Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Runout on the Chatter Frequencies of Milling Processes

A mechanical model of a 2 DoF milling process with static and dynamic considerations for runout is presented. The corresponding mathematical model is a delay differential equation with periodic coefficients. A regenerative time delay equal to the tooth passing period is applied, and the period of the coefficients that account for the tool rotation is equal to the tool rotation period; that is, the principal period of the system is a multiple of the time delay as opposed to the typical modeling assumption (without runout) of the principal period being equivalent to the time delay. Stability analyses are performed and chatter frequencies are determined. It is shown that additional peaks arise in the chatter spectrum due to the runout. Stable machining and period 1, period 2 and quasi-periodic chatter cases are investigated and the structure of the frequency peaks in the corresponding spectra are explained.
ii Biography

Wilson, Dylan Garrett. An Empirical Study of the Tacit Knowledge Management Potential of Pair Programming. (Under the direction of Laurie Ann Williams.) This work describes an experiment comparing knowledge sharing in two distinct team structures. Given the increasing importance of knowledge in the workplace, especially software engineering, we are interested in paradigms that can assist in knowledge management. To this end, we conducted an experiment to determine how the paired or solo programming model affects knowledge sharing during a software project. We show a pattern of results that suggest pair programming has a positive effect on knowledge sharing. We also find development time is somewhat higher when using paired programming, but product quality is unaffected by programming method though these results are not statistically significant. An Empirical Study of the Tacit Knowledge Management Potential of Pair Programming
ANALYSIS OF DYNAMIC-CONTROLLED ROUND JET USING POD AND DMD

Jets are the most basic flow used in industrial field and are widely used for heating, cooling, mixing. Recently, the improvement of mixing efficiency is required in order to downsize many industrial equipments and upgrade their performance. In the case of jets, their characteristic, such as the diffusion, depends on the inlet condition. Therefore, by controlling jet to give appropriate inlet conditions, the mixing efficiency can be improved. Thus far previous studies have mainly investigated excitation control associated with the instability of jets. However, in our previous study, as a new method we proposed vector control to enhance mixing or diffusion of free jets and have found its characteristics [1]. In this study, we focus on the vector control in which an inflow direction is rotating around the streamwise direction. In order to investigate the performance of the proposed method, the DNS of axisymmetric jet under the vector control are conducted and its structures are visualized; the mixing efficiency based on a mixing measure are quantified; further to make clear the reason for the mixing enhancement, the SPOD(snapshot proper orthogonal decomposition) [2] and the DMD (dynamic mode decomposition) method [3] are applied.
RADIATION EXPOSURE IN UNDERGROUND LOW ACTIVITY RADIOACTIVE WASTE REPOSITORY

L.C. TUGULAN1,∗, FELICIA M. DRAGOLICI2, GIANINA CHIROSCA1, A.V. CHIROSCA1, O.G. DULIU3,† 1University of Bucharest, Doctoral School for Physics, 405, Atomistilor str. , P.O. Box MG-11, RO 077125 Magurele (Ilfov), Romania 2Horia Hulubei National Institute for Physics and Nuclear Engineering, Radioactive Waste Management Department, 30, Reactorului str. , P.O. Box MG-06, RO 077125 Magurele (Ilfov), Romania 3University of Bucharest, Department of Structure of Matter, Earth and Atmospheric Physics and Astrophysics, 405, Atomistilor str. , P.O. MG-11, RO 077125 Magurele (Ilfov), Romania E-mail: o.duliu@fizica.unibuc. ro
Process of Developing a Mechanistic-Empirical Asphalt Pavement Design System for California

Mechanistic-Empirical (ME) asphalt pavement design systems have two components: a mechanistic model for calculating the critical primary responses (stresses, strains, and displacements) in the pavement, and empirical models which relate the calculated responses to the pavement distress or performance, in terms of cracking, rutting, and surface roughness. When developing an ME design system it is of utmost importance to pay considerable attention to both of these components. This paper describes the process of developing an effective flexible pavement design system, based on the authors’ experience from development of the flexible pavement design system known as CalME, for the California Department of Transportation (Caltrans). This paper also outlines the process used in developing both the primary response model and distress prediction models (fatigue cracking, rutting, and roughness) based on the incremental-recursive damage approach of the California ME asphalt pavement design system. The paper also presents the benefits of considering the mechanistic and empirical components separately, and using the two types of accelerated pavement testing facilities (Heavy Vehicle Simulator and test tracks) in the mechanistic model validation and distress prediction calibration efforts.
Data Provenance Survey Based On It ' s Applications

