A compact dual band short ended metamaterial antenna with extended bandwidth

A compact dual‐band CPW–fed metamaterial inspired antenna using Composite Right/Left Handed (CRLH) resonant approach is presented in this article. The antenna is designed such that it can be operated in series resonant mode where resonance behavior is characterized by series LC parameters. Proposed antenna comprises two annular ring resonators connected with the signal patch intended to excite the higher order modes. This results extension of second band from 51.4% (f_c = 6.92 GHz) to 69.2% (f_c = 7.35 GHz). In addition to that proposed antenna shows compact nature with an electrical size of 0.14 λ₀ × 0.21 λ0 × 0.01 λ₀ at f₀ = 2.18 GHz. The antenna is operating over 2.14–2.23 GHz, 4.81–9.90 GHz with simulated peak gain of 0.66 and 4.44 dB, respectively. Simulated radiation efficiencies of proposed antenna are 69.8 and 94.1% throughout first and second band, respectively. To examine the resonance and radiation characteristics prototype is fabricated and measured. Observed experimental results are in good agreement with those simulated one. These characteristics makes this antenna is a good candidate for modern wireless communication systems such as Bluetooth, WLAN/Wi‐Fi band. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:435–441, 2016.     

Fast and stable bayesian image expansion using sparse edge priors.

Smoothness assumptions in traditional image expansion cause blurring of edges and other high-frequency content that can be perceptually disturbing. Previous edge-preserving approaches are either ad hoc, statistically untenable, or computationally unattractive. We propose a new edge-driven stochastic prior image model and obtain the maximum a posteriori (MAP) estimate under this model. The MAP estimate is computationally challenging since it involves the inversion of very large matrices. An efficient algorithm is presented for expansion by dyadic factors. The technique exploits diagonalization of convolutional operators under the Fourier transform, and the sparsity of our edge prior, to speed up processing. Visual and quantitative comparison of our technique with other popular methods demonstrates its potential and promise.     

Computing access relevance for path-method generation in OODB and IM-OODB

A path-method (PM) is a mechanism to retrieve or to update information relevant to one class, in an object-oriented database (OODB), that is not stored with that class but with some other class. The PM traverses a chain of classes and connections that ends at the class where the required information is stored. However, it is a difficult task for a user to write PMs. This is because it might require comprehensive knowledge of many classes of the conceptual schema. But a typical user has often incomplete or even inconsistent knowledge of the schema. Currently we are developing a system, called Path-Method Generator (PMG), which generates PMs automatically according to a naive user's requests. One algorithm of PMG uses numerical access relevance between pairs of classes as a guide for the traversal of an OODB schema. In this paper we define the notion of access relevance to measure the significance of the (indirect) connection between any two classes in an OODB and present efficient algorithms to compute access relevance. The manual PM generation in an interoperable multi object-oriented database (IM-OODB) is even more difficult than for one OODB since a user has to be familiar with several OODBs. We use a hierarchical approach for developing efficient online algorithms for the computation of access relevances in an IM-OODB, based on precomputed access relevances for each autonomous OODB. In an IM-OODB the access relevances are used as a guide in generating PMs between the classes of different OODBs.     

Electrical characteristics of low temperature-Al0.3Ga0.7As

In this work, we present electrical characterizations of n⁺ GaAs/low temperature (LT)-Al_0.3Ga_0.7As/n⁺ GaAs resistor structures in which the LT layers are grown at nominal substrate temperatures of 250 and 300°C. The resistivity and V_tfl parameters of these LT-Al_0.3Ga_0.7As layers are compared with those of LT-GaAs and Al_0.3Ga_0.7As grown at a normal growth temperature of 720°C. Low-temperature Al_0.3Ga_0.7As layers exhibit resistivities as high as 10¹² ohm-cm, nearly four orders of magnitude higher than that of LT-GaAs, and V_tfl values as high as 45 V, over twice that of LT-GaAs. We also find that the LT-Al_0.3Ga_0.7As materials grown at 250 and 300°C appear to show opposite and contradictory trends with respect to resistivity and V_tfl. We propose that this result can be explained by residual hopping conduction in the 250°C material. Temperature dependent conductivity measurements confirm the presence of a hopping mechanism in LT-Al_0.3Ga_0.7As grown at 250°C and yield activation energies of 0.77 and 0.95 eV for LT-GaAs and LT-Al_0.3Ga_0.7As, respectively.     

