Miracle-dz/UniFAR-FTUs huggingface dataset:
System Identification Algorithm for a Large-Scale Offshore Wind Farm System

In a typical offshore wind farm, the turbines influence each other due to an aerodynamic phenomenon known as wake interaction. A wake is a trail of reduced wind speed generated behind the turbine as result of the exchange of kinetic energy between the incoming wind field and the rotor of the turbine. When a wind turbine is operating in the wake of another turbine, the power production of this turbine is reduced. Usually, the interaction between the turbines is not included on the modeling and the control of a wind farm. Typically, the power production of every turbine is maximized locally by setting the pitch angle and the rotational speed such that the maximum point of the power coefficient is reached. Even though the power is maximized locally, the total power production of the wind farm is not optimized. Therefore, new techniques to model the interactions between the turbines need to be developed. In addition, the obtained models should be flexible and suitable for controller synthesis. In this thesis, an output-error identification method for spatially interconnected systems that makes use of sequentially semi-separable (SSS) matrices is applied to the modeling of a row of wind turbines. The advantage of using this method in this case is twofold: Firstly, the use of the SSS parameterization permits to model naturally the interaction between the turbines and secondly, all the computations involved in the modeling process can be performed efficiently. In addition, the delays present in the wake interactions can be modeled by intercalating state space models that represent pure delays and that can also be placed in SSS structure. The disadvantage of the selection of an appropriate initial guess common in the output error approaches is overcame by obtaining a model in cascade via PO-MOESP subspace identification. A comparison with a centralized identification approach is also provided.
Fostering participaction in smart cities: a geo-social crowdsensing platform

This article investigates how and to what extent the power of collective although imprecise intelligence can be employed in smart cities. The main visionary goal is to automate the organization of spontaneous and impromptu collaborations of large groups of people participating in collective actions (i.e., participAct), such as in the notable case of urban crowdsensing. In a crowdsensing environment, people or their mobile devices act as both sensors that collect urban data and actuators that take actions in the city, possibly upon request. Managing the crowdsensing process is a challenging task spanning several socio-technical issues: from the characterization of the regions under control to the quantification of the sensing density needed to obtain a certain accuracy; from the evaluation of a good balance between sensing accuracy and resource usage (number of people involved, network bandwidth, battery usage, etc.) to the selection of good incentives for people to participAct (monetary, social, etc.). To tackle these problems, this article proposes a crowdsensing platform with three main original technical aspects: an innovative geo-social model to profile users along different variables, such as time, location, social interaction, service usage, and human activities; a matching algorithm to autonomously choose people to involve in participActions and to quantify the performance of their sensing; and a new Android-based platform to collect sensing data from smart phones, automatically or with user help, and to deliver sensing/actuation tasks to users.
A taxonomy of model-based testing

Model-based testing relies on models of a system under test and/or its environment to derive test cases for the system. This paper provides an overview of the field. Seven different dimensions define a taxonomy that allows the characterization of different approaches to model-based testing. It is intended to help with understanding benefits and limitations of model-based testing, understanding the approach used in a particular model-based testing tool, and understanding the issues involved in integrating model-based testing into a software development process. To illustrate the taxonomy, we classify several approaches embedded in existing model-based testing tools.
Handling Time-Warped Sequences with Neural Networks

Being able to deal with time-warped sequences is crucial for a large number of tasks autonomous agents can be faced with in real-world environments , where robustness concerning natural temporal variability is required, and similar sequences of events should automatically be treated in a similar way. Such tasks can easily be dealt with by natural animals, but equipping an animat with this capability is rather diicult. The presented experiments show how this problem can be solved with a neural network by ensuring slow state changes. An animat equipped with such a network not only adapts to the environment by learning from a number of examples, but also generalizes to yet unseen time-warped sequences.
PCA-based Reconstruction of 3D Face shapes using Tikhonov Regularization

Reconstructing a 3D face shape from a limited number of 2D facial feature points is considered as an ill-posed problem which can be solved using regularization. Tikhonov regularization is a popular method that incorporates prior information towards providing the existence of closed-form solutions which we obtain as a result of applying PCA, in order to solve the ill-posed problem. The common factors that generally affect Tikhonov regularization are the regularization matrix, the number of feature points, regularization parameters and noise. In this study we report our findings on how various factors influence the reconstruction accuracy based on a case study performed on the USF Human ID 3D database. Further, a statistical comparison between two Tikhonov regularization matrices viz., the identity matrix and the diagonal matrix comprising of the eigenvalues (eigenvalue matrix), has been performed. We found that, the reconstruction error can be reduced significantly by using the later one. Finally our study aids to determine the most feasible interval in conjunction with optimal regularization parameters which would lead towards achieving accurate and plausible solutions.
On the length of one-dimensional reactive paths

