A Framework for Scalable Autonomous P2P Resource Discovery for the Grid Implementation

Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.

Resistive Switching in TaN/AlNx/TiN Cell

Resistive switching of aluminum nitride (AlNx) thin film was demonstrated in a TaN/AlNx/TiN memory cell that was prepared by sputter deposition techniques. The memory cell showed bipolar switching of resistance between +3.5 V and –3.5 V. The resistance ratio of high resistance state (HRS) to low resistance state (HRS), RHRS/RLRS, was about 2 over 100 cycles of endurance test. Both the LRS and HRS of the memory cell exhibited ohmic conduction at low voltages and Poole-Frenkel emission at high voltages. The electrical conduction in the TaN/AlNx/TiN memory cell was possibly attributed to the interactions between charges and defects in the AlNx film.

Towards Automatic Recognition and Grading of Ganoderma Infection Pattern Using Fuzzy Systems

This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

Lodging Business Management in Nakhon Pathom with Sufficient Economy Approach

The objectives of this research are to search the management pattern of Nakhon Pathom lodging entrepreneurs for sufficient economy ways, to know the threat that affects this sector and design fit arrangement model to sustain their business with Nakhon Pathom style. What will happen if they do not use this approach? Will they have a financial crisis? The data and information are collected by informal discussions with 12 managers and 400 questionnaires. A mixed method of both qualitative research and quantitative research are used. Bent Flyvbjerg’s phronesis is utilized for this analysis. Our research will prove that sufficient economy can help small business firms to solve their problems. We think that the results of our research will be a financial model to solve many problems of the entrepreneurs and this way will can be a model for other provinces of Thailand.

Study on Microbial Pretreatment for Enhancing Enzymatic Hydrolysis of Corncob

The complex structure of lignocellulose leads to great difficulties in converting it to fermentable sugars for the ethanol production. The major hydrolysis impediments are the crystallinity of cellulose and the lignin content. To improve the efficiency of enzymatic hydrolysis, microbial pretreatment of corncob was investigated using two bacterial strains of Bacillus subtilis A 002 and Cellulomonas sp. TISTR 784 (expected to break open the crystalline part of cellulose) and lignin-degrading fungus, Phanerochaete sordida SK7 (expected to remove lignin from lignocellulose). The microbial pretreatment was carried out with each strain under its optimum conditions. The pretreated corncob samples were further hydrolyzed to produce reducing glucose with low amounts of commercial cellulase (25 U·g-1 corncob) from Aspergillus niger. The corncob samples were determined for composition change by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscope (SEM). According to the results, the microbial pretreatment with fungus, P. sordida SK7 was the most effective for enhancing enzymatic hydrolysis, approximately, 40% improvement.

Proton-conducting PVA/PMA Hybrid Membranes for Fuel Cell Applications

The hybrid membranes containing inorganic materials in polymer matrix are identified as a remarkable family of proton conducting hybrid electrolytes. In this work, the proton conducting inorganic/organic hybrid membranes for proton exchange membrane fuel cells (PEMFCs) were prepared using polyvinyl alcohol (PVA), tetraethoxyorthosilane (TEOS) and heteropolyacid (HPA). The synthesized hybrid membranes were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction spectroscopy (XRD), Scanning electron microscopy (SEM) and Thermogravimetry analysis (TGA). The effects of heteropolyacid incorporation on membrane properties, including morphology and thermal stability were extensively investigated.

Enhanced Quality of Zeolite LSX: Studying Effect of Crystallized Containers

Low silica type X (LSX) Zeolite is one of useful material in many manufacturing due to the advantage properties including high surface area, stability, microporous crystalline aluminosilicates and positive ion in an extra–framework. The LSX was used rice husk silica source which obtained by leaching with hydrochloric acid and calcination at 500C. To improve the synthesis method, the LSX was crystallizated in Teflon–lined autoclave will expedite deceasing of the amorphous particles. The mixed gel with composition of 5.5 Na2O : 1.65 K2O : Al2O3 : 2.2 SiO2 : 122 H2O was crystallized in different container (Polypropylene bottom and Teflon–lined autoclave). The obtained powder was characterized by X–ray diffraction (XRD), X–ray fluorescence spectrometry, N2 adsorption-desorption analysis BET surface area Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy to justify the quality of zeolite. The results showed the crystallized zeolite in Teflon lined autoclave has 102.8 nm of crystal size, 286 m2/g of surface area and fewer amounts of round amorphous particles when compared with the crystallized zeolite in Polypropylene.

