Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal digital control of a laboratory-scale paper machine headbox

This paper describes the design of a multi-input multi-output (MIMO) digital-linear-quadratic-regulator (DLQR) control system for the headbox of a paper machine. The complete design procedure is described from development of a mathematical model of the nonlinear headbox system, through experimental identification of linear model, to demonstration of closed-loop system performance on a laboratory-scale mock-up of an actual headbox. The important role of computer-aided-design tools is illustrated using Matlab and associated toolboxes. The control algorithm is implemented on a personal computer running the Labtech Notebook control program. The controlled system satisfactorily controls set point changes in total pressure and water level, and rejects disturbances in feedwater pressure. The material presented in the paper is used in a senior level course in digital process control at the University of Idaho. The course is jointly offered by the chemical and electrical engineering departments.
Effect of Ivermectin on semen characteristics of Iraqi Awassi ram

The objective of this study was evaluation the effect of ivermcetin on semen quality and serum testosterone levels of Iraqi Awassi ram. Ten mature Awassi rams (aged 2.54 years and weighing 3744 ± 0.3 kg) were used in this study. Rams were divided randomly into 2 groups each group contain 5 animals; the first one consider as treatment which was sub cautiously injected with ivermcetin at dose 0.2 mg/ kg bw, the second group left as control group injected with physiological normal saline. Semen samples collected by using artificial vagina at 1 day prior to ivermcetin injection and after 1, 3, 5, 7, 14 days following semen volume, mass motility, individual motility, sperms concentration, percentage of live sperm, percentage of abnormal sperms and blood samples were taken for estimated serum testosterone levels at each times of collection. Result of this study shows significantly (P<0.05) decrease in semen volume, sperm concentration and serum testosterone levels of treatment group while percentage of mass and individual motility show no insignificantly differences after 3 days following ivermcetin injection and Sperm abnormalities increase significantly (P<0.05) in treatment group comparing with the control group. After 5 days following ivermcetin injection, Semen parameters and serum testosterone levels demonstrate no significant differences between control and treatment groups. It could be concluded it's not prefer be use animals for breeding at least 5 days following the ivermcetin injection due to its harmful effect on semen quality and serum testosterone level. ريثأت راقع شابكلل يونملا لئاسلا تافص ىلع نيتكمرفيلاا ةيقارعلا ةيساوعلا
Inductive power transfer to an electric vehicle-analytical model

The roadway powered electric vehicle (RPEV) system is a unique electric vehicle system that receives electric power by inductive coupling from an inductor buried beneath the road surface. The analytical model of the system that transfers power from the wayside to the vehicle battery and DC traction motor is analyzed. This model includes the roadway inductor, the vehicle-mounted pick up inductor, and the onboard circuitry for control/conditioning of the coupled power. The equivalent circuit model of the inductive power coupling system is derived. Based on this model, the electrical characteristics of the system are explained. Trade-offs in selecting system parameters are discussed. All test results have tended to confirm simulation results obtained using the analytical model. <<ETX>>
The Simulation Platform ParFlow

ParFlow [1–4] is an integrated hydrology model that simulates saturated and variably saturated subsurface flow in heterogeneous porous media. ParFlow is written mainly in C, with the exception of the land surface model CLM which is a FORTRAN 90/95 code. ParFlow is built using distributed MPI parallelism and suitable to solve large scale, high resolution problems. It provides a solver for the three dimensional Richards equation [5] based on a cell centered finite difference (FD) scheme on regular Cartesian meshes. Time integration is performed with an Euler implicit method. The resulting system of algebraic equations is solved by a Newton-Krylov nonlinear solver that employs a multigrid preconditioned conjugate gradient solver in the linear step. The non-linear solver and preconditioners are provided by the libraries KINSOL [6] and hypre [7], respectively. Visualization of output data sets is possible with VisIt [8]. To this end, the output should be written using the SILO format, which is available as direct output option when compiling the code against the external dependency SILO [9]. SILO is effectively a serial library, which implies that a workaround has to be activated to write output in parallel. With ParFlow, it is possible to divide the MPI processes into N groups and write a separate SILO file for each group. Within each group, the processes write to a single file, where one and only one process performs write access to the group’s file at any given time. Hence, I/O is serial within a group and parallel across groups. This technique is called Poor Man’s Parallel I/O (PMPIO). ParFlow also supports distributed output of data sets in a binary format, which can be translated to vtk or SILO formats using post-processing tools. Since these tools work in serial, the approach is not advised when the number of processes is large. The ParFlow code has been proved to execute on machines up to 32k processes (MPI ranks), and good parallel efficiency (without I/O) has been reported for uses up to 16k processes [10]. The version of ParFlow that we have been developing in the DFG SFB/TR32 project D8 can be run to the full size of JUQUEEN at 458k cores with good parallel efficiency [11]. The main change introduced in our modified version is the integration of the parallel adaptive mesh refinement library p4est [12, 13] as its new mesh manager.
Air Traffic Delay Prediction Based on Machine Learning and Delay Propagation