Motivated by some numerical observations on molecular dynamics simulations, we analyze metastable trajectories in a very simplecsetting, namely paths generated by a one-dimensional overdamped Langevin equation for a double well potential. More precisely, we are interested in so-called reactive paths, namely trajectories which leave definitely one well and reach the other one. The aim of this paper is to precisely analyze the distribution of the lengths of reactive paths in the limit of small temperature, and to compare the theoretical results to numerical results obtained by a Monte Carlo method, namely the multi-level splitting approach.
Steganography- A Data Hiding Technique

Steganography is the art of hiding information and an effort to conceal the existence of the embedded information. It serves as a better way of securing message than cryptography which only conceals the content of the message not the existence of the message. Original message is being hidden within a carrier such that the changes so occurred in the carrier are not observable. In this paper we will discuss how digital images can be used as a carrier to hide messages. This paper also analyses the performance of some of the steganography tools. Steganography is a useful tool that allows covert transmission of information over an over the communications channel. Combining secret image with the carrier image gives the hidden image. The hidden image is difficult to detect without retrieval. This paper will take an in-depth look at this technology by introducing the reader to various concepts of Steganography, a brief history of Steganography and a look at some of the Steganographic technique.
123 PATHOPHYSIOLOGY OF PARKINSON ’ S DISEASE

Parkinson’s disease (PD) is thought to affect more than 1 million people in the United States alone, 1 of every 100 individuals above the age of 55. In the two centuries since it was first described by James Parkinson, we have learned a great deal about the disorder. We have, for example, learned where the primary lesion is and what many of the clinical manifestations are. However, it has only been in the past few decades that insights have begun to emerge regarding the cause of the disease, and only now can one begin to see the possibilities of treatments emerging that will provide more than temporary symptomatic relief. Beginning with the Nobel Prize–winning work of Arvid Carlsson, which pointed to the loss of dopamine (DA) as the principal deficit in PD and to levodopa as a mode of pharmacotherapy, we have come to understand what fails in this disorder and, more recently, how we might correct that failure. Moreover, although Parkinson focused entirely on motor symptoms, we have come to realize that the disorder is much more complex and includes a panoply of psychiatric symptoms as well. The clinical features, course, and treatment of PD are presented in detail in Chapters 122 and 124; thus, for the purposes of this review of etiology and pathogenesis, we only briefly highlight the more important aspects of these topics, including those of a psychiatric nature. We then describe the pathology before turning to several promising leads with regard to the underlying etiology of the disorder.
Towards Identifying Usability and Security Features of Graphical Password in Knowledge Based Authentication Technique

Text-based passwords are ubiquitous authentication system. This traditional authentication system is well- known for its flaws in the aspects of usability and security issues that bring problems to users. Hence, there is a need for alternative mechanism to overcome these problems. Graphical passwords, which consist of clicking or dragging activities on the pictures rather than typing textual characters, might be the option to overcome the problems that arise from the text-based passwords system. In this paper, a comprehensive study of the existing graphical password schemes is performed. We compared and categorized these schemes into two groups; recognition-based scheme and recall-based scheme. We also list out several usability and security features for research continuity in this area.
Robust andTrend-following Student ’ s t-KalmanSmoothers ?

Two nonlinear Kalman smoothers are proposed using the Student’s t distribution. The first, which we call the T-Robust smoother, finds the maximum a posteriori (MAP) solution for Gaussian process noise and Student’s t observation noise. It is extremely robust against outliers, outperforming the recently proposed `1-Laplace smoother in extreme situations with data containing 20% or more outliers. The second, which we call the T-Trend smoother, is a MAP solver for a model with Student’s t-process noise and Gaussian observation noise. This smoother tracks sudden changes in the process model. A key ingredient of our approach is a novel technique to overcome the non-convexity of the Student’s t loss function. By exploiting the structure of the underlying dynamics, the computational effort per iteration grows linearly with the length of the time series. Convergence analysis is provided for both smoothers. Numerical results for linear and nonlinear models illustrate the performance of the new smoothers for both robust and fast tracking applications, including an underwater tracking application with real data.
A Mixed Reality-Based Exercise Program for Upper-Limb Post-Stroke Rehabilitation

