Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the carburized layer on the plasma nitriding behavior of duplex treated M50NiL steel

In this study, carburizing and nitriding duplex treatment was carried out at various carburizing pressures in the range of 1000–2500 Pa on M50NiL steel. The modified layers were characterized by laser scanning confocal microscopy (LSCM), scanning electron microscopy (SEM), transmission electron microscopy (TEM), x-ray diffraction (XRD) and microhardness testing. The results show that increasing the carburizing pressure to 2000 Pa leads to a decrease in the thickness of compound layer and nitrided layer, and resulted in a great increase in the number of spherical precipitates M(C,N) in the nitrided layer. The compound layer consists of ε phase and γ′ phase as well as a trace of Fe3O4. The change of carbon content in the surface layer after carburizing and the increase in carbon content in the surface layer caused by the transformation from carbides into nitrides during nitriding greatly decreased the content of γ′ phase in the compound layer when the carburizing pressure increased from 1000 Pa to 1500 Pa. The effects of the solid solution by alloying elements, the precipitates and the diffusion of carbon atoms on the diffusion rate of nitrogen atoms are discussed.
ICA Based Neural Networks for Pattern Recognition of Mechanical Faults

Artificial neural network (ANN), especially the self-organizing map (SOM) based on unsupervised learning is a kind of excellent method for patterns clustering and recognition. And, independent component anslysis (ICA) is a powerful tool for analyzing nongaussian data. In ICA, the JADE based on jointly approximate diagonalisation of eigen-matrices is a kind of robust and steady algorithm, which is specially appropriate to feature extraction of multivariate data. In this paper, the JADE is firstly proposed for feature extraction of different mechanical patterns (including normal and gear pitting), followed by certain a typical ANN (for example MLP, RBFN or SOM) which implements the final classification. By means of ICA and the further feature extraction strategys based on residual mutual information (RMI), higher than second order features embedded in multi-channel vibration measurements can be captured effectively. Thus, mechanical fault patterns can be recognized correctly. The results from contrast experiments showed that the compound ICA-SOM classifier can be constructed in simpler way, and classify various fault patterns at considerable accuracy, both of which imply its great potential in health condition monitoring of machines. 
Mobility Pattern Analysis and Trajectory Prediction Using Mobile GPRS Data

In this article,we analyzed users′mobility patterns and proposed several predictors to solve the next location prediction problem with users′mobile GPRS data.It is found that individual′s mobile behaviors are bursting,heterogeneous,weakly regular in temporal-spacial aspect,and individuals tend to stay in the same location in a short interval time.Furthermore,based on these empirical results,a blending model is developed to improve the prediction accuracy,overcomingall models with standalone feature.
Normalization Algorithm Based on the Technology of Probability Distribution Equalization and Its Application in Pattern Recognition

Normalization is an important process in samples classifying.The paper advanced a normalization algorithm based on the technology of probability distribution equalization,and changed the ira-balance of samples' distribution by uniting low-probability areas and splitting high-probability areas,in order to make the samples' distribution as even distribution.At last,the algorithm was used in the system of decision tree and BP neural network in microscope cells recognition,and was compared with those using rain-max normalization and zero-even normalization.It was proved that the algorithm improved the recognition accuracy and speed.
Optimal Selection of Secondary Variables Based on GA-PLS Algorithm and Its Application to Soft Sensor Modeling

A novel method based on genetic algorithm and partial least square regression is proposed to select the most suitable secondary process variables used as a soft sensor inputs.In the proposed approach,coding technique is very simple by exploiting binary code in which the numerical value(0 or 1) of each bit represents whether one variable is selected or not.Genetic algorithm is able to find optimal(or near) solution faster than typical schemes,such as stepwise regression,especially in high dimensional input spaces.Partial least square regression can be employed to overcome difficulties encountered with the existing collinearity in multivariable regression and is also suitable for situation with low observation/variable ratio.The proposed method has been applied to develop a soft-sensor for measuring the stabilizing oil components of catalytic reform reactor and the results demonstrate that the method is effective and suitable for practical application.
Improved semi-supervised online boosting for object tracking

