Fixed argument pairings

A common scenario in many pairing-based cryptographic protocols is that one argument in the pairing is fixed as a long term secret key or a constant parameter in the system. In these situations, the runtime of Miller's algorithm can be significantly reduced by storing precomputed values that depend on the fixed argument, prior to the input or existence of the second argument. In light of recent developments in pairing computation, we show that the computation of the Miller loop can be sped up by up to 37 if precomputation is employed, with our method being up to 19.5 faster than the previous precomputation techniques.

Description and evaluation of a Newton-based electronic appetite rating system for temporal tracking of appetite in human subjects

This study assessed the reliability and validity of a palm-top-based electronic appetite rating system (EARS) in relation to the traditional paper and pen method. Twenty healthy subjects [10 male (M) and 10 female (F)] — mean age M=31 years (S.D.=8), F=27 years (S.D.=5); mean BMI M=24 (S.D.=2), F=21 (S.D.=5) — participated in a 4-day protocol. Measurements were made on days 1 and 4. Subjects were given paper and an EARS to log hourly subjective motivation to eat during waking hours. Food intake and meal times were fixed. Subjects were given a maintenance diet (comprising 40% fat, 47% carbohydrate and 13% protein by energy) calculated at 1.6×Resting Metabolic Rate (RMR), as three isoenergetic meals. Bland and Altman's test for bias between two measurement techniques found significant differences between EARS and paper and pen for two of eight responses (hunger and fullness). Regression analysis confirmed that there were no day, sex or order effects between ratings obtained using either technique. For 15 subjects, there was no significant difference between results, with a linear relationship between the two methods that explained most of the variance (r2 ranged from 62.6 to 98.6). The slope for all subjects was less than 1, which was partly explained by a tendency for bias at the extreme end of results on the EARS technique. These data suggest that the EARS is a useful and reliable technique for real-time data collection in appetite research but that it should not be used interchangeably with paper and pen techniques.

Nitrogen and phosphorus transformations in fixed-film biofilters subjected to aeration/no-aeration cycles

Despite recent developments in fixed-film combined biological nutrients removal (BNR) technology; fixed-film systems (i.e., biofilters), are still at the early stages of development and their application has been limited to a few laboratory-scale experiments. Achieving enhanced biological phosphorus removal in fixed-film systems requires exposing the micro-organisms and the waste stream to alternating anaerobic/aerobic or anaerobic/anoxic conditions in cycles. The concept of cycle duration (CD) as a process control parameter is unique to fixed-film BNR systems, has not been previously investigated, and can be used to optimise the performance of such systems. The CD refers to the elapsed time before the biomass is re-exposed to the same environmental conditions in cycles. Fixed-film systems offer many advantages over suspended growth systems such as reduced operating costs, simplicity of operation, absence of sludge recycling problems, and compactness. The control of nutrient discharges to water bodies, improves water quality, fish production, and allow water reuse. The main objective of this study was to develop a fundamental understanding of the effect of CD on the transformations of nutrients in fixed-film biofilter systems subjected to alternating aeration I no-aeration cycles A fixed-film biofilter system consisting of three up-flow biofilters connected in series was developed and tested. The first and third biofilters were operated in a cyclic mode in which the biomass was subjected to aeration/no-aeration cycles. The influent wastewater was simulated aquaculture whose composition was based on actual water quality parameters of aquacuture wastewater from a prawn grow-out facility. The influent contained 8.5 - 9:3 mg!L a111monia-N, 8.5- 8.7 mg/L phosphate-P, and 45- 50 mg!L acetate. Two independent studies were conducted at two biofiltration rates to evaluate and confirm the effect of CD on nutrient transformations in the biofilter system for application in aquaculture: A third study was conducted to enhance denitrification in the system using an external carbon- source at a rate varying from 0-24 ml/min. The CD was varied in the range of0.25- 120 hours for the first two studies and fixed at 12 hours for the third study. This study identified the CD as an important process control parameter that can be used to optimise the performance of full-scale fixed-film systems for BNR which represents a novel contribution in this field of research. The CD resulted in environmental conditions that inhibited or enhanced nutrient transformations. The effect of CD on BNR in fixed-film systems in terms of phosphorus biomass saturation and depletion has been established. Short CDs did not permit the establishment of anaerobic activity in the un-aerated biofilter and, thus, inhibited phosphorus release. Long CDs resulted in extended anaerobic activity and, thus, resulted in active phosphorus release. Long CDs, however, resulted in depleting the biomass phosphorus reservoir in the releasing biofilter and saturating the biomass phosphorus reservoir in the up-taking biofilter in the cycle. This phosphorus biomass saturation/depletion phenomenon imposes a practical limit on how short or long the CD can be. The length of the CD should be somewhere just before saturation or depletion occur and for the system tested, the optimal CD was 12 hours for the biofiltration rates tested. The system achieved limited net phosphorus removal due to the limited sludge wasting and lack of external carbon supply during phosphorus uptake. The phosphorus saturation and depletion reflected the need to extract phosphorus from the phosphorus-rich micro-organisms, for example, through back-washing. The major challenges of achieving phosphorus removal in the system included: (I) overcoming the deterioration in the performance of the system during the transition period following the start of each new cycle; and (2) wasting excess phosphorus-saturated biomass following the aeration cycle. Denitrification occurred in poorly aerated sections of the third biofilter and generally declined as the CD increased and as the time progressed in the individual cycle. Denitrification and phosphorus uptake were supplied by an internal organic carbon source, and the addition of an external carbon source (acetate) to the third biofilter resulted in improved denitrification efficiency in the system from 18.4 without supplemental carbon to 88.7% when the carbon dose reached 24 mL/min The removal of TOC and nitrification improved as the CD increased, as a result of the reduction in the frequency of transition periods between the cycles. A conceptual design of an effective fixed-film BNR biofilter system for the treatment of the influent simulated aquaculture wastewater was proposed based on the findings of the study.

