Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of Individual Characteristics of Driving Behavior based on Hidden Markov Model

Drivers' individual difference is one of the key factors to influence the accuracy of driving behavior model. The accuracy of model should include the effect characteristics of individual difference on driving behavior. The overtaking process was the research object to study the individual characteristics of driving behavior. The operation data of accelerator and steering wheel of each driver was analyzed with the character of time series. Based on both of the operation data, hidden Markov model (HMM) was employed to model the individual characteristics of driving behavior. Two individual models were built for each driver, one trained from accelerator data and one learned from steering wheel angel data. The models can be used to identify different drivers and the accuracy can reach to 85 %. It proved that individual difference is one factor which cannot be ignored in driving behavior model, and HMM has effectiveness in modeling it. Copyright © 2014 IFSA Publishing, S. L.
The Importance of Network Recommendations in the Director Labor Market

Directors are more likely to obtain additional directorships or be promoted if the CEO and peer directors of their current board are well-connected. The impact of CEO and peer director connections is stronger for additional appointments and promotions at firms in the CEO’s and peer directors’ networks. CEO connections are particularly important for directors with a weaker labor market. There is no evidence that the appointments of referred directors are less well-received by the market than other appointments. Overall, connections are important in the director labor market. Access to additional networks provides strong incentives for directors to join corporate boards.
Digital Image Processing and Analysis

Whether for computer evaluation of otherworldly terrain or the latest high definition 3D blockbuster, digital image processing involves the acquisition, analysis, and processing of visual information by computer and requires a unique skill set that has yet to be defined a single text. Until now. Taking an applications-oriented, engineering approach, Digital Image Processing and Analysis provides the tools for developing and advancing computer and human vision applications and brings image processing and analysis together into a unified framework.Providing information and background in a logical, as-needed fashion, the author presents topics as they become necessary for understanding the practical imaging model under study. He offers a conceptual presentation of the material for a solid understanding of complex topics and discusses the theory and foundations of digital image processing and the algorithm development needed to advance the field. With liberal use of color through-out and more materials on the processing of color images than the previous edition, this book provides supplementary exercises, a new chapter on applications, and two major new tools that allow for batch processing, the analysis of imaging algorithms, and the overall research and development of imaging applications. It includes two new software tools, the Computer Vision and Image Processing Algorithm Test and Analysis Tool (CVIP-ATAT) and the CVIP Feature Extraction and Pattern Classification Tool (CVIP-FEPC). Divided into five major sections, this book provides the concepts and models required to analyze digital images and develop computer vision and human consumption applications as well as all the necessary information to use the CVIPtools environment for algorithm development, making it an ideal reference tool for this fast growing field.
Analysis of DNA transcription termination sequences of gene coding for phaC1 polymerase in Pseudomonas species

Problems related to the negative influence of petrochemicalderived plastic on global environment have generated interest in the development of biodegradable plastic polymers. Biopolymers are divided into three categories: chemically synthesized polymers, starch-based biodegradable plastics and polyhydroxyalkanoates The most commonly encountered microbial storage polymer is PHA. The last one attract more attention and interest from scientists and industrialists because they have similar physical and thermal properties with those of synthetic plastics. Polyhydroxyalkanoates (PHAs) are a class of natural polyesters produced as discrete granules and used as a storage material for carbon and reducing equivalents. For that reason the PHA have useful properties: they are biodegradable, thermoplastic, biocompatible, non-toxic, and are considered as a replacement for petrochemical polymers. The wide range of procaryotic organisms, including Gramnegative and Gram-positive bacteria, show the ability to synthesize PHAs from numerous carbon sources such as alkanoic acids, alcohol and alkanes (Poirier et al. 1995). The amount of polymer accumulated by bacteria can reach levels as high as 90% of their cell dry weight (Madison et al. 1999). With few exception, PHAs are synthesized when an essential nutrient such as nitrogen, phosphate, magnesium or oxygen is available in limiting concentrations and the carbon source is present in excess (Schlegel et al. 1961). Classification of PHAs is based on the number of carbon atoms in the polymer. Polyhydroxyalkanoates can consist of short-chain-length hydroxyalkanoic acids (PHASCL), medium-chain-length monomers (PHAMCL) or long-chain-length (PHALCL), depending on the bacterial strain that produces the polymer and the culture condition available to the bacteria. Medium-chain-length polyhydroxyalkanoates (mclPHAs), a group of PHAs with a monomer length of 6 to 12 carbon atoms, which are produced by Pseudomonas species, have attracted considerable attention in recent years because some of their functional groups can be modified by chemical reactions. Furthermore, due to its biocompatibility, biodegradability and thermo plasticity, mcl-PHAs are highly ABS TRACT
Division by zero, pseudo-division by zero, Zhang dynamics method and Zhang-gradient method about control singularity conquering

