Bias dependence of high-frequency noise in heterojunction bipolar transistors

Hawkins' isothermal model developed to study noise in bipolar junction transistors (BJTs) is modified to investigate bias-dependent noise in heterojunction bipolar transistors (HBTs) by incorporating thermal effects. It is shown that the inclusion of thermal effects into the high-frequency noise model of HBTs is necessary as the temperature of the device may become very different from the ambient temperature, especially at high bias current. Calculation of the noise figure by including the thermal effect shows that the isothermal calculation may underestimate the noise figure at high bias current. It is observed that noise at low bias is ideality factor n dependent whereas high bias noise is insensitive to the variation of n. Moreover, the common base current gain plays a major role in the calculation of the minimum noise figure. The excellent fit obtained between the theoretical calculation and the measured data are attributed to the inclusion of the bias-dependent junction heating as well as C/sub De/ and C/sub bc/ into the present calculation.     

Investigation of solar selective and microstructural properties of molybdenum black immersion coatings on cobalt substrates

Molybdenum black solar selective coatings have been produced on cobalt by immersion in a solution of ammonium paramolybdate and nickel sulphate. The cobalt was electroplated on nickel-plated copper prior to immersion in the paramolybdate solution. The maximum solar absorptance of the resulting molybdenum black coating was about 0.91. The minimum emittance was about 0.1 for coatings on cobalt deposited with an addition agent and about 0.23 for coatings on cobalt deposited without addition agent in the 60 °C plating solution. These differences have been related to the coating morphology determined by scanning electron microscopy. The emittance of coatings on cobalt deposited without addition agent decreases (or remains unchanged) during short-term heat treatment while that of coatings deposited on cobalt plated with addition agent increases somewhat. Reduction of the cobalt plating bath temperature to 45 °C can also lead to good initial coating properties but without the requirement for an addition agent in the cobalt plating bath. XPS studies show that the oxidation state of molybdenum in the coatings is approximately + 5 corresponding to Mo₄O₁₁. This reduces to + 4 after argon ion bombardment. Some cobalt may be present in the coatings in the form of CoO.     

Extremal optimization vs. learning automata: Strategies for spin selection in portfolio selection problems

Nowadays, various imitations of natural processes are used to solve challenging optimization problems faster and more accurately. Spin glass based optimization, specifically, has shown strong local search capability and parallel processing. But, spin glasses have a low rate of convergence since they use Monte Carlo simulation techniques such as simulated annealing (SA). Here, we propose two algorithms that combine the long range effect in spin glasses with extremal optimization (EO-SA) and learning automata (LA-SA). Instead of arbitrarily flipping spins at each step, these two strategies aim to choose the next spin and selectively exploiting the optimization landscape. As shown in this paper, this selection strategy can lead to faster rate of convergence and improved performance. The resulting two algorithms are then used to solve portfolio selection problem that is a non-polynomial (NP) complete problem. Comparison of test results indicates that the two algorithms, while being very different in strategy, provide similar performance and reach comparable probability distributions for spin selection. Furthermore, experiments show there is no difference in speed of LA-SA or EO-SA for glasses with fewer spins, but EO-SA responds much better than LA-SA for large glasses. This is confirmed by tests results of five of the world's major stock markets. In the last, the convergence speed is compared to other heuristic methods such as Neural Network (NN), Tabu Search (TS), and Genetic Algorithm (GA) to approve the truthfulness of proposed methods.     

Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated as initial reconfigurable technologies have emerged. Hence, in this paper, it is proposed that the DWT method can be implemented on a field-programmable gate array in a digital architecture (FPGA-DA). We examined the effects of quantization on DWT performance in classification problems to demonstrate its reliability concerning fixed-point math implementations. The Advanced Encryption Standard (AES) algorithm for DWT learning used in this architecture is less responsive to resampling errors than the previously proposed solution in the literature using the artificial neural networks (ANN) method. By reducing hardware area by 57%, the proposed system has a higher throughput rate of 88.72%, reliability analysis of 95.5% compared to the other standard methods.     