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.
THE MODERATING EFFECT OF LEADER ANGER ON THE RELATIONSHIP BETWEEN LEADER-MEMBER EXCHANGE AND FOLLOWER JOB OUTCOMES

This study investigates the moderating effect of leader anger on the relationship between LMX, which is one of the most prominent leadership theories, and the three follower job outcomes of affective commitment towards the organization, trust in leader, and job satisfaction. This study was undertaken in the format of an experiment which is followed by a survey in which four groups of different fictional leader types were created, and respondents were asked to answer questions about these leaders assuming that they work with the described leader. The results of the study reveal that leader anger moderates the relationship between leader-member exchange and the three follower job outcomes in such a way that they result in diminished levels of affective commitment towards the organization, trust in leader, and job satisfaction in cases of both high LMX and low LMX leaders.
Factors affecting the acquisition and retention of employment among individuals with intellectual disabilities

This study analyzed factors affecting the acquisition and retention of employment among individuals with intellectual disabilities (ID). These factors were verified according to job type and were classified into general characteristics, family-related factors, psychological factors, and abilities. Data from 398 individuals with ID were analyzed using chi-square tests, independent t-tests, and regression analyses using the second wave of the first year Panel Survey of Employment for the Disabled in Korea. We found significant differences in sex, education level, receipt of basic living security assistance, transportation use, household income level, and family support between employed and unemployed participants. Additionally, the employed (vs. unemployed) ID group had significantly higher scores for all variables related to psychological factors and abilities. Factors affecting employment among individuals with ID included age, education level, receipt of basic living security assistance, family support, and vocational ability. Older age, higher education level, absence of basic living security assistance, greater family support, and higher vocational ability were associated with a higher probability of current employment. Transportation use and parents’ education were associated with a high probability of non-manufacturing-type jobs. Being married, absence of basic living security assistance, greater householder income level, family support, and manufacturing industry work were associated with increased job retention. Consequently, modifying the benefit system and developing family support systems may promote employment acquisition and retention among people with ID. Efforts are also needed to expand the job types available to individuals with ID.
Parallel computing simulation of water entry of a 2D rigid wedge using an explicit finite element method

Design against slamming loads is the concern of ship designers from the view point of strengths.An explicit finite element code is applied to study the impact of one rigid wedge subject to water entry using the Arbitrary Lagrangian-Eulerian(ALE) algorithm.The numerical results are compared and validated with experimental slamming acceleration and pressures in time domain,obtaining very good agreement.A convergence study for mesh density is carried out.Parallel computing technology is applied to improve the computing efficiency,which is one important issue arising in simulation when personal computers are used before.
Phase modulation in super-resolution microscopy

Phase modulation in super-resolution microscopy by Wenxiao Wang Phase modulation attracts arising attention in super-resolution studies because of the convenience and efficiency in encoding the information. Current super-resolution microscopy typically achieves high spatial resolution, but the temporal resolution remains low and obstructs most physical and chemical studies. Based on phase modulation, the novel technique Super Temporal-Resolved Microscopy is proposed to compress time information and thus improve the temporal resolution of 2D super-resolution microscopy. The fundamental basis for STReM is the utilization of a double helix phase mask that is rotated at fast speed to encode temporal information in the Fourier domain. Complicated movement can be also decomposed and reconstructed through an L1 norm constrained optimization process. STReM has been verified using both simulated and experimental 2D data and the temporal resolution is improved 20 times when comparing traditional methods to that of the novel method of STReM presented in this thesis. Besides the application to boost the temporal resolution, phase modulation is also applied to extract depth information in super-resolution microscopy. Most physical and chemical processes occur in 3D space and the underlying mechanism is usually unavailable or misleading due to the poor depth detection ability. Recently, phase modulation is reported as a promising solution to 3D imaging in superresolution microscopy. Various functions have been achieved through phase modulation such as improving the axial spatial localization precision and expanding the axial detection range. However, a current challenge is the lack of a robust and efficient algorithm to design a phase mask for arbitrary desired point spread function patterns in 3D continuous space. In this thesis the phase mask design algorithm is proposed using a phase retrieval scheme. Multiple algorithms were studied and compared for solving the phase retrieval, including Gerchberg Saxton, stochastic gradient decent, and Gauss-Newton methods. The Gauss-Newton method is proved to be the best by reaching the minima of the phase retrieval optimization. Several phase mask patterns for 3D super-resolution microscopy are proposed, and their corresponding PM patterns are successfully designed and experimentally fabricated with light lithography. Finally, by combining depth and time modulations, phase modulation is proposed to encode the information simultaneously in 4D space, which will definitely benefit super-resolution studies in the future.
Does capitalism (still) come in varieties?