The Effectiveness of Tebuconazole and Chitosan in Inhibiting the Growth of Fusarium Species on Winter Wheat Grain under Field Conditions

A three-year field experiment (2010-2012) was conducted to determine the abundance of epiphytic and endophytic filamentous fungi colonizing the grain of winter wheat cv. Bogatka. Wheat spikes were protected with tebuconazole or chitosan at the watery ripe stage. Untreated plants served as control. Tebuconazole exerted an inhibitory effect primarily on F. culmorum and F. graminearum, and its effectiveness was determined by the pressure from pathogens that infected wheat spikes during the growing season. Chitosan did not suppress the growth of Fusarium species and Alternaria alternata.

An Exact MCNP Modeling of Pebble Bed Reactors

Double heterogeneity of randomly located pebbles in the core and Coated Fuel Particles (CFPs) in the pebbles are specific features in pebble bed reactors and usually, because of difficulty to model with MCNP code capabilities, are neglected. In this study, characteristics of HTR-10, Tsinghua University research reactor, are used and not only double heterogeneous but also truncated CFPs and Pebbles are considered.Firstly, 8335 CFPs are distributed randomly in a pebble and then the core of reactor is filled with those pebbles and graphite pebbles as moderator such that 57:43 ratio of fuel and moderator pebbles is established.Finally, four different core configurations are modeled. They are Simple Cubic (SC) structure with truncated pebbles,SC structure without truncated pebble, and Simple Hexagonal(SH) structure without truncated pebbles and SH structure with truncated pebbles. Results like effective multiplication factor (Keff), critical height,etc. are compared with available data.

A Subjectively Influenced Router for Vehicles in a Four-Junction Traffic System

A subjectively influenced router for vehicles in a fourjunction traffic system is presented. The router is based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy routing procedure. The BPNN detects priorities of vehicles based on the subjective criteria. The subjective criteria and the routing procedure depend on the routing plan towards vehicles depending on the user. The routing procedure selects vehicles from their junctions based on their priorities and route them concurrently to the traffic system. That is, when the router is provided with a desired vehicles selection criteria and routing procedure, it routes vehicles with a reasonable junction clearing time. The cost evaluation of the router determines its efficiency. In the case of a routing conflict, the router will route the vehicles in a consecutive order and quarantine faulty vehicles. The simulations presented indicate that the presented approach is an effective strategy of structuring a subjective vehicle router.

Enhanced Performance for Support Vector Machines as Multiclass Classifiers in Steel Surface Defect Detection

Steel surface defect detection is essentially one of pattern recognition problems. Support Vector Machines (SVMs) are known as one of the most proper classifiers in this application. In this paper, we introduce a more accurate classification method by using SVMs as our final classifier of the inspection system. In this scheme, multiclass classification task is performed based on the "one-againstone" method and different kernels are utilized for each pair of the classes in multiclass classification of the different defects. In the proposed system, a decision tree is employed in the first stage for two-class classification of the steel surfaces to "defect" and "non-defect", in order to decrease the time complexity. Based on the experimental results, generated from over one thousand images, the proposed multiclass classification scheme is more accurate than the conventional methods and the overall system yields a sufficient performance which can meet the requirements in steel manufacturing.

Analytical Solution of Time-Harmonic Torsional Vibration of a Cylindrical Cavity in a Half-Space

In this article an isotropic linear elastic half-space with a cylindrical cavity of finite length is considered to be under the effect of a ring shape time-harmonic torsion force applied at an arbitrary depth on the surface of the cavity. The equation of equilibrium has been written in a cylindrical coordinate system. By means of Fourier cosine integral transform, the non-zero displacement component is obtained in the transformed domain. With the aid of the inversion theorem of the Fourier cosine integral transform, the displacement is obtained in the real domain. With the aid of boundary conditions, the involved boundary value problem for the fundamental solution is reduced to a generalized Cauchy singular integral equation. Integral representation of the stress and displacement are obtained, and it is shown that their degenerated form to the static problem coincides with existing solutions in the literature.

Analysis of Driving Conditions and Preferred Media on Diversion

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

Why do Clawback Provisions Affect Financial Reporting Quality? - An Analysis of Trigger Effects

We identify clawback triggers from firms- proxy statements (Form DEF 14A) and use the likelihood of restatements to proxy for financial reporting quality. Based on a sample of 578 U.S. firms that voluntarily adopt clawback provisions during 2003-2009, when restatement-based triggers could be decomposed into two types: fraud and unintentional error, and we do observe the evidence that using fraud triggers is associated with high financial reporting quality. The findings support that fraud triggers can enhance deterrent effect of clawback provision by establishing a viable disincentive against fraud, misconduct, and otherwise harmful acts. These results are robust to controlling for the compensation components, to different sample specifications and to a number of sensitivity.

