Ozone Generation from Argon-Oxygen Mixtures in Presence of Different Packing Materials within Dielectric Barrier Discharge Gap

Assessments of ozone yield and concentration in Dielectric Barrier Discharge of argon-oxygen mixtures in presence of various packing materials are discussed. These include zeolite molecular sieve 13X pellets, Pyrex beads, Pyrex wool, and porous TiO₂-beads, which presented differential reactive surfaces, nano cavities, photo-catalysis, and dissimilar ionic environments. Their utility was evaluated in conjunction with varied gas composition, flow rate, and electrical inputs. In a mixture of 3–21% O₂ in argon, the ozone concentration ranged between 16–980 ppm, simultaneous measurements of in situ energy dissipation revealed its yield, G(O₃) to change independently from 0.002 to 2.020 μmol J^?1. TiO₂ packing emerged as the most versatile material to produce O₃ in high concentration and yield.     

设计待机功耗低于1W的电源

在过去二十多年里，家庭和办公电子设备的数量与种类迅速增长。电子设备的复杂度和性能也在不断提升。增强的功能要求这些设备即使在用户关断电源的情况下，仍保持一定的功能性。以家用电视机为例，二十年前，电视机的关断机制通常是利用安装在音量控制轴上的旋扭，以旋转方式关断系统的电源。如今，这个开关已被遥控装置所替代。当然，当电源关断时电视机仍处于“启动”状     

Fuzzy logic-based automatic contrast enhancement of satellite images of ocean

In this paper, we evaluate the conventional contrast enhancement techniques [histogram equalization (HE), adaptive HE] and the recent gray-level grouping method and the fuzzy logic method in order to find out which of these is well suited for automatic contrast enhancement for satellite images of the ocean, obtained from a variety of sensors. All the techniques evaluated were based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The performance of the different contrast enhancement algorithms are evaluated based on the visual quality and the Tenengrad criterion. The inter comparison of different techniques was carried out on a standard low-contrast image and also three different satellite images with different characteristics. Based on our study, we advocate that a modified fuzzy logic method elucidated in this paper is well suited for contrast enhancement of low-contrast satellite images of the ocean.     

A new fuzzy-based decision algorithm for high-density impulse noise removal

This paper proposes a new efficient fuzzy-based decision algorithm (FBDA) for the restoration of images that are corrupted with high density of impulse noises. FBDA is a fuzzy-based switching median filter in which the filtering is applied only to corrupted pixels in the image while the uncorrupted pixels are left unchanged. The proposed algorithm computes the difference measure for each pixel based on the central pixel (corrupted pixel) in a selected window and then calculates the membership value for each pixel based on the highest difference. The algorithm then eliminates those pixels from the window with very high and very low membership values, which might represent the impulse noises. Median filter is then applied to the remaining pixels in the window to get the restored value for the current pixel position. The proposed algorithm produces excellent results compared to conventional method such as standard median filter (SMF) as well as some advanced techniques such as adaptive median filters (AMF), efficient decision-based algorithm (EDBA), improved efficient decision-based algorithm (IDBA) and boundary discriminative noise detection (BDND) switching median filter. The efficiency of the proposed algorithm is evaluated using different standard images. From experimental analysis, it has been found that FBDA produces better results in terms of both quantitative measures such as PSNR, SSIM, IEF and qualitative measures such as Image Quality Index (IQI).     

LED背光照明设计中的各种选择

LED正在成为小到中型彩色显示器背光照明技术的主流选择.在显示子系统的设计中,LED的选择将对获得理想的性价比有着重要影响.此外,LED驱动IC,特别是那些新近推出的产品,能够与更廉价的LED一起工作,并通过若干方法增强LED的性能.除了亮度控制,这些驱动IC还能实现精确的亮度匹配,或者兼容若干种VF特性不同的LED.……     

Resource availability–aware adaptive provisioning of virtual data center networks

Optimal provisioning of virtual networks with varying topologies on their physical counterpart is a major challenge in cloud data centers. Embedding the virtual network on the shared physical infrastructure poses a multitude of challenges to the infrastructure provider. This paper proposes a hybrid approach which adapts to the availability and fragmentation level of residual resources for near‐optimal mapping of multiple virtual data center networks on a substrate data center network. The proposed technique uses coordinated static and dynamic embedding phases, adaptively, to maximize the density of embedding which increases the revenue of the cloud service provider. Also, it judiciously modifies the existing mappings for efficient utilization of resources. Empirical results show that the proposed hybrid approach can attain ～10% higher acceptance ratio compared with the existing exact and heuristic techniques in the literature. With the proposed mixed integer programming model for static embedding, the average path length is reduced by 20% compared with the existing techniques.     

