Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised model predictive control of wastewater treatment plant

An optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard measurements. As it is impossible to efficiently control the plant by one universal control strategy under all possible influent conditions, it is proposed in the paper to on-line adapt the nonlinear MPC control strategy in order to best adapt the control actions to actual and predicted WWTP conditions. Adjusting the MPC control strategy is carried out by suitable manipulating the components of performance index and constraints. This process is supervised by Mamdani reasoning system. The supervised MPC controller performance was tested by simulations within large range of plant operating conditions and then compared with classic MPC without such mechanism. The simulation model of the benchmark WWTP utilizes ASM2d model.
Role of women in rural energy programmes: issues, problems and opportunities.

As the predominant sources of fuel are derived from biomass resources, women have a very intrinsic and symbiotic relationship with their surrounding natural resource system. However, due to a variety of reasons, they do not find a role for themselves in the management and control of the resources. Even in the government initiated programmes in the rural energy and environment sectors, there are hardly any mechanisms to incorporate a meaningful role for them in project planning and implementation. It is being recognised now that the lacklustre performance of interventions like the biogas and improved cookstoves programmes can be attributed, to a great extent, to this poor level of involvement and lack of ‘stake’ for the women in these programmes.
An ant colony optimization algorithm based on dynamic evaporation rate fitting

The study of swarm intelligence is more and more popular, much study have been done on swarm intelligence such as ACO (Ant Colony Optimization), and many applications also have been made in the field of combinatorial optimization. However, when solving combinatorial optimization problems, especially these problems with large scale, slow convergence and easy to fall into stagnation still restraint algorithm to be much more widely used. This paper presents the DERFACO (An ACO Algorithm Based on Dynamic Evaporation Rate Fitting) algorithm, using a mechanism of dynamic evaporation rate, which can achieve better balance between solution efficiency and solution quality, avoiding algorithm falling into local optimal. Experiments show that the DERFACO algorithm has better performance, its convergence rate increase by 12% or more. Furthermore, the DERFACO on other classic TSP instances also shows good performance.
Evidence on Relative Tax Burden of Taxpayers with Income from Employment in the Czech Republic

This paper presents the results of a comparative analysis of relative tax burden of taxpayers (natural persons) with income from employment in the Czech Republic from 1993 to 2009. Single, childless taxpayers with tax residency in the Czech Republic were chosen to represent this category of taxpayers. The amount of the tax burden was conceived as the sum of natural person income tax and the social and health insurance premiums paid by the taxpayer (employee), constituting in its nature and character a tax equivalent. The amount of these legally imposed payments was set with respect to the state valid and effective as of December 31st of the relevant year, in the case of the year 2009 with respect to the state as of June 30th. The results of the performed analysis prove gradual decrease in relative tax burden in the period of 1993–2009 for taxpayers of all income groups. However, the decrease cannot be characterized as uniform. The most marked decrease was identified with taxpayers in the upper income groups. The most significant change in the relative tax burden took effect in association with changes introduced in the Act on Income Taxes as of January 1st, 2008 when the progressive income tax of natural persons was replaced with a flat-rate tax and when changes were introduced to the concept of the partial income tax base calculations applicable to natural persons. The main contribution of this paper can be seen in the fact that the comparison encompasses the time interval covering the entire effective life of the Act on Income Taxes. It is also important that in view of the specified solution conditions, the relative tax burden values presented in the graphs can be understood as maximum values of the tax burden of taxpayers having income from employment.
A novel blind watermarking scheme based on neural networks for image

In this paper, a novel blind watermarking scheme based on the back-propagation neural networks (BPNN) for image is presented. First, the convolutional codes encoding is used to refine the watermark for increasing robustness of the scheme. BPNN is developed to memorize the relationships between the wavelet selected samples and a processed chaotic sequence. With wavelet domain of original image being divided into watermarking blocks, then several different BPNN models of selected watermarking blocks are trained simultaneously to form certain relationships, which are employed for embedding the coded watermark bit stream. Compared with conventional watermarking, the proposed scheme based on the trained BPNN models modifies only a small amount of image data such that the distortion on original image is imperceptible. Experimental results demonstrate the high robustness of the proposed scheme against common signal processing.
To Beta or Not to Beta: A Comparison of Historical Versus Fundamental Betas for Hedging Market Risk

Fundamental betas provide several conceptual advantages to historical betas--they reflect information on a timelier basis and are less likely to confuse noise for information. This paper revisits the advantages of using fundamental beta for hedging systematic risk in the U.S. Fundamental beta appears to be a more consistent measure for hedging market risk, particularly for investors who care about downside risk and tail risk.
Stability of autonomous vehicle path tracking with pure delays in the control loop

