A computer program for time series forecasting using single and double exponential smoothing techniques

This paper presents a microcomputer program for time series forecasting. The program has been developed in GW-BASIC for Zenith 150 microcomputers which are IBM PC compatible. It utilizes Single exponential smoothing, Adaptive-response-rate single exponential smoothing, and Brown's double exponential smoothing methods to forecast the future values of a given time series. The program produces plots of the original time series and forecasted series as well as forecasting errors. It computes 90% and 95% confidence intervals for forecasted values and calculates the following statistics: Mean squared error, Mean absolute percentage error, Mean absolute error, Durbin-Watson statistic, and Theil's U statistic.     

Integration of remote measurement calibration with stateestimation-a feasibility study

The authors describe the integration of measurement calibration and state estimation methodologies for increasing the confidence level in a real-time database. The objectives are to improve performance of state estimators and to reduce the system engineering effort which goes into its installations and the related measurement calibrations. These objectives are accomplished by remotely minimizing the systematic errors and providing the state estimator with zero-mean and the actual standard deviation for each measurement. The state estimator is then able to suppress the spurious errors and furnish a dependable real-time database for the computer control of power systems. The approach was supported by experimental results carried on a 55 bus portion of an actual power system     

Leucine metabolism during chronic ethanol consumption

Chronic ethanol consumption is known to increase plasma concentrations of branched-chain amino acids (BCAA) in rats and man, but the mechanisms of this effect are not known. Chronic ethanol consumption may increase levels of BCAA by altering protein turnover and/or by affecting the oxidation of BCAA. These possibilities were investigated in rats pair-fed liquid diets containing either 0% or 36% of total calories as ethanol for 21 days. In the fed state, ethanol-treated rats had a plasma ethanol level of 20 +/- 5 mmol/L and twofold increases in BCAA concentrations in plasma. There were also significant increases (37% to 63%) in muscle, liver, and jejunal mucosa BCAA concentrations. Chronic ethanol consumption significantly increased whole-body rates (mumol/100 g/h) of leucine turnover (73.8 +/- 7.5 v 104 +/- 5.6, P < .01) and oxidation (12.0 +/- 1.7 v 17.7 +/- 1.1, P < .05). In contrast, it significantly decreased leucine incorporation (nmol/mg protein/240 min) into both muscle (0.61 +/- 0.07 v 0.35 +/- 0.05, P < .01) and liver (13.25 +/- 1.40 v 6.78 +/- 0.98, P < .01) proteins. Incorporation of leucine into the mucosal proteins of jejunum (17.42 +/- 1.42 v 15.85 +/- 1.90, P = NS) was not significantly altered by ethanol. These results suggest that reduced protein synthesis and/or increased protein breakdown may account for the elevated tissue BCAA concentrations in chronic ethanol consumption. The consequences of these increased tissue concentrations are increases in tissue oxidation and plasma concentrations of BCAA.     

Experiences Acquired in the Design of RoboCup Teams: A Comparison of Two Fielded Teams

Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. Effective agent interactions in such domains raise some of the most fundamental research challenges for agent-based systems, in teamwork, multi-agent learning and agent modelling. The RoboCup research initiative, particularly the simulation league, has been proposed to pursue such multi-agent research challenges, using the common testbed of simulation soccer. Despite the significant popularity of RoboCup within the research community, general lessons have not often been extracted from participation in RoboCup. This is what we attempt to do here. We have fielded two teams, ISIS97 and ISIS98, in RoboCup competitions. These teams have been in the top four teams in these competitions. We compare the teams, and attempt to analyze and generalize the lessons learned. This analysis reveals several surprises, pointing out lessons for teamwork and for multi-agent learning.     

Multilayer flavoured dynamic source routing in mobile ad-hoc networks

Dynamic source routing (DSR, introduced in 1996) is one of the most frequently used routing protocols for mobile ad-hoc networks (MANETs). Numerous MANET protocols were created based on DSR's algorithm. In addition to inheriting the overall performance specifications of DSR, these MANET protocols are designed to perform optimised for specific functionality. To name a few, these functionalities include: hierarchical routing, security-aware routing and multipath routing. Such flavoured DSR schemes (X-DSR) are often compared against the original DSR protocol through simulation results. The purpose of this survey is to first introduce DSR in detail, discuss most of the DSR flavours, point out their specific features, and to present a complete survey of the analyses given in the current literature against the original DSR protocol. Following this in-depth discussion, we introduce an X-DSR-aware management architecture, which utilises a multilayer scheme that imports parameters from different layers (network, data-link and physical) and performs current network condition matching compared to the closest pre-defined network condition groups. The output of such a match is the selection of the most optimal routing protocol, which satisfies most of the criteria of the predefined condition group.     