However, most of the rehabilitation treatments are stopped one year after post-stroke, during the chronic phase [9]. Several researchers have shown in both animal and human studies that important variables in re-learning motor skills and in changing the underlying neural architecture are the quantity, duration and intensity of training sessions. Focal ischemic lesions in monkeys, similar to what occurs in a stroke, usually result in a loss of cortical territory in the motor area adjacent to the infarcted region. However, three-four weeks of intensive, repetitive, hand training prevented this loss and in some instances led to an expansion of this cortical region [4]. Mental practice, also known as " imagery " , is a rehabilitation tool that can stimulate motor image [7]. In this paper, we propose a set of exercises to be used in a mixed reality environment that promote the recovery of upper-limb motor skills in chronic stroke patients, who had a stroke more than one year before, and who exhibit upper-limb hemiparesis. The exercises are intended to provide chronic stroke patients the visuospatial information to induce a third person perspective motor image. The rest of the paper is organized as follows: Section 2 briefly presents related work. Section 3 reviews Mental Practice. The design and results of the experiments are then discussed in Section 4. Preliminary conclusions and future works are summarized in Section 5. A related work was presented in [6] and [4]. The researchers provided a virtual reality training of the hemiparetic hand of post-stroke patients. The paper [4] presents the virtual reality-based exercise program and preliminary studies performed on users with no hand deficits and with a user who had suffered a stroke but had nearly normal hand function. On the other hand, Abstract This paper describes a proposal of exercises for post-stroke rehabilitation of the upper-limb movements using mixed reality combined with mental practice. Physiotherapists induce patients' mental practices so that they execute the assigned tasks in the mixed reality environment. In the mixed reality environment, patients can visualize themselves and their surroundings, just like in a mirror. However, a virtual upper-limb is superimposed over their real paralyzed upper-limb. The set of proposed exercises include low complexity movements as shoulder infection, shoulder abduction, shoulder adduction, fist extension, and hand grasping as well as high complexity movements like reach and grasp a ball, drag it to the desired position and release it. We be …
The relationship between physical activity and symptoms of depression among adolescents

English The aim of this research was to explore the effects of physical activity (PA) on symptoms of depression among adolescents. The research examined the relationship between physical activity and symptoms of depression, the number of training sessions per week and symptoms of depression, and if participation in organized sports (structured or organized PA) proved to be better at reducing symptoms of depression than individual physical activity (unstructured PA). A simple random sample of 2000 participants, from the Icelandic Centre for Social Research and Analysis (ICSRA) was used for this research. The result showed that physical activity decreased symptoms of depression among adolescents. The more training sessions per week showed reduced symptoms for depression. Participation in organized sports, proved to be better than individual activity at reducing symptoms of depression. Abstract-Icelandic Tilgangur þessarar rannsóknar var að kanna áhrif hreyfingar á þunglyndiseinkenni unglinga. Kannað var hvort að hreyfing hafði áhrif á þunglyndiseinkenni, hvort munur væri á þunglyndiseinkennum miðað við fjölda hreyfingar á viku, og hvort íþróttaiðkun eða einstaklingsþjálfun væri líklegri til að draga úr þungyndiseinkennum. Rannsakandi notaði 2000 manna slembiúrtak frá gagnasafni Rannsóknar og greiningar við gerð rannsóknarinnar. Niðurstöður sýndu fram á að hreyfing dregur úr þunglyndiseinkennum hjá unglingum. Því oftar í viku sem hreyfing á sér stað, því minni eru þunglyndiseinkenni. Íþróttaiðkun dregur meira úr þunglyndiseinkennum heldur en eintaklingsþjálfun. Icelandic Tilgangur þessarar rannsóknar var að kanna áhrif hreyfingar á þunglyndiseinkenni unglinga. Kannað var hvort að hreyfing hafði áhrif á þunglyndiseinkenni, hvort munur væri á þunglyndiseinkennum miðað við fjölda hreyfingar á viku, og hvort íþróttaiðkun eða einstaklingsþjálfun væri líklegri til að draga úr þungyndiseinkennum. Rannsakandi notaði 2000 manna slembiúrtak frá gagnasafni Rannsóknar og greiningar við gerð rannsóknarinnar. Niðurstöður sýndu fram á að hreyfing dregur úr þunglyndiseinkennum hjá unglingum. Því oftar í viku sem hreyfing á sér stað, því minni eru þunglyndiseinkenni. Íþróttaiðkun dregur meira úr þunglyndiseinkennum heldur en eintaklingsþjálfun. PHYSICAL ACTIVITY AND SYMPTOMS OF DEPRESSION 4 The relationship between physical activity and symptoms of depression among
Asynchronous Multicast Push: AMP