Data provenance is defined as the origin and process history of a derived data item, which is becoming increasingly important for scientific research work. Although provenance can be very valuable for applications, research on data provenance is on its beginning and there is still a series of work that needs to be done. In this paper, some categories, which are provenance granularity, data granularity, data status, provenance computing, semantics of provenance, provenance storage and applications, are proposed to classify and analyze present provenance techniques. In this work we introduce a provenance classification for different applications based on proposed categories, to help the researchers in this field to understand the existing problems and the current challenges and how to enable the current techniques for solving these challenges.
Thermal Emmisivity Coeficient of Comercial Selective Coating (Tinox) Measured by Photothermal Radiometry and Photoacustic Spectroscopy Techniques

In this paper photothermal radiometry (PTR) and photoacoustic (PA) spectroscopy techniques a long with a thermal waves propagation model for a layered system [1], have been used to determinate the thermal emissivity of a commercial selective coating (TiNOX) [2] deposited on aluminum and copper foils. PA measurements were made using a modified conventional Rosencwaig cell in which the sample closes the cell on one side and on the other by a transparent window, through which the coating is illuminated by the modulated laser beam at 808nm and with a spot of 5mm. The temperature variations in the air inside the PA cell were detected using an electret microphone coupled to the cell [3]. The PTR system consists of a modulated laser, at 808nm and with a spot of 5mm that impinges directly on the coating, as a consequence the samples heats periodically and the radiation emitted is collected by a couple of parabolic mirrors and sent into a HgCdTe sensor. Both PA and PTR measurements were performed in the range from 5 to 2000Hz. The PA (PTR) signal was normalized with respect to the PA (PTR) signal of the respective substrate. Given that the substrate is very thick compared with the selective coating layers, using the 1-D model for describing the thermal wave (TW) generation on sample surface and its subsequent propagation, it is shown that the normalized PA and PTR signals do not depend on the thermal properties of the layers, but only on the optical and in the light into heat efficiency. Based on this method, and using both the PA and PTR normalized signals, it is shown that the emissivity of the selective coating can be obtained [4]. It is also shown that this procedure can also provide the thermal emissivity for temperatures above room conditions and up to 60 C. In this case the sample is maintained at constant temperature using a controlled Peltier cell.
MARKETPLACES BASED ON THE EFFORT-ACCURACY CO-EXISTENCE FRAMEWORK

With the increasing prosperity of online marketplaces, millions of items are available on a single platform. Due to the limited cognitive capacity of human beings, consumers make purchase decisions in a way that balances both effort and accuracy, as contended by the effort-accuracy trade-off (EATO) framework. However, we propose that the rich functionality of online decision support aids (DSAs), namely image-based searching, cross-platform comparison and collocation recommendation, can first simplify consumers’ information processing in terms of problem identification, alternative generation and product evaluation. DSAs can then help consumers achieve a high level of accuracy in the decision elicitation and making process with minimal effort. We refer to this as effort-accuracy coexistence (EACE) that highlights the non-inversed relationship between effort and accuracy as well as the extended cognitive boundary in consumers’ purchase decision making. We plan to validate the conceptual model using experiments with online buyers. The proposed methodology and implications are discussed in this research-in-progress paper.
An Interactive Review of Object Motion Detection, Classification and Tracking Algorithms Related to Video Analysis in Computer Vision

During the past three decades, a number of moving objects’ detection, classification and tracking methods have been reported in the literature. This chapter presents a review of object motion detection, classification and tracking algorithms related to video analysis in computer vision. It also presents the studies pertaining to vehicle motion detection, classification, and tracking. Furthermore, the major strengths and weaknesses of these systems are reviewed. In general, detection, classification, and tracking are considered distinct areas of research. Nonetheless, for moving objects’ tracking purposes, the detection of movement and classification of candidate objects are essential in most cases.
Distribution of the Genetic Diversity of Pinus ayacahuite ( Ehrenberg ) at the Communal Forest of Totonicapán , Guatemala

The genetic diversity of Pinus ayacahuite from six stands at the Communal Forest of Totonicapan (Guatemala) was evaluated with chloroplast microsatellite markers. The analysis along an altitudinal cline showed a diverse pattern in both genetic diversity and genetic differentiation estimates. Three areas were established: 1) a lower area, located near human establishments that includes a forest nursery, is characterized by the highest genetic diversity (He: 0.7-0.8) and differentiation (D: 0.22-0.44) detected. Human impacts are frequent and the introduction of foreign plant material could have caused alterations in the genetic composition, 2) an intermediate area is characterized by a moderate anthropogenic perturbation (familiar-small agricultural farms). It has experienced a recent reduction of their effective population size and exhibit a reduction of haplotype richness and 3) a higher area showed elevated genetic diversity and differentiation values. The latter, has been revealed as a genetic diversity reservoir thanks to a low human impact. This study shows several important data that can contribute to the management of this forest area in the future. The low-perturbated stands with high genetic diversity indexes are critical to ensure effective sampling with afforestation purposes. _____________________________________________________________________________________________________________
Deeper Direct Perception in Autonomous Driving