Optimization of biodiesel production process in a continuous microchannel using response surface methodology

We assessed the biodiesel production process in a continuous microchannel through preparation of a heterogeneous catalyst (CaO/MgO) from demineralized water plant sediment. This mixed oxide catalyst was used for transesterification of rapeseed oil as feedstock by methanol to produce biodiesel fuel at various conditions. A microchannel, utilized as a novel reactor, was applied to convert rapeseed oil into biodiesel in multiple steps. The effects of the process variables, such as catalyst concentration, methanol to oil volume ratio, n-hexane to oil volume ratio, and reaction temperature on the purity of biodiesel, were carefully investigated. Box-Behnken experimental design was employed to obtain the maximum purity of biodiesel response surface methodology. The optimum condition for the production of biodiesel was the following: catalyst concentration of 7.875 wt%, methanol to oil volume ratio of 1.75: 3, n-hexane to oil volume ratio of 0.575: 1, and reaction temperature of 70 °C.     

Nanoscale Optoregulation of Neural Stem Cell Differentiation by Intracellular Alteration of Redox Balance

Regulation of stem cell (SC) fate, a decision between self‐renewal and differentiation, is of immense importance in regenerative medicine and has been proven to be a powerful stimulus regulating many cell functions influencing the SC fate. This study uses triphenylphosphonium‐functionalized gold nanoparticles (TPP‐AuNPs) to explore the interplay of intracellular electromagnetic (EM) exposure and the SC fate. Localized EM waves are generated inside neural stem cells (NSCs) to stimulate TPP‐AuNPs (AuNPs), targeting the mitochondria through inducing reactive oxygen species and differentiating these cells into neurons. Following laser irradiation of TPP‐AuNPs‐transfected NSCs, their differentiation to neurons is monitored by tracing the relevant markers both at the genetic and protein levels. The electrophysiology technique is further used to examine the functionality of neurons. The results confirm that TPP‐AuNPs subjected to electromotive forces have the potential to regulate cellular fate, although further investigations are still required to shed light on the mechanisms underlying the interaction of EM‐stimulated TPP‐AuNPs on cellular fate to design highly adjustable cell differentiation and reprogramming methods.     

Information Maximization in a Linear Manifold Topographic Map

This article addresses the problem of unsupervised learning of multiple linear manifolds in a topology preserving neural map. The model finds simple linear estimations of the regions of the unknown data manifold. Each neuron of the map corresponds to a linear manifold whose basis and mean vectors and on- and off-manifold standard deviations must be learnt. The learning rules are derived based on competition between neurons and maximizing an approximation of the mutual information between the input and the output of each neuron. Neighborhood functions are also considered in the learning rules in order to develop the topology preserving property for the map. Considering two special density models for the input data, the optimal nonlinear input/output mappings of the neurons are found. Experimental results show a good performance for the proposed method on synthesized and practical problems compared with other relevant techniques.     

Photocarrier‐Induced Active Control of Second‐Order Optical Nonlinearity in Monolayer MoS2

Atomically thin transition metal dichalcogenides (TMDs) in their excited states can serve as exceptionally small building blocks for active optical platforms. In this scheme, optical excitation provides a practical approach to control light‐TMD interactions via the photocarrier generation, in an ultrafast manner. Here, it is demonstrated that via a controlled generation of photocarriers the second‐harmonic generation (SHG) from a monolayer MoS₂ crystal can be substantially modulated up to ≈55% within a timeframe of ≈250 fs, a set of performance characteristics that showcases the promise of low‐dimensional materials for all‐optical nonlinear data processing. The combined experimental and theoretical study suggests that the large SHG modulation stems from the correlation between the second‐order dielectric susceptibility χ⁽²⁾ and the density of photoexcited carriers in MoS₂. Indeed, the depopulation of the conduction band electrons, at the vicinity of the high‐symmetry K/K′ points of MoS₂, suppresses the contribution of interband electronic transitions in the effective χ⁽²⁾ of the monolayer crystal, enabling the all‐optical modulation of the SHG signal. The strong dependence of the second‐order optical response on the density of photocarriers reveals the promise of time‐resolved nonlinear characterization as an alternative route to monitoring carrier dynamics in excited states of TMDs.