Abstract That capitalisms vary and that these capitalisms neatly resolve themselves into distinct and discrete ‘varieties of capitalism’ is an almost foundational claim of contemporary comparative political economy. Yet it is far from evident that it is true. In this article, I return to the varieties conjecture, assessing the degree to which the claim might be warranted. In the process, I argue for the importance of differentiating clearly between ideal types and real types and for the value of heeding Weber’s advice about the dangers of confusing one for the other. I suggest that although capitalisms do not really come in varieties it is sometimes useful to proceed on the basis that they do, particularly if we think of such varieties as potentially dystopic. I suggest that such an acknowledgement is crucial in sensitizing us to the potential biases of varietal thinking, drawing out the implications for the positing of capitalist varieties in the period after the global financial crisis.
Did the German Minimum Wage Reform Influence (Un)employment Growth in 2015? Evidence from Regional Data

Abstract Using the variation across space, age and sex and the variation across space and sectors, we analyse the relationship between the minimum wage and (un)employment growth in 2015. We use difference-in-differences specifications and instrument the bite of the minimum wage by the lagged bite. The results provide stable evidence that a higher minimum wage bite is related to a higher growth rate of regular employment. We also find stable evidence that a higher minimum wage bite is related to a lower growth rate of marginal employment. These results are consistent with a transformation of marginal to regular jobs. The relationship to total employment is slightly positive in our preferred specification but insignificant or negative in others. For unemployment, we find a positive relationship between the bite of the minimum wage and unemployment growth in our preferred specification but insignificant or negative results in others.
Does Capital Adequacy Ratio Moderates the Relationship Between Ownership Structure and Performance?

This research aims to investigate the impact of the three-ownership structure (government, institutional and family) with capital adequacy ratio as the moderating element towards bank performance as measured by return on asset (ROA), return on equity (ROE), and market performance represented by Tobin’s Q, along with the five control variables. Data from eight Large Domesticallyowned Commercial Banks in Malaysia for the period that runs from 2000 to 2012 are used in this research. Hierarchical moderated multiple regressions methods are applied in this study. Results suggest that capital adequacy is significant as moderating factor of the three ownership structures towards the three bank performances regardless of the mix directions. However, the interaction between the three-ownership structure and capital adequacy are also found to be significant only towards return on equity (ROE).
Efficient and robust routing on mobile ad hoc networks

With the advance of wireless communication technologies and the increasing popularization of wireless devices, mobile ad hoc networks have attracted substantial interest in recent years. Due to the frequent changes in the network topology and the constrained power supply, routing in Mobile Ad Hoc Networks (MANETs) is difficult compared with the traditional routing protocols. Presently existing routing schemes are not well adapted to the mobile environment in terms of energy efficiency and routing robustness. In this thesis, we present schemes for energy-efficient routing and for robust routing. For energy-efficiency, a localized topology control scheme is proposed to achieve energy-efficient routing on mobile ad hoc networks. The distributed algorithm is simple yet efficient, and hence suitable for mobile ad hoc networks. With this algorithm, nodes can dynamically adjust their transmission power to construct an energy-efficient topology on the underlying ad hoc network. The power control approach not only reduces the power consumption in transmission, but also maintains the overall network connectivity so that the communication routes between nodes will not be disconnected. For routing robustness, we present a geographic routing protocol inspired by the fisheye technique. A node maintains accurate location information of nearby nodes and approximate location information of faraway nodes. The further away a node x is with respect to a given node y, the less information about x will be maintained on y. The routing protocol is based on the approximate location information and greedy forwarding. Packet forwarding decisions can be made independently for each node. This protocol is adaptive and robust for the mobile environments without high update messages overhead. This master thesis documents the project, the issues involved, our approach toward routing as well as the results obtained. We believe that the experience and results gained in this research could be useful for further work. ix ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library
The Lexical Status of the Root in Processing Morphologically Complex Words in Arabic