Deep neural network architectures[14][4] have achieved amazing results on classification tasks in the ImageNet challenge (ILSVRC)[13] over recent years. While these networks are optimized for object classification problem with a given set of target classes, they also demonstrate strong capability in generalizing to other vision tasks such as object detection[12], pose estimation[17], etc. In this paper, we propose to apply transfer learning to the domain of autonomous driving based on a direct perception approach[2]. We present and evaluate our methods in fine-tuning pre-trained convolutional neural netowrk(CNN) models[14] for a regression task. Finally, we visualize and analyse the results of our model on test set as well as in game.
Partial Graph Matching by Enumerating Pseudo-Cliques in a Common Space ジェイ 泓杰

We proposed a new method for partial graph matching based on non-negative matrix factorization (NMF) and pseudo-clique mining. Compared with existing researches, it can find several potential matching solutions with different structural and attribute similarities. To achieve this purpose, we firstly map all the vertices of graphs into a common space by a modified non-negative matrix factorization. To find several subspaces in which local similarities between graphs can be observed, we apply pseudo-clique enumerator in this common space. As the similarity between graphs can be a global similarity in each subspace, standard global graph matching techniques is enough to cut off useless vertices and to obtain a targeted similarity as a result of partial graph matching. Our contributions in this research are that: Firstly, we presented a new framework for solving partial graph matching problem. Secondly, we designed a new class of NMF for finding common space. Furthermore, our experiments on both images and text data-sets reveal that our formulation works well on different kinds of data.
Concentration of solids in 3 D Rossby vortices

Vortices have been proposed as a solution to the "meter-size barrier" in the context of planetesimals formation. Indeed vortices may concentrate the solids in their centres and accelerate grain growth. By this mean, grains may overcome this size barrier without falling onto the central star due to gas drag. The Rossby Wave Instability (RWI) may be a solution to form such vortices again the destructive effect of differential rotation. We present here the first three dimensional (3D) simulations of the concentration of solids in such Rossby vortices.
Genetic diversity of Prunus domestica selected from ten countries across Europe

A DNA marker-based study in European plum was performed within the project “Identification of a representative set of Prunus domestica accessions of European origin, well documented and characterized, to be included into the AEGIS system (PRUNDOC)”. A total of 46 local plum accessions from 10 European countries (Belgium, France, Germany, Greece, Italy, Latvia, Norway, Serbia, Slovakia and Sweden) were analysed using SSR loci. In addition, seven reference cultivars (Bistrica, Hanita, Mirabelle de Nancy, Reine Claude Violette, Stanley, Valor and Victoria) were analysed for standardization of allele sizes. The following nine primers were used; PacA33 is an EST-SSR developed in apricot, BPPCT039, BPPCT007, BPPCT014, BPPCT034, BPPCT040, UDP96 and UDP98 were developed from genomic peach DNA while CPSCT026 was developed from genomic DNA of Japanese plum Prunus salicina. None of the 46 investigated local plum accessions were identical, nor were any of them identical to any of the 7 reference cultivars. Genetic similarity among accessions was examined using Jaccard's similarity coefficients. The obtained dendrogram showed that the plum accessions did not group in a pattern corresponding to their country of origin.
Viscoelastic analyses of a prestressed

Many wooden trusses built in the 19th Century were designed to be prestresseel, in order to have both diagonaIs active without tensile connections. However, the viscous behavior of wood can cause temporal losses in prestress. In the present contribution, a standard-linear-solid model for wood is used to carry out viscoelastic analyses. Simple prestressing experiments, to quantify the model parameters, are proposed. Results ofviscoelastic analyses ofthe Pine BluffHowe Bridge in Indiana are presented.
MEMORANDUM No 15 / 2007 Farrell Revisited : Visualising the DEA Production Frontier

