0.61, while the values of the coercivity, H _c , and magnetization, M _s , measured were 4482.4 G and 9.71 emu/g, respectively, and the average particle size of the ferrite nanocomposites was < 50 nm for all the samples. It was also shown that H _c decreased as the weight percent of the soft ferrite increased, which resulted from the dipolar interaction that occurred in the ferrite nanocomposites, showing the effect of phase distribution on the magnetic properties.     

Lateral Magnetically Modulated Multilayers by Combining Ion Implantation and Lithography

The combination of lithography and ion implantation is demonstrated to be a suitable method to prepare lateral multilayers. A laterally, compositionally, and magnetically modulated microscale pattern consisting of alternating Co (1.6 µm wide) and Co‐CoO (2.4 µm wide) lines has been obtained by oxygen ion implantation into a lithographically masked Au‐sandwiched Co thin film. Magnetoresistance along the lines (i.e., current and applied magnetic field are parallel to the lines) reveals an effective positive giant magnetoresistance (GMR) behavior at room temperature. Conversely, anisotropic magnetoresistance and GMR contributions are distinguished at low temperature (i.e., 10 K) since the O‐implanted areas become exchange coupled. This planar GMR is principally ascribed to the spatial modulation of coercivity in a spring‐magnet‐type configuration, which results in 180° Néel extrinsic domain walls at the Co/Co‐CoO interfaces. The versatility, in terms of pattern size, morphology, and composition adjustment, of this method offers a unique route to fabricate planar systems for, among others, spintronic research and applications.     

Self-reinforcing mechanisms for cellularisation: a longitudinal case study

Firms that adopt cellular manufacturing (CM) often need to restructure their products, personnel, equipment, factory management and organisation culture. Despite voluminous literature on CM, only a few case studies related to cellularisation exist. Therefore, to enhance understanding in this area, this paper presents a longitudinal case study on cellularisation in an electronic assembly plant. Six years of data were collected from the observations and discussions of an industrialist and an academician. Events instrumental to the persistence of CM were highlighted, with reference to path dependence analysis. Cellularisation is not entirely evolutionary or teleological but is an interplay of the two; it is significantly influenced by the positive feedback of self-reinforcing mechanisms after departing from critical junctures. The observed self-reinforcing mechanisms were expounded and divided into six categories.