Plasma Density Distribution in Asymmetric Geometry Capacitive Coupled Plasma Discharge System

In this work, we used the single Langmuir probe to measure the plasma density distribution in an geometrically asymmetric capacitive coupled plasma discharge system. Because of the frame structure of powered electrode, the plasma density was not homogeneous in the discharge volume. It was higher under the frame, but lower in the centre. Finite element simulation results showed a good agreement with the experiment results. To increase the electron density in the central volume and improve the homogeneity of the plasma, we added an auxiliary electrode, powered by DC voltage, in the simulation geometry. The simulation results showed that the auxiliary electrode could alter the potential distribution and improve the density homogeneity effectively.

Sample-Weighted Fuzzy Clustering with Regularizations

Although there have been many researches in cluster analysis to consider on feature weights, little effort is made on sample weights. Recently, Yu et al. (2011) considered a probability distribution over a data set to represent its sample weights and then proposed sample-weighted clustering algorithms. In this paper, we give a sample-weighted version of generalized fuzzy clustering regularization (GFCR), called the sample-weighted GFCR (SW-GFCR). Some experiments are considered. These experimental results and comparisons demonstrate that the proposed SW-GFCR is more effective than the most clustering algorithms.

Conflict, Confusion, Choice: A Phenomenological Approach to Acts of Corruption

Public sector corruption has long-term and damaging effects that are deep and broad. Addressing corruption relies on understanding the drivers that precipitate acts of corruption and developing educational programs that target areas of vulnerability. This paper provides an innovative approach to explore the nature of corruption by drawing on the perceptions and ideas of a group of public servants who have been part of a corruption investigation. The paper examines these reflections through the ideas of Pierre Bourdieu and Alfred Schutz to point to some of the steps that can lead to corrupt activity. The paper demonstrates that phenomenological inquiry is useful in the exploration of corruption and, as a theoretical framework, it highlights that corruption emerges through a combination of conflict, doubt and uncertainty. The paper calls for anti-corruption education programs to be attentive to way in which these conditions can influence the steps into corruption.

Adaptive Naïve Bayesian Anti-Spam Engine

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.

Synthesis and Characterization of ZnO and Fe3O4 Nanocrystals from Oleat-based Organometallic Compounds

Magnetic and semiconductor nanomaterials exhibit novel magnetic and optical properties owing to their unique size and shape-dependent effects. With shrinking the size down to nanoscale region, various anomalous properties that normally not present in bulk start to dominate. Ability in harnessing of these anomalous properties for the design of various advance electronic devices is strictly dependent on synthetic strategies. Hence, current research has focused on developing a rational synthetic control to produce high quality nanocrystals by using organometallic approach to tune both size and shape of the nanomaterials. In order to elucidate the growth mechanism, transmission electron microscopy was employed as a powerful tool in performing real time-resolved morphologies and structural characterization of magnetic (Fe3O4) and semiconductor (ZnO) nanocrystals. The current synthetic approach is found able to produce nanostructures with well-defined shapes. We have found that oleic acid is an effective capping ligand in preparing oxide-based nanostructures without any agglomerations, even at high temperature. The oleate-based precursors and capping ligands are fatty acid compounds, which are respectively originated from natural palm oil with low toxicity. In comparison with other synthetic approaches in producing nanostructures, current synthetic method offers an effective route to produce oxide-based nanomaterials with well-defined shapes and good monodispersity. The nanocystals are well-separated with each other without any stacking effect. In addition, the as-synthesized nanopellets are stable in terms of chemically and physically if compared to those nanomaterials that are previous reported. Further development and extension of current synthetic strategy are being pursued to combine both of these materials into nanocomposite form that will be used as “smart magnetic nanophotocatalyst" for industry waste water treatment.

Marangoni Convection in a Fluid Saturated Porous Layer with a Deformable Free Surface

The stability analysis of Marangoni convection in porous media with a deformable upper free surface is investigated. The linear stability theory and the normal mode analysis are applied and the resulting eigenvalue problem is solved exactly. The Darcy law and the Brinkman model are used to describe the flow in the porous medium heated from below. The effect of the Crispation number, Bond number and the Biot number are analyzed for the stability of the system. It is found that a decrease in the Crispation number and an increase in the Bond number delay the onset of convection in porous media. In addition, the system becomes more stable when the Biot number is increases and the Daeff number is decreases.