The contributions of the paper are threefold: i) compare with mathematical rigour the Charnes, Cooper, and Rhodes DEA model and the Farrell model exhibiting constant returns to scale, ii) reinterpret the contribution of Farrell and Fieldhouse that extended the analysis to variables returns to scale and establish the connection with the approach in Banker, Charnes and Cooper, iii) provide graphical visualisation of properties of the frontier function. Both papers by Farrell emphasised the importance of graphical visualisation of non-parametric frontier functions, but, to our knowledge, this is seldom followed up in the literature. We use a graphical package (EffiVision) with a numerical representation of the frontier functions, representing the contemporary development of visualisation. By making suitable cuts through the DEA frontier in multidimensional space, various graphical representations of features of economic interest can be done. Development of ray average cost function and scale elasticity are novel illustrations.
Efficient flutter boundary and limit-cycle prediction algorithm based on the time spectral method

The computational efficiency of traditional time domain numerical method for solving the flutter boundary and limit-cycle oscillation is very low, which limits its application in engineering . In this paper, we develop an efficient numerical algorithm for predicting the flutter boundary and limit-cycle oscillation based on the time spectral method. The periodic aerodynamic forces can be quickly obtained by the time spectral method and the critical balanced equations are constructed. Then the second iteration method is used in the solution of the structural equations to avoid trapping the local optimum when searching the balance point. The standard test cases of a two-dimensional transonic airfoil are adopted to verify this algorithm. The results show that this algorithm can accurately capture the critical characteristic of flutter and limit-cycle oscillation with very few iteration steps. The calculation results are consistent with those of the traditional time domain method, while the computational efficiency can be improved by 1-2 orders of magnitude. So this algorithm has a very good application prospect.
VIDEO BASED FACE RECOGNITION USING FACE MANIFOLD WITH VIEW-DEPENDENT COVARIANCE MATRIX

Appearance variations in camera or video-captured images usually occur naturally. These variations might be caused by some changes in enviromental condition or by the erroneous of a preprocessing step. Therefore, a robust face recognition system should be able to deal with these variations in order to perform correct identity recognition of the input images. Unfortunately, relying on the simple manifold technique to deal with both pose and degradation problems is not sufficient. In this paper, we propose a face manifold with viewdependent covariance matrix method for video-based face recognition application. The view-dependent covariance matrices are obtained in an efficient way by interpolating only the eigenvectors and the eigenvalues of the covariance matrices of two consecutive training poses. Here the viewdependent covariance matrix plays an important role in providing the distribution information of samples in each class along the face manifold. Moreover, a pose estimation system is also integrated to the recognition system in order to handle pose variations. Experimental results showed that our proposed face manifold with view-dependent covariance matrix outperforms the well known simple manifold method.
AT THE DAWN OF THE TWENTY-FIRST CENTURY

■ Abstract In the first Annual Review of Psychology chapter since 1977 devoted exclusively to work motivation, we examine progress made in theory and research on needs, traits, values, cognition, and affect as well as three bodies of literature dealing with the context of motivation: national culture, job design, and models of person-environment fit. We focus primarily on work reported between 1993 and 2003, concluding that goal-setting, social cognitive, and organizational justice theories are the three most important approaches to work motivation to appear in the last 30 years. We reach 10 generally positive conclusions regarding predicting, understanding, and influencing work motivation in the new millennium.
Influence of electrolytes on the low-temperature performance of LiFePO4/C composite electrodes

The electrolyte, a key cell component for the successful operation of electrode materials, is greatly affected by its solvents. The influence of nonaqueous solvents on the electrochemical performance of a LiFePO4/C composite cathode was investigated at various operating temperatures. The kinetics of the LiFePO4/C composite electrode reaction, including changes of rate capability, redox potential, polarization degree, electrode reaction process, lithium ion diffusion efficiencies, exchange current densities, and activation energies, were evaluated using various techniques. The composition and composition ratio of solvents greatly affect the electrode reaction kinetics. In the mixed solvents of ethylene carbonate (EC), dimethyl carbonate (DMC) and ethyl methyl carbonate (EMC), EMC is beneficial for the room temperature performance, while the substitution of 20 vol.% of EMC by ethyl acetate (EA) is good for the low temperature performance. When 30 vol.% of DMC is substituted by 10 * Corresponding author. E-mail address: guixin66@scu.edu. cn, guixinwang1@gmail.com Tel. : +86-28-85406192. vol.% of EMC and 20 vol.% of EA, the diffusion coefficient of lithium ions increases from 2.62×10 to 2.50×10 cm s, while the exchange current density increases from 2.20×10 to 3.75×10 A cm at -20 oC, and the activation energy of the electrode reaction decreases from 48.36 to 33.01 kJ mol. These results are significant for the exploration of appropriate electrolytes for the extensive applications of LiFePO4/C composite electrodes.