Bailout forward contracts for edge-to-edge internet services

Despite the huge success of the Internet in providing basic communication services, its economic architecture needs to be upgraded so as to provide end-to-end guaranteed or more reliable services to its customers. Currently, a user or an enterprise that needs end-to-end bandwidth guarantees between two arbitrary points in the Internet for a short period of time has no way of expressing its needs. To allow these much needed basic services, we propose a single-domain edge-to-edge (g2g) dynamic capacity contracting mechanism, where a network customer can enter into a bandwidth contract on a g2g path at a future time, at a predetermined price. For practical and economic viability, such forward contracts must involve a bailout option to account for bandwidth becoming unavailable at service delivery time, and must be priced appropriately to enable Internet Service Providers (ISPs) manage risks in their contracting and investments. Our design allows ISPs to advertise point-to-point different prices for each of their g2g paths instead of the current point-to-anywhere prices, allowing discovery of better end-to-end paths, temporal flexibility and efficiency of bandwidth usage. We compute the risk-neutral prices for these g2g bailout forward contracts (BFCs), taking into account correlations between different contracts due to correlated demand patterns and overlapping paths. We apply this multiple g2g BFC framework on network models with Rocketfuel topologies. We evaluate our contracting mechanism in terms of key network performance metrics like fraction of bailouts, revenue earned by the provider, and adaptability to link failures. We also explore the tradeoffs between complexity of pricing and performance benefits of our BFC mechanism.     

The effects of immunological castration against GnRH with recombinant OL protein (Ovalbumin-LHRH-7) on carcass and meat quality characteristics,histological appearance of testes and pituitary gland in Kıvırcık male lambs

The aims of the study were to investigate the effects of immunization against GnRH using OL protein (Ovalbumin-LHRH-7) on feedlot performance, carcass, meat quality and some reproductive traits in K?v?rc?k ram lambs. Ram lambs in the immunization (I, n = 7) group were immunized against GnRH using OL protein and boosted 2 weeks later. Control (C, n = 7) group was not treated. The animals were kept at pasture for 6 weeks after the first immunization, subjected to a 70 day fattening program, and then slaughtered. Growth performance, various carcass and meat quality characteristics were not affected from the immunization. GnRH immunization induced GnRH antibody production, suppressed testosterone production and testicular growth (P < 0.01). Testicular structure was negatively affected from the immunization, but not pituitary. These results suggest that immunization against GnRH with OL could be an alternative castration technique in ram lambs without negatively affecting carcass and meat quality characteristics.     

Development of an RF Conditioning System for Charged-Particle Accelerators

Charged-particle accelerators use various vacuum windows on their accelerating radio-frequency (RF) cavities to throughput very high RF power. Before being placed on the cavities, the windows should be cleaned, baked, and fully RF conditioned to prevent a poor vacuum from outgassing, as well as other forms of contamination. An example is the coaxial fundamental power coupler (FPC) with an annular alumina ceramic window for each of the 81 superconducting RF cavities in the Spallation Neutron Source (SNS) linear accelerator. The FPCs needed to be tested up to 650-kW peak in a traveling wave and 2.6 MW with standing wave peaks in 1.3 and 60 pulses/s at 805 MHz. In this paper, an Experimental-Physics-and-Industrial-Control-System-based RF conditioning system for the SNS RF test facility is presented. This paper summarizes the hardware and software design strategies, provides the results obtained, and describes the future research scope.     

Characteristics of CFRP retrofitted hollow brick infill walls of reinforced concrete frames

The mechanical characteristics of infill walls retrofitted with carbon fiber reinforced polymer (CFRP) sheets are really important for the realistic prediction of seismic performance of the vulnerable reinforced concrete (RC) frames retrofitted through CFRP strengthened infill walls. In this study, 36 hollow brick wall specimens were tested either under uniaxial compression or diagonal tension before and after retrofitting externally with CFRP sheets. The test parameters are the dimensions of the walls, the orientation of holes of bricks, the type of mortar, the amount of CFRP sheets and the details of strengthening application. At the end of the tests, a significant contribution of CFRP sheets on the mechanical characteristics of hollow brick walls was observed in terms of several important structural design parameters such as Young and shears moduli, axial and shears strengths as well as the deformation capacity. Finally, the strength and deformability characteristics of the walls and frames retrofitted with CFRP sheets were predicted analytically. The predictions were in good agreement with the experimental data.     