Effect of alloying on the electronic structure and magnetic properties of Fe,Co and Ni with Au and Ag

We use the self-consistent, augmented space recursion technique to study the electronic structure and magnetic properties of alloys of the transition metals, Fe, Co and Ni with the noble metals, Ag and Au. We analyse the effect of local environment and the hybridization between the constituent bands on the electronic and magnetic properties.     

Influence of variation in calcium content on casein micelle stability and techno-functional properties of buffalo milk

Changes in techno-functional properties of buffalo milk were evaluated due to variation in calcium content. Decalcification resulted in significant variation in ζ-potential, casein size, colour and η_app. However, calcium addition only influenced ζ-potential of milk. In case of acid gelation, the time and temperature required for coagulation decreased significantly for both calcium-depleted and -added milks. However, during chymosin gelation, only 20%–30% of calcium-depleted milk coagulated with an increased clotting time. Furthermore, calcium addition increased firmness, consistency and cohesiveness of both chymosin and acid-induced gelation.     

Practical approach to tuning MPC

This paper presents the results of a heuristic approach for developing model predictive control (MPC) tuning rules. The tuning has been applied and tested in easy-to-use MPC. Process modeling in this MPC uses normalized input/ output range. As a result there is no need for tuning outputs, a procedure known as adjusting equal concern error. Penalties on moves are set as a function of process dead time as the primary factor, with some correction from process gain. The default calculation delivers robust control, which tolerates up to triple increase in process static gain. If control is too aggressive, further on-line adjustment can be done by set point reference trajectory. Test results show that this tuning is robust for process gain change, however, it is much less efficient in compensating for process dead-time changes. It was found that dead-time mismatch is much better compensated with the model correction filter. Combining the three handles, i.e., penalties on moves, reference trajectory, and model filter, easy and intuitively understandable MPC tuning was achieved. The findings are illustrated by numerous MPC simulated tests.     

Improving reliability and reducing cost of task execution on preemptible VM instances using machine learning approach

The Journal of Supercomputing - Cloud users can acquire resources in the form of virtual machines (VMs) instances for computing. These instances can be on-demand, reserved and spot instances....     

State-of-the-art technology in variable compression ratio mechanism for spark ignition engine

Present investigations deal with development of a novel variable compression ratio (VCR) mechanism and its implementation in a small and relatively large size single-cylinder engines. Operation of this mechanism is found to be smooth and effective in the running condition of the engine as well. This mechanism, when incorporated in the small size spark ignition HONDA engine, portrayed improvement in engine performance with increment in compression ratio (CR) for petrol and kerosene. Their respective optimum CRs 5.02 (petrol) and 5.27 (kerosene) are higher than the base value 4.8. In case of large size KIRLOSKAR engine, the present VCR mechanism is found to be useful while operating with liquefied petroleum gas (LPG), where measurements showed that combustion duration is lower with LPG for CR 9.79 as compared with base value 9.0. The present experiments clearly demonstrate the usefulness of VCR mechanism in improving engine performance for a given fuel and broadening the range of alternative fuels burnt in the engine. Ease of fabrication, simplicity in installation, accessibility in troubleshooting and smooth run-time alterations are the advantages with the current novel mechanism.     

Activatable Nanoreporters for Real-Time Tracking of Macrophage Phenotypic States Associated with Disease Progression

Diagnosis of inflammatory diseases is characterized by identifying symptoms, biomarkers, and imaging. However, conventional techniques lack the sensitivities and specificities to detect disease early. Here, it is demonstrated that the detection of macrophage phenotypes, from inflammatory M1 to alternatively activated M2 macrophages, corresponding to the disease state can be used to predict the prognosis of various diseases. Activatable nanoreporters that can longitudinally detect the presence of the enzyme Arginase 1, a hallmark of M2 macrophages, and nitric oxide, a hallmark of M1 macrophages are engineered, in real-time. Specifically, an M2 nanoreporter enables the early imaging of the progression of breast cancer as predicted by selectively detecting M2 macrophages in tumors. The M1 nanoreporter enables real-time imaging of the subcutaneous inflammatory response that rises from a local lipopolysccharide (LPS) administration. Finally, the M1-M2 dual nanoreporter is evaluated in a muscle injury model, where an initial inflammatory response is monitored by imaging M1 macrophages at the site of inflammation, followed by a resolution phase monitored by the imaging of infiltrated M2 macrophages involved in matrix regeneration and wound healing. It is anticipated that this set of macrophage nanoreporters may be utilized for early diagnosis and longitudinal monitoring of inflammatory responses in various disease models.