ABSTRACT In this paper, the division-by-zero (DBO) problem in the field of nonlinear control, which is traditionally termed the control singularity problem (or specifically, controller singularity problem), is investigated by the Zhang dynamics (ZD) method and the Zhang-gradient (ZG) method. According to the impact of the DBO problem on the state variables of the controlled nonlinear system, the concepts of the pseudo-DBO problem and the true-DBO problem are proposed in this paper, which provide a new perspective for the researchers on the DBO problems as well as nonlinear control systems. Besides, the two classes of DBO problems are solved under the framework of the ZG method. Specific examples are shown and investigated in this paper to illustrate the two proposed concepts and the efficacy of the ZG method in conquering pseudo-DBO and true-DBO problems. The application of the ZG method to the tracking control of a two-wheeled mobile robot further substantiates the effectiveness of the ZG method. In addition, the ZG method is successfully applied to the tracking control of a pure-feedback nonlinear system.
Accurate Real-time Complex Cutting in Finite Element Modeling

This paper presents a real-time method for enacting accurate cutting of thin materials while retaining the physical accuracy of the underlying deformable material model. Our primary contribution is to offer a flexible real-time solution that can allow accurate cuts, re-cuts, curved cuts, sectioning (cutting out) on a deformable FEM model. Further contributions include improved handling of mesh element resizing after cutting for increasing material stability while balancing such resizing against real-time requirements. In this manner, we can represent precise cut incision (which may be curved or irregular) by subdividing mesh elements locally (at the cut point) while negating inappropriate (ill-shaped) elements with real-time level computational overhead and so avoiding modeling instabilities efficiently. We present the results of our solution that show the accuracy of the cutting method and illustrate timings for our optimised approach demonstrating its real-time qualities.
Conception et réalisation d'une machine synchrone à double excitation : application à l'entraînement direct

Un nombre croissant d'industriels et d'organismes de recherche tentent de trouver des solutions technologiques innovantes permettant une meilleure gestion de l'energie. Les machines synchrones a double excitation (MSDE) sont parmi les solutions les plus interessantes qui ne cessent d'immerger dans cette perspective. Mon travail de these s'inscrit dans le cadre de la conception d'une MSDE destinee a l'entrainement electromecanique direct. Une MSDE a ete dimensionnee, realisee et testee. Un rapport de gain en vitesse de 3 a ete atteint ce qui est bon au regard des structures du meme type actuellement publiees dans la litterature. Le travail mene s'est d'abord oriente vers l'etude bibliographique de la problematique de la these (le vehicule electrique), le cahier des charges dimensionnant de sa motorisation et les differentes solutions envisageables pour l'entrainement direct. L'etude comparative de ces solutions nous a justifie le choix des MSDE en general et en particulier la structure proposee : MSDE de serie avec la bobine auxiliaire placee au rotor. Ensuite nous avons developpe les modeles analytiques (par reseaux de reluctances) d'une part et numerique par element fini couple a matlab/simulink d'autre part. Ces derniers ont ete utilises avec succes. Dans un deuxieme temps nous avons voulu etudier en grandeur nature la solution proposee et cela a travers la realisation d'un prototype de MSDE. Pour des raisons economiques nous avons juste realise le rotor sur mesure d'un stator que nous avons recupere d'une machine a induction dont la puissance est 5. 5kw. Les tests pratiques sont encourageants tant au niveau des parametres physiques qu'au niveau des performances du defluxage.
The Structuring of Creative Processes using GSS: A Framework for Research