Visual perception and mixed-initiative interaction for assisted visualization design

This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets. ViA applies knowledge of low-level human vision to: (1) evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and (2) rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date. Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences. We visualize historical weather conditions to compare ViA's search strategy to exhaustive analysis, simulated annealing, and reactive tabu search, and to measure the improvement provided by mixed-initiative interaction. We also visualize intelligent agents competing in a simulated online auction to evaluate ViA's perceptual guidelines. Results from each study are positive, suggesting that ViA can construct high-quality visualizations for a range of real-world datasets.     

Antifungal activity of five different essential oils in vapour phase for the control of Colletotrichum gloeosporioides and Lasiodiplodia theobromae in vitro and on mango

Mango fruit has high commercial value; however, major postharvest losses are encountered throughout the supply chain due to postharvest diseases. These results lead to the search for natural fungicide for postharvest diseases control. The antifungal effects of five essential oils (thyme, clove, cinnamon, anise and vitex) were assessed by disc volatilisation method. Thyme oil vapours at 5 μL per Petriplate, and clove and cinnamon oil at 8 μL per Petriplate showed 100% growth inhibition of mango pathogens in vitro. GC/MS analysis of essential oil showed thymol (23.88), o‐cymol (23.88) and terpinolene (23.88) as the major constituents of thyme oil. Clove and cinnamon oils contain 3‐allyl‐2‐methoxyphenol (37.42%) and benzofuran 3‐methyl (17.97%), respectively. Thyme oil as a fumigant at 66.7 μL L^?1 showed a significant (P < 0.05) inhibition on postharvest pathogens of mango fruits stored at 25 °C for 6 days. Results of our study suggest the possibility of using thyme oil as an alternate natural fungicide to manage postharvest diseases in mango.     

One-pot synthesis of hematite-alumina hollow sphere composite by ultrasonic spray pyrolysis technique with high adsorption capacity toward PAHs

A hybrid nanocomposite of alumina and hematite was synthesized by ultrasonic spray pyrolysis technique. The study of microscopic images, mapping analysis, and XRD patterns revealed that the Al₂O₃ – Fe₂O₃ nanocomposite was composed of separated spherical particles with a thin layer ball-shaped structure that metal oxides are uniformly distributed in the wall of hollow sphere particles, led to a coherent and monotonous construction. A series of coefficients of equilibrium sorption of polycyclic aromatic hydrocarbons (PAHs) as hazardous materials were measured on the prepared composite material in a batch technique. The free or pure Al₂O₃ or Fe₂O₃ showed negligible removal efficiency for the mentioned analytes. The various significant variables, such as initial analyte concentration, solution pH, adsorbent dose, and contact time to remove analyte, were studied in the aqueous solutions. Adsorption data were modeled to Langmuir, Freundlich, and Temkin isotherms, and a good correlation found in the case of Langmuir isotherm and adsorption capacity for anthracene, phenanthrene, and naphthalene were 370, 333, and 322 mg g^?1, respectively. Investigation of the kinetic models proved a pseudo-second-order, and the prepared adsorbent can be reused more than 7 times without a significant decrease of adsorption performance.     

The Promise of Novel Molecular Markers in Bladder Cancer

Bladder cancer is the fourth most common malignancy in the US and is associated with the highest cost per patient. A high likelihood of recurrence, mandating stringent surveillance protocols, has made the development of urinary markers a focus of intense pursuit with the hope of decreasing the burden this disease places on patients and the healthcare system. To date, routine use of markers is not recommended for screening or diagnosis. Interests include the development of a single urinary marker that can be used in place of or as an adjunct to current screening and surveillance techniques, as well identifying a molecular signature for an individual’s disease that can help predict progression, prognosis, and potential therapeutic response. Markers have shown potential value in improving diagnostic accuracy when used as an adjunct to current modalities, risk-stratification of patients that could aid the clinician in determining aggressiveness of surveillance, and allowing for a decrease in invasive surveillance procedures. This review discusses the current understanding of emerging biomarkers, including miRNAs, gene signatures and detection of circulating tumor cells in the blood, and their potential clinical value in bladder cancer diagnosis, as prognostic indicators, and surveillance tools, as well as limitations to their incorporation into medical practice.