This paper presents a new method to analyze the stability of a general class of mobile robot path-tracking algorithms taking into account explicitly the computation and communication delays in the control loop. These pure delays are present in autonomous vehicles due to position estimation. The problem is analyzed by solving directly the transcendental characteristic equation that appears when the time delay is considered. The analysis has been done for straight paths and paths of constant curvature. The method has been applied to the pure pursuit path-tracking algorithm, one of the most widely used. The paper presents several tests with two different outdoor autonomous vehicles (ROMEO-3R and a computer controlled HMMWV), in spite of difficulties of practical experiments with real vehicles close to the stability limits. These tests pointed out how the predictions of the stability of the proposed methods obtained by using simple models are verified in practice with two different outdoor vehicles.
A novel method to compare converters for PV applications based on energy efficiency

A novel method for selecting the most suitable converter for photovoltaic (PV) panels is given in this paper. The innovations reside on the analysis of energy efficiency; where, in addition to the converter power efficiency, the extraction power efficiency and the energy power distribution are considered. It is shown that the conventional method of selecting the converter based on its power efficiency is not always accurate in terms of the harvested energy. Two interleaved flyback converters with different designs and control and switching strategies are compared; one is controlled by duty cycle and the other is controlled by frequency. The result of the conventional method of comparison suggests that the design controlled by frequency is about 2 % more efficient that the design controlled by duty cycle. However, the proposed method of the comparison shows that the design controlled by duty cycle delivers to the load 12.5 MJ more per year, that represents a 1.9 % increase in energy efficiency, showing that the conventional method is not the best in terms of the harvested energy.
Self-Adaptive Energy Saver

Currently one of the main areas of improvement of the buildings energy performance is the optimization of regulation systems and controlling the flow of energy. To this end, we propose an approach based on multi-agent systems in which the optimization is performed without prior knowledge about the dynamics of the building. We evaluate the developed multi-agent system on its learning ability and optimization of the set point during the night. We show that the result converges efficiently towards the optimum, previously determined by a professional building simulator. This approach is generic enough to be extended to many observable and checkpoints building without modification of the algorithms decision agents.
Comparison of Extraintestinal Pathogenic Escherichia coli Strains from Human and Avian Sources Reveals a Mixed Subset Representing Potential Zoonotic Pathogens

ABSTRACT Since extraintestinal pathogenic Escherichia coli (ExPEC) strains from human and avian hosts encounter similar challenges in establishing infection in extraintestinal locations, they may share similar contents of virulence genes and capacities to cause disease. In the present study, 1,074 ExPEC isolates were classified by phylogenetic group and possession of 67 other traits, including virulence-associated genes and plasmid replicon types. These ExPEC isolates included 452 avian pathogenic E. coli strains from avian colibacillosis, 91 neonatal meningitis E. coli (NMEC) strains causing human neonatal meningitis, and 531 uropathogenic E. coli strains from human urinary tract infections. Cluster analysis of the data revealed that most members of each subpathotype represent a genetically distinct group and have distinguishing characteristics. However, a genotyping cluster containing 108 ExPEC isolates was identified, heavily mixed with regard to subpathotype, in which there was substantial trait overlap. Many of the isolates within this cluster belonged to the O1, O2, or O18 serogroup. Also, 58% belonged to the ST95 multilocus sequence typing group, and over 90% of them were assigned to the B2 phylogenetic group typical of human ExPEC strains. This cluster contained strains with a high number of both chromosome- and plasmid-associated ExPEC genes. Further characterization of this ExPEC subset with zoonotic potential urges future studies exploring the potential for the transmission of certain ExPEC strains between humans and animals. Also, the widespread occurrence of plasmids among NMEC strains and members of the mixed cluster suggests that plasmid-mediated virulence in these pathotypes warrants further attention.
Psychotherapy participants show increased physiological responsiveness to a lab stressor relative to matched controls

