Miracle-dz/UniFAR-FTUs huggingface dataset:
Gaussian Process Based Trajectory Tracking for Nonholonomic Robots with Velocity Constraints

In this paper, we propose a novel learning-based robust adaptive trajectory tracking controller for nonholononmic robots subject to velocity input uncertainties and velocity input constraints. Gaussian process regression (GPR) is employed on account of its powerful estimation ability and wide scope of applications as a nonparametric regression method. The velocity uncertainties are estimated online using the real-time measured data. The prediction mean and variance of the GPR are used to counteract the effect of the uncertainties and to design the robust control term, respectively. A continuous robust controller is proposed which has the advantage of achieving asymptotic convergence of the trajectory tracking error instead of uniformly ultimately boundedness. Moreover, the velocity constraints can be handled by the design parameters. Simulation examples illustrate the effectiveness of the proposed controller.
Multinational enterprises, foreign direct investment and trade in China: A cointegration and Granger-causality approach

Multinational enterprises (MNEs) play a dominant role in the international business (IB) literature. Traditionally, by far the majority of IB studies deal with issues at the micro level of the individual MNE, or at the meso level of a sample of individual MNEs. This paper focuses on a macro-level issue: the impact of MNE behavior through foreign direct investment (FDI) on international trade, and vice versa. In so doing, this study responds to a recent plea for more macro-level studies in IB into the effect of MNE behavior on the macroeconomic performance of countries as a whole, particularly developing and emerging economies. In this way, IB research would inform the heated debate about the pros and cons of globalization, where antiglobalization rhetoric emphasizes the negative consequences of the increased dominance of MNEs for the world at large and the Third World in particular. In the current study, we focus on the largest developing or emerging economy of all: China. Applying sophisticated econometric techniques, we unravel the causality and direction of FDI ? trade linkages for the Chinese economy in the 1980 ? 2003 period.
The Sociology of Healthcare Safety and Quality

The immediate attraction is because it is about an important global issue, that of healthcare safety and quality. The topic is important for all health professionals but is doubly so for those of us who manage or lead health services. Greater accountability for safety and quality is being required of Australian health managers in 2017 as new provisions of the Australian Healthcare Agreements’ between the Commonwealth and States and Territories are being enacted. This public policy initiative also means that those of us who teach and research and are involved in the education of health professionals, particularly health managers, need to make increased effort in this area. The Monograph goes some way to being useful to assist us in these endeavours.
An Accelerated and Risk-free AC Power Flow Method with Machine Learning based Initiation

In recent years, the dynamics of power system has increased drastically due to faster load and generation variations. This has imposed challenges to both power system operation and planning. As a result, reducing the power flow computation time has become highly desired, especially for large power networks. In previous research works, the linearization approach may introduce errors in cases where the linear assumptions do not hold true; the conventional pure data-driven approach requires significant training effort and can be risky to systems with high variability due to its “black-box” nature. This paper proposes a risk-free method to accelerate AC power flow with machine learning based initiation: first, 4 machine learning models are used for estimating the initial PF solution; then the initial PF solution is taken as the warm-start point and fed into the Newton-Raphson stage to accelerate its converging speed. Comprehensive experiments are conducted on 4 power networks covering small to large sizes. The experiment shows the PF solution time can be reduced by 24% to 64% with lossless accuracy. The approach also demonstrates great robustness to system scenario change.
Analytical Center of Mass Trajectory Generation for Humanoid Walking and Running with Continuous Gait Transitions

We present an analytical trajectory generation framework for the combined computation of multiple walking and running sequences with continuous gait transitions. This framework builds on the Divergent Component of Motion (DCM)-based walking algorithm and the spline-based trajec-tory generation of the Biologically Inspired Deadbeat (BID) control for running. We describe our approach to generating closed-form center of mass (CoM) trajectories for walking and running by alternately linking the two gaits through continuity constraints. Thereby, we distinguish between vertical and horizontal planning. The vertical trajectory is computed in a forward recursion from the first to the last gait sequence. Due to the coupling of the gait sequences in the horizontal direction, we show the efficient generation of the horizontal CoM trajectory in a single matrix calculation. Subsequently, we unify the control strategies using a DCM tracking controller for the complete trajectory and integrate the proposed framework into an inverse dynamics-based whole-body controller. Finally, the presented approaches are validated in simulations with the humanoid robot Toro.
Comparison between the Optimal-Ordered SIC Detector in “Low-Complexity SIC Detection Algorithms for Multiple-Input Multiple-Output Systems” and a Previous SIC detector

In the conclusion of the paper “Low-Complexity SIC Detection Algorithms for Multiple-Input Multiple-Output Systems” published in 2015, it is claimed that the proposed optimal-ordered successive interference cancellation (OSIC) detector mainly uses “fast Givens rotations” and a new method for updating the squared norms of the rows in the inverse Cholesky factor of the error covariance matrix, to achieve the lowest average complexity among the existing OSIC detectors, including a previous one published in 2011 that also utilizes the inverse Cholesky factor and Givens rotations. This paper shows that “fast Givens rotations” proposed by the above-mentioned paper in 2015 and the Givens rotations utilized in the previous detector are similar and then they should both require the same complexity. We also show that the detector proposed in 2015 and the previous detector both take the dominant complexity to compute the initial inverse Cholesky factor and triangularize the permuted inverse Cholesky factor by Givens rotations, and then the dominant complexity is not affected by the method to update the squared norms of the rows in the inverse Cholesky factor. Finally, it is concluded that both the detectors require the same dominant complexity, including the same average complexity when both of them permute the channel matrix in the same way. On the other hand, we revise the incorrect complexities quoted or claimed in the above-mentioned paper published in 2015, to show that the worst-case complexity of the OSIC detector proposed in 2015 is equal to that of the previous OSIC detector.
CKRM: Class-based Prioritized Resource Control in Linux