We propose a new transport paradigm, called asynchronous multicast push (AMP) that leads to much more efﬁcient use of network bandwidth, to higher throughput, and to reduced server load. AMP decouples request and delivery for frequently requested data and uses multicast delivery. We derive quantitativelyby how much the server load and the network load is reduced by introducing an asyn-chronism between data request and data delivery.
Machine Learning, 1{27 () Learning with Non-uniform Class and Cost Distributions: Eeects and a Multi-classiier Approach

Many factors innuence a learning process and the performance of a learned classiier. In this paper we investigate the performance eeects of class distribution in the training set. We also study diierent methods of measuring performance based on cost models and the performance eeects of training class distribution with respect to the diierent cost models. Observations from these eeects help us devise a distributed multi-classiier meta-learning approach to learn in domains with skewed class distributions, non-uniform cost per error, and large amounts of data. One such domain is credit card fraud detection and our empirical results on real-world data indicate that our approach, to a certain degree of skewness in the distribution, can signiicantly reduce loss due to illegitimate transactions.
Tree diversity promotes insect herbivory in subtropical forests of south-east China

1. Insect herbivory can strongly affect ecosystem processes, and its relationship with plant diversity is a central topic in biodiversity–functioning research. However, very little is known about this relationship from complex ecosystems dominated by long‐lived individuals, such as forests, especially over gradients of high plant diversity.
Neurobiology for forensic psychologists

ABSTRACT The aim of this paper is to outline some of the parts of the brain to increase understanding of the aetiology of criminal behaviours. It goes without saying that any complete answer will encompass: evolutionary, genetic, biochemical, neuropsychological, and cognitive factors as well as social factors (familial and societal). Antisocial and social behaviours are underpinned by feeling, cognitions and actions, which are in turn, underpinned by the neurobiological actions in the brain. The daunting task of understanding the relations between brain function and offending is made potentially more tractable by the way in which the brain can be seen as being organised into discrete anatomical circuits, many of which have definable functions. The paper describes a number of these circuits in detail.
Frequency characterization of a 2.4 GHz CMOS LNA by thermal measurements

This paper presents a technique to obtain electrical characteristics of analog and RF circuits, based on measuring temperature at the silicon surface close to the circuit under test. Experimental results validate the feasibility of the technique. Simulated results show how this technique can be used to measure the bandwidth and central frequency of a 2.4 GHz low noise amplifier (LNA) designed in a 0.35 microns standard CMOS technology
Adding damping in power distribution systems by means of power electronic converters

The amount of non-linear and unbalanced loads (such as adjustable speed drives and personal computers) connected to the electric power system is steadily growing. As a result, the power quality i.e. the reliability of the energy supply and the quality of the voltage waveform, may be severely degraded. Especially in the case of resonances, severe voltage distortion can be the result. Both harmonic voltage and current distortion may cause many unfavourable effects on both the power system and the connected loads. Although complete compensation is only possible using true active filters, resistive shunt harmonic impedances (SHI) have been shown to provide a considerable reduction of the harmonic distortion. These impedances can be implemented using active power electronic devices which are controlled to synthesize a resistive load. Benefits are: no need to measure the polluting current of non-linear loads, effective for all harmonics and different resonance conditions, simple control strategy, and possible implementation as a secondary control function of active power supplies and distributed power inverters. In this paper, a practical implementation of a resistive SHI is proposed. A new control strategy for a full-bridge ac-dc converter has been implemented in order to achieve a programmable resistive input impedance for harmonics, independent of the input impedance for the fundamental component. The potential to damp a resonance in a power distribution system is demonstrated using an experimental setup. Providing extra damping into the power system is an interesting feature for power electronic loads as well as for converters used in distributed power generation
Paper Special Section on Knowledge-based Software Engineering High-volume Continuous Xpath Querying in Xml Message Brokers

SUMMARY The core technical issue in XML message brokers, which play a key role in exchanging information in ubiquitous environments, is processing a large set of continuous XPath queries over incoming XML streams. In this paper, a new system as an epochal solution for this issue is proposed. The system is designed to minimize the runtime workload of continuous query processing by transforming XPath expressions and XML streams into newly proposed data structures and matching them efficiently. Also, system performances are estimated both in terms of space and time, and verified through a variety of experimental studies, showing that the proposed system is practically linear-scalable and stable in terms of processing a set of XPath queries in a continuous and timely fashion.