Accumulating evidence indicates that psychotherapy participants show increased physiological responsiveness to stress. The purpose of the present study was to examine differences between individuals participating in outpatient psychotherapy and matched controls using an experimental design. Forty-two psychotherapy participants and 48 matched controls were assessed on cardiovascular and cortisol functioning at baseline, during the Trier Social Stress Test (TSST), and during a 20-min recovery period. Psychotherapy participants and matched controls did not differ at baseline or during the TSST on the physiological measures but psychotherapy participants had higher cortisol and heart rate (HR) during the recovery period. In regards to reactivity, cortisol increased during the recovery period for the psychotherapy participants but decreased for those in the matched control group. Psychotherapy participants experiencing clinically significant levels of distress displayed elevated systolic and diastolic blood pressure and HR during the TSST when compared to psychotherapy participants not experiencing clinically significant levels of distress. Overall, physiological reactivity to stress appears to be an important issue for those in psychotherapy and directly addressing this issue may help improve psychotherapy outcomes.
Determining inspection cost-effectiveness by combining project data and expert opinion

There is a general agreement among software engineering practitioners that software inspections are an important technique to achieve high software quality at a reasonable cost. However, there are many ways to perform such inspections and many factors that affect their cost-effectiveness. It is therefore important to be able to estimate this cost-effectiveness in order to monitor it, improve it, and convince developers and management that the technology and related investments are worth while. This work proposes a rigorous but practical way to do so. In particular, a meaningful model to measure cost-effectiveness is proposed and a method to determine cost-effectiveness by combining project data and expert opinion is described. To demonstrate the feasibility of the proposed approach, the results of a large-scale industrial case study are presented and an initial validation is performed.
Predictability Considerations in the Design of Multi-Core Embedded Systems ∗

Embedded systems with hard real-time constraints need sound timing-analysis methods for proving that these constraints are satisfied. Computer architects have made this task harder by improving average-case performance through the introduction of components such as caches, pipelines, out-of-order execution, and different kinds of speculation. This article argues that some architectural features make timing analysis very hard, if not infeasible, but also shows how smart configuration of existing complex architectures can alleviate this problem.
Quaternionic Multilayer Perceptron with Local Analyticity

A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons' states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of the network.
Indole Alkaloids from Catharanthus roseus: Bioproduction and Their Effect on Human Health

Catharanthus roseus is a medicinal plant belonging to the family Apocynaceae which produces terpenoid indole alkaloids (TIAs) of high medicinal importance. Indeed, a number of activities like antidiabetic, bactericide and antihypertensive are linked to C. roseus. Nevertheless, the high added value of this plant is based on its enormous pharmaceutical interest, producing more than 130 TIAs, some of which exhibit strong pharmacological activities. The most striking biological activity investigated has been the antitumour effect of dimeric alkaloids such as anhydrovinblastine, vinblastine and vincristine which are already in pre-, clinical or in use. The great pharmacological importance of these indole alkaloids, contrasts with the small amounts of them found in this plant, making their extraction a very expensive process. To overcome this problem, researches have looked for alternative sources and strategies to produce them in higher amounts. In this sense, intensive research on the biosynthesis of TIAs and the regulation of their pathways has been developed with the aim to increase by biotechnological approaches, the production of these high added value compounds. This review is focused on the different strategies which improve TIA production, and in the analysis of the beneficial effects that these compounds exert on human health.
Group Nearest Neighbor Queries for Fuzzy Geo-Spatial Objects

A geo-spatial object with non-deterministic boundaries and compositions is commonly known as a fuzzy geo-spatial object. The advancement of data capturing devices such as sensors and satellite imaging technologies enable us to identify fuzzy geo-spatial objects from a large and complex image of an area. The nearest neighbor (NN) query processing on fuzzy objects, which finds the nearest fuzzy object to the given query point, has been addressed recently. In this paper, we envision a new set of applications that require finding the nearest fuzzy geo-spatial object for a group of fuzzy geo-spatial query objects. For example, when an oil spill occurs at a sea, the primary concern of an emergency response planner is to find an environmentally sensitive area, e.g., port or harbor, that will be affected the most by the oil spill. To support such applications, in this paper, we propose a new query type, called a fuzzy group nearest neighbor (FGNN) query. Given a set of fuzzy geo-spatial data objects, and a group of fuzzy geo-spatial query objects, an FGNN query returns a fuzzy geo-spatial object that minimizes the aggregate distance to the group. To solve FGNN queries, we develop an efficient technique in this paper. Our extensive experimental study reveals the efficacy and efficiency of our proposed technique.
Improving Data Association Based on Finding Optimum Innovation Applied to Nearest Neighbor for Multi-Target Tracking in Dense Clutter Environment