An expert system for the humidity and temperature control in HVAC systems using ANFIS and optimization with Fuzzy Modeling Approach

The aim of this study is to design a HVAC system which damper gap rates have been controlled by PID controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. In the authors’ previous theoretical work, PID parameters were theoretically obtained by using fuzzy sets for the same HVAC system. Optimization with Fuzzy Modeling Approach of PID parameters has been performed to maximize the performance of the system. The obtained PID parameters in the previous theoretical work were used in this study. Besides, the damper gap rates of a HVAC system with only one zone were predicted by using Artificial Neural Fuzzy Interface System (ANFIS) method. The input-output data sets of this system were first stored and then these data sets were used to obtain its intelligent model and control based on ANFIS. Efficiency of the developed ANFIS method was tested and a mean 99.98% recognition success was obtained. This paper shows that the values predicted with the ANFIS can be used to predict damper gap rate of HVAC system quite accurately. Therefore, faster and simpler solutions can be obtained based on ANFIS.     

An ANFIS-based approach for predicting the bed load for moderately sized rivers

A total of 346 sets of bed-load data obtained from the Kinta River, Pari River, Kerayong River and Langat River were analyzed using four common bed-load equations. These assessments, based on the median sediment size (d₅₀), show that the existing equations were unable to predict the measured bed load accurately. All existing equations over-predicted the measured values, and none of the existing bed-load equations gave satisfactory performance when tested on local river data. Therefore, the present study applies a new soft computing technique, i.e. an adaptive neuro-fuzzy inference system (ANFIS), to better predict measured bed-load data. Validation of the developed network (ANFIS) was performed using a new set of bed-load data collected at Kulim River. The results show that the recommended network can more accurately predict the measured bed-load data when compared to an equation based on a regression method.     

Synthesis and optimization of barium manganate nanofibers by electrospinning

Barium manganate nanofibers were successfully synthesized for the first time after heat treatment of composite nanofibers of polyvinyl pyrrolidone (PVP), barium acetate and manganese acetate using electrospinning technique. Different PVP concentrations were used and the results show that PVP concentration had played important role in the formation, uniformity, homogeneity and particularly in the reduction of nanofibers diameter. Crystal structure, microstructure, elemental analysis and surface morphology were studied using X-ray diffraction analysis, scanning electron microscopy, energy dispersive X-ray spectroscopy and Fourier transform infrared spectroscopy. X-ray diffraction results show that at low temperature there is no crystallinity in the fibers sample and at ∼400 °C formations of barium manganate crystalline phase starts and finally at 700 °C all the nanofibers became single phase. The first two high intensity peaks (1 0 1) and (1 1 0) give an average crystallite size of about 20 nm. The scanning electron micrographs show that the morphology of the fibers is smooth and uniform at low temperature and become slightly porous at intermediate temperature and finally at high temperature of 700 °C the fibers become highly porous, shrank and their average diameter reduced from ∼400 nm to about 100 nm. These fibers are made of grains with sizes ranging from 15 to 30 nm. Energy dispersive X-ray spectroscopy and Fourier transform infra-red results are also in good agreement with XRD and SEM results.     

Size Distributions of Species in Fine Particles in Denver Using a Microorifice Impactor

Size-fractionated fine particles in Denver, Colorado, were collected by a microorifice impactor and analyzed for mass and elemental composition by a β-gauge and an X-ray fluorescence spectrometer. A least-squares procedure was used to fit a lognormal distribution function to the data in order to determine values and uncertainties for the mass median aerodynamic diameter and geometric standard deviation. The validity of the uncertainties so determined was tested by comparing them to uncertainties derived from Monte Carlo simulations.