Artificial neural network for the second virial coefficient of organic and inorganic compounds: An ANN for B of organic and inorganic compounds

An artificial neural network (ANN) to estimate the second virial coefficient, valid for organic and inorganic compounds, is presented. First, we statistically analyzed 6,531 experimental points, belonging to 234 fluids, collected from literature. The data were investigated with a factor analysis approach to identify the most significant parameters that influence the second virial coefficient. The factor analysis, combined with physical considerations, allowed to find four (T_r, T_c, P_c, ω) or five (μ_r) parameters as input variables for the ANN, according to the specific chemical family. The architecture of the proposed multi-layers perceptron (MLP) neural network consists of one input layer with five input variables (T_r, T_c, P_c, ω, μ_r), one output layer with one neuron (B) and two-hidden-layers with 19 neurons each. We trained, validated and tested several configurations of the neural network to obtain this network topology that minimizes the deviations between experimental and calculated points. Results show that the ANN is able to calculate the second virial coefficient with greater accuracy (RMSE?=?29.38?cm³/mol) than that of correlations available in literature. To identify the outliers and applicability domain of the proposed MLP neural network, an outlier diagnosis based on the Leverage approach was performed. This analysis shows that the model is statistically valid.     

ELITE S2 – A Facility for Quantitative Human Movement Analysis on Board the ISS

Microgravity Science and Technology - This paper describes the activities for utilization and control of ELITE S2 on board the International Space Station (ISS). ELITE S2 is a payload of the...     

Measurements of projected areas of seated and standing people of southern Italy based on a statistical analysis

One of the most important components affecting the human thermal balance is represented by its radiative exchange with the surrounding surfaces. The projected area of the human body is an important parameter of these thermal exchanges. Unfortunately, although the anthropometric measures of people are characterized by significant differences among various populations, the experimental data currently available in the literature refers to a small group of people. Moreover, measurements are generally performed regardless of the statistical significance of the involved subjects with respect to the population to which they belong.In this study, a statistical study is introduced that is based on a large analysis of the anthropometric characteristics of the analysed population. Moreover, a new experimental procedure is applied to evaluate the projected area factor and the effective radiating area of a sample of people belonging to the population of southern Italy.The calculated projected area factors are fairly in accordance with those originally proposed by Fanger for standing people. For seated people, however, the experimental values of the present study show some differences from those of the literature. This study provided a tentative explanation for these discrepancies.     

A dynamic programming strategy to balance exploration and exploitation in the bandit problem

The K-armed bandit problem is a well-known formalization of the exploration versus exploitation dilemma. In this learning problem, a player is confronted to a gambling machine with K arms where each arm is associated to an unknown gain distribution. The goal of the player is to maximize the sum of the rewards. Several approaches have been proposed in literature to deal with the K-armed bandit problem. This paper introduces first the concept of “expected reward of greedy actions” which is based on the notion of probability of correct selection (PCS), well-known in simulation literature. This concept is then used in an original semi-uniform algorithm which relies on the dynamic programming framework and on estimation techniques to optimally balance exploration and exploitation. Experiments with a set of simulated and realistic bandit problems show that the new DP-greedy algorithm is competitive with state-of-the-art semi-uniform techniques.     

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Multi-step ahead forecasting is still an open challenge in time series forecasting. Several approaches that deal with this complex problem have been proposed in the literature but an extensive comparison on a large number of tasks is still missing. This paper aims to fill this gap by reviewing existing strategies for multi-step ahead forecasting and comparing them in theoretical and practical terms. To attain such an objective, we performed a large scale comparison of these different strategies using a large experimental benchmark (namely the 111 series from the NN5 forecasting competition). In addition, we considered the effects of deseasonalization, input variable selection, and forecast combination on these strategies and on multi-step ahead forecasting at large. The following three findings appear to be consistently supported by the experimental results: Multiple-Output strategies are the best performing approaches, deseasonalization leads to uniformly improved forecast accuracy, and input selection is more effective when performed in conjunction with deseasonalization.     

A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector

This paper deals with “The Enchanted Journey,” which is a daily event tour booked by Bollywood-film fans. During the tour, the participants visit original sites of famous Bollywood films at various locations in Switzerland; moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour. For operational reasons, however, two or more buses cannot stay at the same location simultaneously. Further operative constraints include time windows for all activities and precedence constraints between some activities. The planning problem is how to compute a feasible schedule for each bus. We implement a two-step hierarchical approach. In the first step, we minimize the total waiting time; in the second step, we minimize the total travel time of all buses. We present a basic formulation of this problem as a mixed-integer linear program. We enhance this basic formulation by symmetry-breaking constraints, which reduces the search space without loss of generality. We report on computational results obtained with the Gurobi Solver. Our numerical results show that all relevant problem instances can be solved using the basic formulation within reasonable CPU time, and that the symmetry-breaking constraints reduce that CPU time considerably.     

Confinement-shear lattice CSL model for fracture propagation in concrete

A previously developed lattice model is improved and then applied to simulations of mixed-mode crack propagation in concrete. The concrete meso-structure is simulated by a three-dimensional lattice system connecting nodes which represent the centers of aggregate particles. These nodes are generated randomly according to the given grain size distribution. Only coarse aggregates are taken into account. Three-dimensional Delaunay triangulation is used to determine the lattice connections. The effective cross-section areas of connecting struts are defined by performing a three-dimensional domain tessellation partly similar to Voronoi tessellation. The deformations of each link connecting two adjacent aggregate pieces are defined in the classical manner of Zubelewicz and Ba?ant in which rigid body kinematics is assumed to characterize the displacement and rotation vectors at the lattice nodes. Each strut connecting adjacent particles can transmit both axial and shear forces. The adopted constitutive law simulates fracture, friction and cohesion at the meso-level. The behavior in tension and shear is made dependent on the transversal confining strain, which is computed assuming a linear displacement field within each tetrahedron of Delaunay triangulation, and neglecting the effect of the particle rotations. A mid-point explicit scheme is used to integrate the governing equations of the problems. General procedures to handle the boundary conditions and to couple the lattice mesh to the usual elastic finite element mesh are also formulated. Numerical simulations of mixed-mode fracture test data are used to demonstrate that the model is capable of accurately predicting complex crack paths and the corresponding load-deflection responses observed in experiments.     

Energy-optimal collaborative file distribution in wired networks

The impact of the ICT sector in worldwide power consumption is an increasing concern, motivating the research community to devote an important effort to define novel energy efficient networking solutions. Despite file distribution is responsible for a major portion of the current Internet traffic, little effort has been dedicated to address the issue of its energy efficiency so far. Most of the previous literature focuses on optimizing the download time of file distribution schemes (e.g. centralized server-based or distributed peer-to-peer solutions) while it is yet unclear how to optimize file distribution schemes from the point of view of energy consumed. In this paper, we present a general modelling framework to analyze the energy consumption of file distribution systems. First, we show that the general problem of minimizing energy consumption in file distribution is NP-hard. Then, for restricted versions of the problem, we establish theoretical bounds to minimal energy consumption. Furthermore, we define a set of optimal algorithms for a variety of system settings, which exploit the service capabilities of hosts in a P2P fashion. We show that our schemes are capable of reducing at least 50 % of the energy consumed by traditional (yet largely used) centralized distribution schemes even when considering effects such as network congestion and heterogeneous access speed across nodes.