Li, Meng MS, Purdue University, May 2018. Air Traffic Delay Prediction Based on Machine Learning and Delay Propagation. Major Professor: Dengfeng Sun. Flight Delay creates significant problems in the current aviation system. Methods are needed to analyze the manner in which delay propagates in the airport networks. Traditional methods are inadequate to the task. This paper presented a new machine learning based air traffic delay prediction model that combined multi-label random forest classification and approximated delay propagation model. To improve the prediction performance, an optimal feature selection process is introduced and demonstrated to have better performance than directly using all the features of available datasets. Departure delay and late arriving aircraft delay are shown to be the most critical features for delay prediction. To utilize these two features, a delay propagation model is proposed as a link to connect them to build a chained delay prediction model. Given the initial departure delay, the chained model is demonstrated to have the ability to predict the flight delay along the same aircrafts itinerary. By updating the actual departure delay with the iteration number along with the itinerary, the model’s accuracy can be further improved. Our application results demonstrate the value of machine learning and delay propagation for analyzing and predicting the air traffic delay in daily operation.
HamleDT 3.0

HamleDT (HArmonized Multi-LanguagE Dependency Treebank) is a compilation of existing dependency treebanks (or dependency conversions of other treebanks), transformed so that they all conform to the same annotation style. This version uses Universal Dependencies as the common annotation style. Update (November 1017): for a current collection of harmonized dependency treebanks, we recommend using the Universal Dependencies (UD). All of the corpora that are distributed in HamleDT in full are also part of the UD project; only some corpora from the Patch group (where HamleDT provides only the harmonizing scripts but not the full corpus data) are available in HamleDT but not in UD.
DUPLICATED EFFECTS OF SOIL NONLINEARITY ON PORT ISLAND RECORDS by

Empirical Green’s function (EGF) method has been applied to the records at Port Island during the 1995 Hyogo-ken Nanbu Earthquake and it’s aftershocks to evaluate the nonlinear effects on the mainshock records with special attention to two distinguished phases which are estimated to represent direct S wave and reverberating S wave inside the basin. Kamae and Irikura’s [1998] source model has been adopted. The results can be summarized as follows. 1. Direct S phase during the mainshock can be successfully reproduced with EGF method by taking into account the nonlinear behavior of the local soft soil layers above GL-83m. 2. On the other hand, the second phase seems to have already lost approximately 60% of it’s amplitude before it’s incidence to Port Island due to nonlinearity. This loss of amplitude may be attributed to the non-linear soil behavior during it’s first reverberation on the free surface. 3. Nonlinear ground response analysis shows that this kind of amplitude reduction during reverberation can exist under certain condition.
An Image Fusion In Gradient Based Multi-focus Image Enhancement

A dynamic picture mix plot for infrared and unmistakable course of action in light of range target ID is proposed in this paper. Target acknowledgment framework is used to divide the source pictures into target and establishment areas. Particular mix rules are gotten independently in target and establishment territories. A limitedly dreary discrete wavelet change (LR DWT) methodology is familiar with finish move invariant multi-assurance depiction of each source pictures. Blend researches genuine picture progressions demonstrate that the proposed method is convincing and capable, which fulfills best execution over the non-particular mix technique.
Mode Effects in Free-list Elicitation

The growth of the Internet opens new possibilities for web-based data collection in cognitive anthropology. This study examines whether free-list data collected online are comparable to those collected with face to face interviews or with self-administered paper questionnaires. We collected free lists for two cultural domains in the United States: one diffuse (things that mothers do) and one relatively well defined (racial and ethnic groups). We selected a purposive sample of 318 university students and randomly assigned participants to provide free lists for one of these domains using a web-based survey, a face to face interview, or a self-administered paper questionnaire. All three modes identified the same set of salient concepts in each domain. Median list length per respondent varied across modes in response to a standard free-list question and to supplementary probes. For the well-defined domain of “racial and ethnic groups,” supplementary probes widened differences among modes; for the more diffuse domain of “things that mothers do,” probes erased evidence of mode effects. Collecting free lists online is viable but may yield different results depending on the study population and attributes of the cultural domains.
Localization of Planetary Exploration Rovers with Orbital Imaging : a survey of approaches

