Stability enhancement of polypyrrole thin film ammonia sensor by camphor sulfonic acid dopant

Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin...     

Characterization of the Ion Beam Current Density of the RF Ion Source with Flat and Convex Extraction Systems

Silicon - The characterization of ion beam current density distribution and beam uniformity is crucial for improving broad-beam ion source technologies. The design of the broad ion beam extraction...     

Poly(acrylic acid)/gum arabic/ZnO semi-IPN hydrogels: synthesis,characterization and their optimizations by response surface methodology

Iranian Polymer Journal - Synthesis of novel semi-interpenetrating poly(acrylic acid) (PAA)/gum arabic (AG)/ZnO hydrogels by in situ free radical polymerization was optimized using response surface...     

Swarm Intelligence Approaches for Grid Load Balancing

With the rapid growth of data and computational needs, distributed systems and computational Grids are gaining more and more attention. The huge amount of computations a Grid can fulfill in a specific amount of time cannot be performed by the best supercomputers. However, Grid performance can still be improved by making sure all the resources available in the Grid are utilized optimally using a good load balancing algorithm. This research proposes two new distributed swarm intelligence inspired load balancing algorithms. One algorithm is based on ant colony optimization and the other algorithm is based on particle swarm optimization. A simulation of the proposed approaches using a Grid simulation toolkit (GridSim) is conducted. The performance of the algorithms are evaluated using performance criteria such as makespan and load balancing level. A comparison of our proposed approaches with a classical approach called State Broadcast Algorithm and two random approaches is provided. Experimental results show the proposed algorithms perform very well in a Grid environment. Especially the application of particle swarm optimization, can yield better performance results in many scenarios than the ant colony approach.     

Where does model-driven engineering help? Experiences from three industrial cases

There have been few experience reports from industry on how Model-Driven Engineering (MDE) is applied and what the benefits are. This paper summarizes the experiences of three large industrial participants in a European research project with the objective of developing techniques and tools for applying MDE on the development of large and complex software systems. The participants had varying degrees of previous experience with MDE. They found MDE to be particularly useful for providing abstractions of complex systems at multiple levels or from different viewpoints, for the development of domain-specific models that facilitate communication with non-technical experts, for the purposes of simulation and testing, and for the consumption of models for analysis, such as performance-related decision support and system design improvements. From the industrial perspective, a methodology is considered to be useful and cost-efficient if it is possible to reuse solutions in multiple projects or products. However, developing reusable solutions required extra effort and sometimes had a negative impact on the performance of tools. While the companies identified several benefits of MDE, merging different tools with one another in a seamless development environment required several transformations, which increased the required implementation effort and complexity. Additionally, user-friendliness of tools and the provision of features for managing models of complex systems were identified as crucial for a wider industrial adoption of MDE.     

Heat treatment of YuNDK3 5T5 Alloys

Conclusions We investigated the effect of the cooling rate from 900 to 600° and high-temperature magnetic tempering at 790–830° on the magnetic properties of YuNDK35T5 alloys.It was found that the magnetic properties remain substantially unchanged with changes of the cooling rate from 2.1 to 0.73 deg/sec. The optimal temperature and time of high-temperature magnetic tempering coincide with those of ITMT in a lead bath.Cooling in magnetic field at rates of 2.1–0.73 deg/sec with subsequent high-temperature magnetic tempering at 810° for 12 min and two-stage tempering at 650° for 6 h+550° for 24 h makes it possible to obtain the following magnetic properties of alloys YuNDK35T5 and YuNDK35T5BA without use of a lead bath; B_r=9250 G and 11,300 G; H_c=1470 Oe and 1410 Oe; (BH)_max=5.5·10⁶ G-Oe and 11.2·10⁶ G-Oe.Moscow Institute of Steel and Alloys. Translated from Metallovedenie i Termicheskaya Obrabotka Metallov, No. 8, pp. 30–33, August, 1973.     

Polarization Effect in ESR of Co Doped CuGeO<Subscript>3</Subscript>

Electron spin resonance of a single crystal of CuGeO₃ doped with 2% of Co has been studied at f = 99 GHz in temperature range 1.8–50 K. Contributions to ESR absorption from Cu²⁺ chains and from Co²⁺ ions were derived. It is found that functions obtained for ESR integrated intensities: Curie-Weiss for Cu²⁺ (χCu ∼ C _Cu/(T + Θ), with Θ = 92 K) and Curie for Co²⁺ (χCo ∼ C _Co/T) are well consistent with temperature dependence of static magnetic susceptibility. Strong dependence of ESR absorption on polarization of oscillating magnetic field was discovered for Co²⁺ contribution. Polarization effect was studied for magnetic field applied along a, b and c directions. Values of g-factors of resonance lines are presented.     

Impact of query intent and search context on clickthrough behavior in sponsored search

Implicit feedback techniques may be used for query intent detection, taking advantage of user behavior to understand their interests and preferences. In sponsored search, a primary concern is the user’s interest in purchasing or utilizing a commercial service, or what is called online commercial intent. In this paper, we develop a methodology for employing the content of search engine result pages (SERPs), along with the information obtained from query strings, to study characteristics of query intent, with a particular focus on sponsored search. Our work represents a step toward the development and evaluation of an ontology for commercial search, considering queries that reference specific products, brands, and retailers. Characteristics of query categories are studied with respect to aggregated user clickthrough behavior on advertising links. We present a model for clickthrough behavior that considers the influence of such factors as the location of ads and the rank of ads, along with query category. We evaluate our work using a large corpus of clickthrough data obtained from a major commercial search engine. In addition, the impact of query intent is studied on clickthrough rate, where a baseline model and the query intent model are compared for the purpose of calculating an expected ad clickthrough rate. Our findings suggest that query-based features, along with the content of SERPs, are effective in detecting query intent. Factors such as query category, the rank of an ad, and the total number of ads displayed on a result page relate to the context of the ad, rather than its content. We demonstrate that these context-related factors can have a major influence on expected clickthrough rate, suggesting that these factors should be taken into consideration when the performance of an ad is evaluated.