ABSTRACT This study investigated the effects of the Arabic root in the visual word recognition process among young readers in order to explore its role in reading acquisition and its development within the structure of the Arabic mental lexicon. We examined cross-modal priming of words that were derived from the same root of the target (/murattabun/-/tarti:bun/well ordered–order) relative to prime words that included three letters of the target but not root letters (/tura:bun/-/tarti:bun/soil-order) in two elementary-school age groups: second grade and fifth grade. The results showed facilitation in lexical decisions about target words, suggesting that the root is a lexical unit that plays a crucial role in the processing and representation of Arabic from the early stages of written language acquisition. This issue may stem from the morpho-orthographic nature of the written Arabic word and/or from the semantic information conveyed from the roots’ morpheme.
Lane Detection and Following Algorithm Based on Imaging Model

Considering the interruption of non-lane road markings,authors presented a lane detection and following algorithm on the basis of imaging model.In detection stage,lane image was firstly preprocessed by a morphological top-hat transform,imaging model was created for building relationship of lane parameters of the image coordinate and the world geodesic system(WGS) coordinate.Then the image was scanned for the first time on the basis of imaging model,after that,the edge distribution function(EDF) and RANSAC algorithm were used for the most sure lane detection.Based on the imaging model and the most sure lane,the image was scanned for the second time,local maximum values of EDF which were fitted to straight lane were recorded after the edge points.In following stage,Kalman filter was used for searching lane area,then B-spline model was applied to the lane fitting.Test results show that the proposed algorithm can efficiently and accurately detect and follow multiple lanes in the complex environments,particularly in the presence of interruption of non-lane road markings.
Transition of deformation mechanisms in nanotwinned single crystalline SiC

ABSTRACT The ability to experimentally synthesise ceramic materials to incorporate nanotwinned microstructures can drastically affect the underlying deformation mechanisms and mechanics through the complex interaction between stress state, crystallographic orientation, and twin orientation. In this study, molecular dynamics simulations are used to examine the transition in deformation mechanisms and mechanical responses of nanotwinned zinc-blende SiC ceramics subjected to different stress states (uniaxial compressive, uniaxial tensile, and shear deformation) by employing various twin spacings and loading/crystallographic orientations in nanotwinned structures, as compared to their single crystal counterparts. The simulation results show that different combinations of stress states and crystal/twin orientation, and twin spacing trigger different deformation mechanisms: (i) shear localised deformation and shear-induced fracture, preceded by point defect formation and dislocation slip, in the vicinity of the twin lamellae, shear band formation, and dislocation (emission) avalanche; (ii) cleavage and fracture without dislocation plasticity, weakening the nanotwinned ceramics compared to their twin-free counterpart; (iii) severe localised deformation, generating a unique zigzag microstructure between twins without any structural phase transformations or amorphisation, and (iv) atomic disordering localised in the vicinity of coherent twin boundaries, triggering dislocation nucleation and low shearability compared to twin-free systems.
Pen to the tiller: Land reform and social mobility across the 1979 Iranian revolution

Giovanni Arrighi joined together questions of agrarian political economy with questions concerning the livelihoods of rural migrants and the fate of peasant communities as they dissipated. In this article, we apply Arrighi's concerns to the case of Iran to examine how processes of agrarian transformation link with trends in social stratification and upward mobility. First, we argue that land reform implemented during the reign of Mohammad Reza Shah Pahlavi contributed to a heterogenous social differentiation of the Iranian peasantry. Second, we claim that the widening of access to credentials fostered by Ayatollah Ruhollah Khomeini's Islamic Republic laid the tracks by which peasants and rural households could convert landholding assets into newly accessible forms of cultural capital. The benefits of these transformational processes, however, fell disproportionately to the rural middle strata created under the Pahlavi monarchy. Through the use of a new survey dataset, we show how pre‐1979 land reform in Iran favoured segments of the peasantry, not for those who remained in rural agricultural production, but instead for those who utilized landholdings as a means to transfer status and opportunities to their children after the 1979 Iranian revolution.