Owing to the rovers exploring the surface of Mars being assigned with ever more complex tasks, it is the autonomy of such operations that enables their effective planetary activities. An indicative case of the escalation in requirements is the upcoming Mars Sample Return mission (MSR), which is a joint effort of the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The mission involves a Sample Fetching Rover (SFR) to gather a previously deposited cache of soil that, eventually, will be directed towards Earth. With the aim to retrieve the cache and rendezvous with the Mars Ascent Vehicle (MAV), the rover should be apt to globally localize itself on the Martian surface. Due to the absence of Global Navigation Satellite System (GNSS) on Mars, the most suited approach is the blending of information stemming from ground rovers and orbital imagery. The scope of the paper in hand is to summarize the work delivered so far on the localization of space exploratory rovers based on such information.
HYPHEN

Narrative clinical records and biomedical articles constitute rich sources of information about phenotypes, i.e., markers distinguishing individuals with specific medical conditions from the general population. Phenotypes help clinicians to provide personalised treatments. However, locating information about them within huge document repositories is difficult, since each phenotypic concept can be mentioned in many ways. Normalisation methods automatically map divergent phrases to unique concepts in domain-specific terminologies, to allow location and linking of all mentions of a concept of interest. We have developed a hybrid normalisation method (HYPHEN) to handle concept mentions with wide ranging characteristics, across different text types. HYPHEN integrates various normalisation techniques that handle surface-level variations (e.g., differences in word order, word forms or acronyms/abbreviations) and lexical-level variations (where terms have similar meanings, but potentially unrelated forms). HYPHEN achieves robust performance for both biomedical academic text and narrative clinical records, and has the ability to significantly outperform related methods.
Practical fingerprinting system for images

This paper presents a feasible system for image fingerprinting. Two important problems of fingerprinting are the design collusion-secure codes and the watermarking strategies for the fingerprints. We address these problems by proposing hierarchical fingerprint codes and a content adaptive watermarking scheme. It is challenging to find a practical collusion-secure code for fingerprinting because of the trade-offs between the fingerprint code's length, its collusion resiliency, and the size of the customer base. Therefore, instead of pursuing a high-performance code, we construct a new fingerprint code by concatenating existing codes using a hierarchical structure. The resulting code is efficient in decoding, much shorter than existing codes for similar parameters, and thus practical for real systems. In the fingerprinting, the codes are often very long if the applicable colluder-resisting ability and large customer bases are needed. The resulting acute degradation of fingerprinted content may be unacceptable. Hence the long-length watermark must be appropriately embedded into images to preserve the image quality. We design a strength-decision algorithm, on the basis of neural networks, to adaptively embed the long-length fingerprints with suitable magnitudes into different image regions. This adaptive watermarking technique maintains the combination of robustness and imperceptibility without the effort of dealing with visual models. In addition, we analyze the disturbance due to collusion attacks on images and propose an optimization algorithm that can select better embedding positions to resist collusion attacks and preserve acceptable transparency of the watermark according to different multimedia contents. Experimental results show the high detection correctness of the traitor tracing. It implies that our fingerprinting system, constructed by applying a hierarchical fingerprint code to the content-adaptive watermarking scheme, is effective for multimedia application.
Tree Wrap-data Extraction Using Tree Matching Algorithm

In this paper, we develop a non-visual automatic wrapper to extract data records from search engine results pages which contain important information for computer users. Our wrapper consists of a series of data filter to detect and remove irrelevant data from the web page. In the filtering stages, we incorporate two main algorithms which are able to check the similarity of data records and to detect and extract the correct data region based on their component sizes. To evaluate the performance of our algorithm, we carry out experimental and deletion tests. Experimental tests show that our wrapper outperforms the existing state of the art wrappers such as ViNT and DEPTA. Deletion studies by replacing our novel techniques with state of the art conventional techniques show that our wrapper design is efficient and could robustly extract data records from search engine results pages. With the speed advantages, our wrapper could be beneficial in processing large amount of web sites data, which could be helpful in meta search engine development.
Exploring Linguistic Features for Deception Detection in Unstructured Text

Detecting deception in unstructured texts has many applications but faces serious obstacles. Recent research has shown that linguistic traces of deception can be extracted from texts, such as political speech, and a number of theoretically derived features have been linked to deception. In this paper, we explore methods to extract and select computationallyderived linguistic features in order to improve the performance of deception detection in political speech. We extract semantic features from different language tools and use feature selection techniques to select the optimal feature set. The selected features include both theoretically expected features (e.g., negative emotion tone) and empirically-derived features (e.g., narrative and cohesion). Using the selected features can significantly improve deception detection performance compared with a theoretical approach that uses a limited set of features.
PRELIMINARY DESIGN OF OPTIMAL COMBINED CYCLE POWER PLANTS THROUGH EVOLUTIONARY ALGORITHMS