Torsional Interaction Studies on a Power System Compensated by SSSC and Fixed Capacitor

In this paper, a static synchronous series compensator (SSSC), along with a fixed capacitor, is used to avoid torsional mode instability in a series compensated transmission system. A 48-step harmonic neutralized inverter is used for the realization of the SSSC. The system under consideration is the IEEE first benchmark model on SSR analysis. The system stability is studied both through eigenvalue analysis and EMTDC/PSCAD simulation studies. It is shown that the combination of the SSSC and the fixed capacitor improves the synchronizing power coefficient. The presence of the fixed capacitor ensures increased damping of small signal oscillations. At higher levels of fixed capacitor compensation, a damping controller is required to stabilize the torsional modes of SSR.

In vivo knockdown of the androgen receptor results in growth inhibition and regression of well-established, castration-resistant prostate tumours

Purpose: Progression to the castration-resistant state is the incurable and lethal end stage of prostate cancer, and there is strong evidence that androgen receptor (AR) still plays a central role in this process. We hypothesize that knocking down AR will have a major effect on inhibiting growth of castration-resistant tumors. Experimental Design: Castration-resistant C4-2 human prostate cancer cells stably expressing a tetracycline-inducible AR-targeted short hairpin RNA (shRNA) were generated to directly test the effects of AR knockdown in C4-2 human prostate cancer cells and tumors. Results:In vitro expression of AR shRNA resulted in decreased levels of AR mRNA and protein, decreased expression of prostate-specific antigen (PSA), reduced activation of the PSA-luciferase reporter, and growth inhibition of C4-2 cells. Gene microarray analyses revealed that AR knockdown under hormone-deprived conditions resulted in activation of genes involved in apoptosis, cell cycle regulation, protein synthesis, and tumorigenesis. To ensure that tumors were truly castration-resistant in vivo, inducible AR shRNA expressing C4-2 tumors were grown in castrated mice to an average volume of 450 mm3. In all of the animals, serum PSA decreased, and in 50% of them, there was complete tumor regression and disappearance of serum PSA. Conclusions: Whereas castration is ineffective in castration-resistant prostate tumors, knockdown of AR can decrease serum PSA, inhibit tumor growth, and frequently cause tumor regression. This study is the first direct evidence that knockdown of AR is a viable therapeutic strategy for treatment of prostate tumors that have already progressed to the castration-resistant state.

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn ma- neuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sen- sors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to main- tain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera.

Iteratively specified tree-based regression : theory and trip generation example

Focuses on a study which introduced an iterative modeling method that combines properties of ordinary least squares (OLS) with hierarchical tree-based regression (HTBR) in transportation engineering. Information on OLS and HTBR; Comparison and contrasts of OLS and HTBR; Conclusions.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Signalling layout for fixed-block railway lines with real-coded genetic algorithms.

Signalling layout design is one of the keys to railway operations with fixed-block signalling system and it also carries direct effect on overall train efficiency and safety. Based on an analysis to system objectives, this paper presents an optimization model with two objectives in order to devise an efficient signalling layout scheme. Taking into account the present railway line design practices in China, the paper describes steps of the computer-based signalling layout optimisation with real-coded genetic algorithms. A computer-aided system, based on train movement simulator, has also been employed to assist the optimisation process. A case study on a practical railway line has been conducted to make comparisons between the proposed GA-based approach and the current practices. The results illustrate the improved performance of the proposed approach in reducing signal block joints and shortening minimum train service headway.

A Heuristic algorithm for fixed train runtime

This paper proposes a train movement model with fixed runtime that can be employed to find feasible control strategies for a single train along an inter-city railway line. The objective of the model is to minimize arrival delays at each station along railway lines. However, train movement is a typical nonlinear problem for complex running environments and different requirements. A heuristic algorithm is developed to solve the problem in this paper and the simulation results show that the train could overcome the disturbance from train delay and coordinates the operation strategies to sure punctual arrival of trains at the destination. The developed algorithm can also be used to evaluate the running reliability of trains in scheduled timetables.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.