Radical and discontinuous change is the order of the day in the 1990s. Organizations are seeking to improve their fit with a constantly changing environment through initiatives such as business process redesign (BPR) and total quality management (TQM). Getting people to think creatively is critical to the success of these change efforts. Group Support Systems (GSS) have emerged as a potential means of supporting and augmenting creativity in the modem team-based organization. GSS research, however, has largely ignored the nature (i.e., creativity) of ideas that are generated.This paper seeks to move GSS research on idea generation beyond its previously limited focus on the quantity of ideas generated when using GSS. Drawing on multiple theoretical perspectives and research streams--creativity and idea generation, Kirton's cognitive style, GSS, and adaptive structuration theory (AST)--we distinguish between two orthogonal dimensions for measuring creativity (of ideas, individuals, and creativity processes)--creativity level and paradigm-relatedness; identify and characterize fundamental structuring mechanisms present in creativity techniques and GSS that influence one or the other dimension; and explore the implications of the above for research, design, and the targeted deployment of GSS and creativity techniques in organizations.We develop a theoretical framework of creative processes that is independent of any available or yet unforeseen technologies and techniques. The framework allows researchers and designers to examine GSS and creativity techniques at a finer level of detail than before, thereby allowing a richer understanding of how they work. This improved understanding will help organizations develop and maintain environments that foster creativity in the work force.
ICT and IT Initiatives in Public Governance − Benchmarking and Insights from Ethiopia

Aim: The paper mainly aims to identify Benchmark Practices of ICT and IT initiatives in Public Governance, Specifically the Case of India and others. Also it attempts to describe the status quo of ICT and IT initiatives in Public Governance in Ethiopia and assess the impact of ICT / IT initiatives on Public Sector Reforms. Research Methodology: To assess the Global practices of ICT and IT enabled Public Governance the paper has adopted descriptive and qualitative approach. To describe the status quo of ICT and IT initiatives in Public Governance in Ethiopia and assess the impact of ICT / IT initiatives on Public Sector Reforms a mixed mode approach is adopted using secondary data (literature), qualitative and quantitative data. 15 Face-face In-Depth Interviews were conducted over a time period of 6 weeks, with various stakeholders of Public Governance with open ended questions on ICT / IT initiatives and public sector reforms in Ethiopia. In addition, a quantitative study using questionnaire (Sample size = 412, Cronbach’s α = 0.565) was also conducted by convenient sampling. Findings: Some of the innovative ICT /IT based Global Benchmark E-Governance Services includes, EEmployment Services, GIS based Emergency Assistance, Integrated Social Assistance System, Open government data, etc. The face-face in depth interviews revealed major issues like high levels of Corruption, non-transparency, lack of skilled manpower in ICT/IT domain, low levels of literacy, cultural and language barriers, etc. In the evolved linear regression model from the questionnaire survey, it indicates that the model best explains the impact of ICT/IT initiatives (Independent variable) on the Public sector reforms (dependent variable) by nearly 50%. (R=.701, R Square = 0.492, F=65.387, Sig = .000).
Oxygen Isotope Fractionation in the System Dolomite-Calcite-Carbon Dioxide

Oxygen isotopes were equilibrated between carbon dioxide and calcite at four temperatures in the range 350� to 610�C and between carbon dioxide and dolomite at 350� and 400�C. Carbon of unusual isotopic composition was used as a tracer to demonstrate the nature and extent of the exchange process. Extrapolation of these data at lower temperatures indicates that at 25�C dolomite is enriched in oxygen-18 by 6.8 per mil with respect to calcite. This result indicates that those natural dolomite-calcite assemblages which show very small fractionations were not formed in isotopic equilibrium.
Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination

Model errors are inevitable in any prediction exercise. One approach that is currently gaining attention in reducing model errors is by combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictions. A new dynamic approach (MM‐1) to combine multiple hydrological models by evaluating their performance/skill contingent on the predictor state is proposed. We combine two hydrological models, “abcd” model and variable infiltration capacity (VIC) model, to develop multimodel streamflow predictions. To quantify precisely under what conditions the multimodel combination results in improved predictions, we compare multimodel scheme MM‐1 with optimal model combination scheme (MM‐O) by employing them in predicting the streamflow generated from a known hydrologic model (abcd model orVICmodel) with heteroscedastic error variance as well as from a hydrologic model that exhibits different structure than that of the candidate models (i.e., “abcd” model or VIC model). Results from the study show that streamflow estimated from single models performed better than multimodels under almost no measurement error. However, under increased measurement errors and model structural misspecification, both multimodel schemes (MM‐1 and MM‐O) consistently performed better than the single model prediction. Overall, MM‐1 performs better than MM‐O in predicting the monthly flow values as well as in predicting extreme monthly flows. Comparison of the weights obtained from each candidate model reveals that as measurement errors increase, MM‐1 assigns weights equally for all the models, whereas MM‐O assigns higher weights for always the best‐performing candidate model under the calibration period. Applying the multimodel algorithms for predicting streamflows over four different sites revealed that MM‐1 performs better than all single models and optimal model combination scheme, MM‐O, in predicting the monthly flows as well as the flows during wetter months.
SHARING THE RISK OF INNOVATIVE INVESTMENT: ASSESSING THE EFFECT OF A NEW EUROPEAN FINANCING INSTRUMENT

Access to finance is a key driver of business activities. It can help firms to grow and innovate. However, due to market failures innovative firms are usually more financinally constrained. To improve access to financing for risky but excellent R&D and innovation investment projects, a new debt-financing instrument called “Risk Sharing Finance Facility” was created in 2007, by a joint initiative of the European Commission and the European Investment Bank. Based on a macro-economic analysis, the aim of the paper is to assess the effect of this new debt-financing instrument on enhancing private R&D expenditure. The database used covers the 28 Member States of the European Union in the period 2007-2016. Private R&D decision is estimated by a function of output growth and several R&D policy instruments. The methodological approach is based on a fixed effect model with control function method in order to correct for endogenous bias of Risk Sharing Finance. The results reveal a positive and significant effect of the new EU policy financing instrument on Private R&D expenditure and its rate of return seems to be higher than that of grants or subsidies. Furthermore, in countries where government funding for private R&D expenditure is above the average, the effect of Risk Sharing Finance shows a lower marginal effect. No evidence of significant differences concerning the size of the effect of the new debt-financing instrument is found when differentiating the level of R&D tax incentives.
Involuntary Resettlement as an Opportunity for Development

The rebuilding of livelihoods in the involuntary resettlement is commonly based on providing compensation to those who are displaced along with the creation of employment and income opportunities to sustain their livelihoods. Unlike rural resettlement, urban resettlement is very complex as it involves providing business opportunities, urban-based employment and income. The article examined the resettlement of displaced families affected by Tehri Hydro Power Project by constructing an entirely new town ‘New Tehri Town’ (NTT) by using impoverishment risks and reconstruction (IRR) framework developed by Cernea (1997, World Development, 25(10), 1569–1587). The result shows that project-affected families (PAFs) are better off in NTT in terms of community amenities, income and employment opportunities and in terms of increase in value of houses, but traditional employment opportunities have been lost, they have to search for new jobs and livelihoods. The R&R policies in urban areas should focus on improving skill sets of the people along with increased income and employment opportunities through the development of market and business opportunities.
The Impact of Dry-Land Sprint Start Training on the Short Track Speed Skating Start