— In this paper, a new method, named optimum innovation data association (OI-DA), is proposed to give the nearest neighbor data association the ability to track maneuvering multi-target in dense clutter environment. Using the measurements of two successive scan and depending on the basic principle of moving target indicator (MTI) filter, the proposed algorithm avoids measurements in the gate size of predicted target position that are not originated from the target and detects the candidate measurement with the lowest probability of error. The finding of optimum innovation corresponding to the candidate valid measurement increases the data association performance compared to nearest neighbor (NN) filter. Simulation results show the effectiveness and better performance when compared to conventional algorithms as Nearest Neighbor Kaman Filter (NNKF), Joint Probabilistic Data Association Algorithm (JPDA).
Effective Electromagnetic Parameters of Metamaterial Transmission Line Loaded With Asymmetric Unit Cells

In this paper, we propose the generalized extraction procedure for retrieval of the effective constitutive parameters for a metamaterial transmission line loaded with asymmetric unit cells. The asymmetric unit cell is replaced with a transmission line immersed in equivalent bianisotropic medium described by effective parameters ε, μ, and Zc, and bianisotropic parameters u and η. The proposed retrieval procedure is applied to novel dual-band unit cells and compared with the standard Nicolson-Ross-Weir (NRW) method that is originally developed for the symmetric unit cell and then extended to the asymmetric one using the averaged value of reflection coefficients. It has been shown that, in case of pronounced asymmetry, the NRW method gives only the exact value of refraction, but effective permittivity and permeability are considerably different from the exact values since they are calculated by means of the approximate value of characteristic impedance.
THE STRUCTURE OF DISCOURSE

This paper presents the basic elements of a computational theory of discourse structure that simplifies and expands upon previous work. By specifying the basic units a discourse comprises and the ways in which they can relate, an account of discourse structure provides the basis for an account of discourse meaning. The paper distinguishes three components of discourse structure: one linguistic, one intentional, and one attentional. The theory, although still incomplete, provides a basis for investigating the structure and meaning of discourse, as well as for constructing "discourse processing systems. "
Singularity-Free Reconfiguration of the 5-DOF Gantry-Tau Parallel Kinematic Machine

This paper presents a systematic approach based on Mixed Integer Linear Programming for finding a near optimal singularity-free reconfiguration path of the 5-DOF Gantry-Tau parallel kinematic machine. The results in the paper demonstrate that singularity-free reconfiguration (change of assembly mode) of the machine is possible, which significantly increases the usable workspace. The method has been applied to a full-scale prototype and the singularity-free path has been verified both in simulations and with physical experiments using real-time control of the prototype.
Comment on “Generalised Linear Dynamic Factor Models - An Approach via Singular Autoregressions”

While this paper makes an important contribution in a systems and control context, it is also a fascinating example of bi-directional contribution between that field, and the field of econometrics. More specifically, the genesis of the paper arises in economic and financial modeling scenarios where the dimension N of the vector of system measurements y t can be large, and possibly bigger than the number of observations of this vector T . For example, as noted in [1], y t may contain measurements of “different macro variables, returns on different assets, [and] data disaggregated by sector or region”. Importantly, models of this sort are likely to be of increasing importance in systems and control settings too as the demands for analyzing larger scale systems rises, particularly in relation to communication, transport and energy networks. Within economic and finance fields, this paper notes that various methods for estimating the parameters modeling such processes have been developed, with particular attention paid to exploiting structural aspects in order to restrict the dimension of the parameter space. One example is the frequency domain type approach in [1]. This paper carefully develops a new and efficient approach based on AR modeling and solving subsequent Yule–Walker equations, where the latter is not straightforward due to the “innovations” process being rank deficient. A distinctive feature is the significant depth of underpinning theory provided to support and develop the proposed approach. This draws heavily on concepts and results developed over many years in the systems and control community many of them by the first two authors. Hence while the problem has its original roots in econometrics and finance, it is highly relevant in a systems and control setting, and indeed as illustrated by this paper, the tools from that field can contribute substantially back into econometrics and related areas. The authors do not arrive at an AR modeling approach casually, and the paper contains a careful analysis of alternatives, such as ARMA modeling via a state-space description
Dynamically transparent window

In this paper, we present a case study of Dynamically Transparent Windows installed during a five weeks period in the facade of a major department store on a busy high street. The windows are fitted with so-called electro-chromatic foil that can change from opaque to transparent when an electric current runs through it. By using strips or rectangles of the foil, narrow bands on the façade interactively change and reveal what is on display in the store in order to draw the by-passers closer, and encourage them to explore the display. Our evaluation based on log-data, video observations, and in-situ observations points to a number of challenges concerning 1) Interaction issues related to the movement vector of pedestrians, 2) Behaviour and attention issues, and 3) Issues pertaining to the diversity of the situations and external conditions in the high street setting.