Abstract. This paper is concerned with the technoeconomic optimization of investments in combined cycle gas turbine (CCGT) power plants. Three CCGT power plant design problems, with total power output in the range of [170, 200] MW , [360, 400] MW and [720, 800] MW , are analyzed and discussed. In each one of them, the gas turbine (GT) is selected from a list of models which are available in the marketplace and produce, used as a single or multiple units, ∼ 120MW , ∼ 260MW and ∼ 520MW , respectively. The constrained, multiobjective optimization is carried out through evolutionary algorithms; the design space consists of continuous and integer variables, where the latter correspond to the selection of the GT model from a database as well as the type of heat recovery steam generator (HRSG). Pareto fronts on the plant efficiency investment cost plane are plotted and compared with optimal designs based on preselected GT models. For each GT model, the design of the optimal HRSG is of particular importance; one-, twoand three-pressure systems, without or with reheat, are used.
Association between C-reactive protein and mortality in peritoneal dialysis patients : a meta-analysis

Objective: The aim of this study was to evaluate the association between C-reactive protein (CRP) levels and all-cause mortality and cardiovascular disease mortality in patients undergoing peritoneal dialysis (PD). Methods: A systematic literature search up to March 2016 was performed in PubMed, Web of Science and the Cochrane Library. Hazard ratio (HR) with 95% confidence interval (CI) for all-cause mortality and cardiovascular disease mortality was extracted from each study. The pooled analysis was performed using the random-effect model by Rev Man 5.3 software. Results: Eighteen studies on CRP involving a total of 3869 PD patients were included in this meta-analysis. The combined analysis revealed that CRP levels were significantly positively associated with all-cause mortality (HR 1.04, 95% confidence interval: 1.02-1.06, P=0.0003) and cardiovascular disease mortality (HR 2.54, 95% confidence interval: 1.08-5.94, P=0.03) in peritoneal dialysis patients. Furthermore, statistically significant heterogeneity was found. The results for subgroup analysis of geographic region, study type, sample size and CRP type were consistent with the result about CRP levels and all-cause mortality. Conclusions: Elevated level of CRP was significantly associated with higher risks of all-cause and cardiovascular disease mortality in PD patients. Early detection of CRP levels in peritoneal dialysis patients is likely to identify patients at increased risk of mortality.
Identification method of spam comments in microblog based on AdaBoost

In view of the existence of a lot of spam comments in microblog,a new method based on AdaBoost was proposed to identify spam comments. This method firstly extracted feature vectors which consisted of eight feature values to represent the comments,then trained several weak classifiers which were better than random prediction on these features via AdaBoost algorithm,and finally combined these weighted weak classifiers to build a strong classifier with a high precision. The experimental results on comment data sets extracted from the popular Sina microblogs indicate that the selected eight features are effective for the method,and it has a high recognition rate in the identification of spam comments in microblog.
The Frontier of Linearity in the Intellectual Capital Metaphor

The purpose of this paper is to demonstrate that linearity is a major limitation of the metaphor Knowledge as Capital. This metaphor proposed by Daniel Andriessen as a challenging debate for ECIC 2009 has been extremely fruitful in promoting knowledge as a new field of interest in economic research and praxis. Since Capital is a core concept of any economic activity, using it as a semantic source for the newly coined expression, Intellectual Capital, proved to be a winning idea. However, any metaphor highlights certain things and hides others. There are some semantic frontiers in the source domain which constitute its limitations. The purpose of this paper is to analyse the linearity property of the source domain, and to demonstrate that it constitutes a major limitation of the IC metaphor. We begin with the mathematical definition of a linear space, and then we analyse how this definition requirements, which are fulfilled within the source domain, cannot be fulfilled within the target domain. We are interested especially in the following requirements of the linear space: commutativity, associativity, distributivity and the application of the principle of superposition. The Knowledge domain does not satisfy any of these requirements which means that the target domain is strongly nonlinear. Although many authors have used these concepts of linearity and nonlinearity in connection with knowledge and intellectual capital, none of them undertook a systematic analysis of the basic properties of linear spaces and how they fit within the knowledge field. Linearity is strongly related to the measurable property of the source domain, and this operational connection explains why many methods proposed to measure knowledge and intellectual capital failed to produce good results. We shall extend our analysis to linear and nonlinear thinking patterns, showing how the frontier of linearity can impair managerial decisions. We hope that our work will stimulate new research aiming at using properly the nonlinearity property of the Knowledge field. Keyword: capital, knowledge, linearity, linear space, linear thinking, nonlinearity