Abstract Haug, WB, Drinkwater, EJ, Cicero, NJ, Barthell, JA, and Chapman, DW. The impact of dry-land sprint start training on the short track speed skating start. J Strength Cond Res 33(2): 544–548, 2019—This investigation sought to determine the effects of dry-land sprint start training on short track speed skating (STSS) start performance. Nine highly trained short track athletes completed a control period of normal STSS training followed by a 4-week training intervention. Before and after the control and intervention periods, athletes performed 3 electronically timed dry-land and on-ice 14.43 m maximal sprint start efforts. The intervention consisted of 2 sprint sessions per week consisting of 9 electronically timed 14.43 m dry-land sprint starts in addition to normal STSS training. The control period resulted in no substantial change in on-ice start performance (mean &Dgr;: −0.01 seconds, 95% confidence limit [CL]: −0.08 to 0.05 seconds; effect size [ES]: −0.05; trivial); however, a small change was observed in dry-land start performance (mean &Dgr;: −0.07 seconds, 95% CL: −0.13 to −0.02 seconds; ES: −0.49). After brief specific dry-land sprint start training, a small improvement was observed in both on-ice (Mean &Dgr;: −0.07 seconds, 95% CL: −0.13 to −0.01 seconds; ES: −0.33) and dry-land (Mean &Dgr;: −0.04 seconds, 95% CL: −0.09 to 0.00 seconds; ES: −0.29) start performance. This investigation suggests that STSS start performance can be improved through a brief dry-land sprint start training program.
Computation of an odd-length DCT from a real-valued DFT of the same length

The discrete cosine transform (DCT) is often computed from a discrete Fourier transform (DFT) of twice or four times the DCT length. DCT algorithms based on identical-length DFT algorithms generally require additional arithmetic operations to shift the phase of the DCT coefficients. It is shown that a DCT of odd length can be computed by an identical-length DFT algorithm, by simply permuting the input and output sequences. Using this relation, odd-length DCT modules for a prime factor DCT are derived from corresponding DFT modules. The multiplicative complexity of the DCT is then derived in terms of DFT complexities. >
Magnetic Flux Analysis of the EAST Vertical Field

The relation between vertical field B<sub>z</sub> and normalized plasma density to the current n̅<sub>e</sub>/I<sub>p</sub> on Experimental Advanced Superconducting Tokamak (EAST) is derived and the quasi-linearity between them is found in the flat-top phase of the elongated plasma current. The poloidal plasma pressure ratio β<sub>p</sub> is formulated to be proportional to n<sub>e</sub>T<sub>e</sub>, the product of electron density ne and temperature T<sub>e</sub>. Thus β<sub>p</sub> can be enhanced significantly by compressing the plasma to its outboard boundary by inserting a set of vertical field coils in the EAST vacuum chamber for highly shaped plasma, as suggested by Li and Gourdain. The additional vertical field will work under pulse mode in the flat-top phase and produce the horizontal compression field to improve n<sub>e</sub> and T<sub>e</sub>, and then realize a high β<sub>p</sub> on EAST. Poynting's theorem method is used for calculating the flux and evaluating the volt-second consumption in the EAST discharges. The analysis results show that the external flux is basically equal to the surface flux and only less than 10% of the total flux is consumed in resistive dissipation in typical EAST shots.
Relaxed Oracles for Semi-Supervised Clustering

Pairwise "same-cluster" queries are one of the most widely used forms of supervision in semi-supervised clustering. However, it is impractical to ask human oracles to answer every query correctly. In this paper, we study the influence of allowing "not-sure" answers from a weak oracle and propose an effective algorithm to handle such uncertainties in query responses. Two realistic weak oracle models are considered where ambiguity in answering depends on the distance between two points. We show that a small query complexity is adequate for effective clustering with high probability by providing better pairs to the weak oracle. Experimental results on synthetic and real data show the effectiveness of our approach in overcoming supervision uncertainties and yielding high quality clusters.