Investigation of deep level defects in copper irradiated bipolar junction transistor

Commercial bipolar junction transistor (2N 2219A, npn) irradiated with 150 MeV Cu¹¹⁺-ions with fluence of the order 10¹² ions cm^?2, is studied for radiation induced gain degradation and deep level defects. I–V measurements are made to study the gain degradation as a function of ion fluence. The properties such as activation energy, trap concentration and capture cross-section of deep levels are studied by deep level transient spectroscopy (DLTS). Minority carrier trap levels with energies ranging from E_C ? 0.164 eV to E_C ? 0.695 eV are observed in the base–collector junction of the transistor. Majority carrier trap levels are also observed with energies ranging from E_V + 0.203 eV to E_V + 0.526 eV. The irradiated transistor is subjected to isothermal and isochronal annealing. The defects are seen to anneal above 350 °C. The defects generated in the base region of the transistor by displacement damage appear to be responsible for transistor gain degradation.     

Predictive-based adaptive switching median filter for impulse noise removal using neural network-based noise detector

A predictive-based adaptive switching median filter for impulse noise removal using neural network-based noise detector (PASMF) is presented. The PASMF has a noise detector stage and a noise filtering stage. The noise detector implemented using feed forward neural network detects impulse noises in the corrupted image. The filter is a modified median filter, which removes detected impulse noise from the image. In contrast to the standard median filter, the PASMF computes the median value after predicting the appropriate values for neighboring corrupted pixels of the current central pixel in the filtering window. The results show that the PASMF gives better performance visually as well as in terms of different performance measures.     

A risk comparison framework for evaluating the impact of telecom cloudification in organizational risk profile

Cloud computing has provided new dimensions and opportunities to telecom providers to enhance their ability in creating new revenue streams, reduce operational costs and increase customer satisfaction. In recent years, the progression of evolving cloud computing systems is huge. Conversely, it also encountered a lot of new challenges to the institutions utilizing cloud systems. It is critical to evaluate the change in organizational risk profile before deciding the level of cloud adoption. The conventional risk assessment framework of telecom providers may be unsuitable for cloud computing owing to the difficulties in the configuration. This paper aims to propose a system to quantify the influences of cloud adoption in telecom risk profile. This study also provides a comparison of overall risk profile change between clouds enabled infrastructure, traditional on-premises information technology solutions, and a combination of both in the telecom sector. The result encourages the selective adoption of the hybrid cloud model which demonstrated a relatively low organizational risk score. This work contributes to cloud computing business research by providing a holistic risk comparison model which reflects the distinctiveness of telecom service provider’s assets and capabilities.

     

Donor‐Induced Performance Tuning of Amorphous SrTiO3 Memristive Nanodevices: Multistate Resistive Switching and Mechanical Tunability

Metal–oxide valence‐change memristive devices are the key contenders for the development of multilevel nonvolatile analog memories and neuromorphic computing architectures. Reliable low energy performance and tunability of nonlinear resistive switching dynamics are essential to streamline the high‐density circuit level integration of these devices. Here, manipulation of room temperature‐synthesized defect chemistry is employed to enhance and tune the switching characteristics of high‐performance amorphous SrTiO₃ (a‐STO) memristors. Substitutional donor (Nb) doping with low concentrations in the a‐STO oxide structure allows extensive improvements in energy requirements, stability, and controllability of the memristive performance, as well as field‐dependent multistate resistive switching. Evidence is presented that room temperature donor doping results in a modified insulator oxide where dislocation sites act as charge carrier modulators for low energy and multilevel operation. Finally, the performance of donor‐doped a‐STO‐based memristive nanodevices is showcased, with the possibility of mechanical modulation of the nonlinear memristive characteristics of these devices demonstrated. These results highlight the potential of donor‐doped a‐STO nanodevices for high‐density integration as analog memories and multifunctional alternative logic elements.