In Linux, control of key resources such as memory, CPU time, disk I/O bandwidth and network bandwidth is strongly tied to kernel tasks and address spaces. The kernel offers very limited support for enforcing userspecified priorities during the allocation of these resources. In this paper, we argue that Linux kernel resource management should be based on classes rather than tasks alone and be guided by class shares rather than system utilization alone. Such class-based kernel resource management (CKRM) allows system administrators to provide differentiated service at a user or job level and prevent denial of service attacks. It also enables accurate metering of resource consumption in user and kernel mode. The paper proposes a framework for CKRM and discusses incremental modifications to kernel schedulers to implement the framework.
Factors influencing motivation of nurse leaders in a private hospital group in Gauteng, South Africa: A quantitative study

Background Nurse leadership is about aligning employees to a vision. This happens with buy-in, motivation and communication. When conducive environments are created by organisations, the motivation of nurse leaders will be enhanced, which will have a positive outcome on the organisation. Highly motivated nurse leaders accomplish more and are more productive. Nurse leadership is an essential source of support, mentorship and role modelling. These attributes tend to be more evident when nurse leaders are motivated. Objectives The objective of this study was to determine the factors that influence the motivation of nurse leaders. Method A quantitative, descriptive design and stratified sampling was used. Participants comprised unit managers (n = 49) from five hospitals in a private hospital group in South Africa. A self-administered questionnaire, namely, the Multidimensional Work Motivation Scale, was used to collect the data. Data were analysed using the IBM SPSS 22.0 program. Results The results indicated that the nurse leaders in this study were intrinsically motivated. Their motivation was influenced by support, relatedness, autonomy and competence. No relationships were found between motivation and age, years in a management position, gender, qualifications and staff-reporting structure. Conclusion By implication, to understand what motivates nurse leaders and to keep them motivated, recommendations were proposed to nursing and human resources management. It is expected that the implementation of the recommendations will have a positive influence on patient outcomes, organisational success and the motivation and satisfaction of nurse leaders.
Proton Exchange Membrane Fuel Cell Signal-Based Diagnostics Using Empirical Fourier Transform

Proton exchange membrane fuel cell (PEMFC) technology offers an attractive alternative to fossil fuels, especially for automotive applications, but it still needs to be improved in terms of reliability to be market competitive. This work presents a method to determine the health state of the cell using empirical Fourier decomposition (EFD) and Hilbert transform (HT) signal processing methods that are more suitable than conventional approaches for non-stationary and non-linear signals. The performance is found to be good in distinguishing the two faults of flooding and drying.
Energy-Aware Coded Transmission Strategy for Hierarchical Cooperative Caching Networks

With the rapid development of millions more edge base stations (EBSs) and billions of user devices in the future networks, the desire for low-energy system design and transmission strategy will be even more compelling. In this letter, we investigate the energy consumption issue of hierarchical cooperative caching networks (HCCNs) in which both EBSs and users are capable of storing content data in their local caches. A three-stage coded transmission strategy in HCCNs is proposed, and the closed expression of energy consumption of each stage is derived. In addition, we formulate a total energy consumption minimization problem with the constraint of EBSs’ cache sizes, and provide an algorithm to obtain the optimal cache placement matrix. We demonstrate by numerical results that, our optimized three-stage coded transmission strategy can achieve lower energy consumption than various multicast transmission strategies under the different users’ cache sizes.
Self-Adaptive Feedback E-Learning Scheme for Elementary Math in Kuwait

Mathematics is widely recognized as the most important and essential discipline because it serves as the foundation for many notable scientific and technical breakthroughs over the centuries. Students' attitudes toward mathematics can be significantly improved by using computers as a medium of instruction, according to several studies. Artificial Intelligence, and thus Machine Learning, is a critical driving force in the advancement of innovation and growth in a wide range of industries today, with the education sector being no exception in this regard. An Adaptive Feedback E-Learning Scheme for Elementary Math in Kuwait is being developed and implemented to improve the quality of mathematics education for the next generation of elementary school students. The proposed methodology attempts to close the gap between students' Math learning abilities and those of their teachers using Artificial Intelligence and Machine Learning methods. The adaptive Learning approach seeks to create a compelling learning experience that is adapted to the individual needs of each learner in a personalized manner. To determine the strengths and weaknesses of each student who enters the system, the suggested model operates in two modes: Diagnostic Mode and Remediation Mode. Additional rounds between the two modes may be required to address all a student's deficiencies for him or her to achieve an appropriate degree of mastery of the various arithmetic topics. Work on this project is being carried out in collaboration with the Kuwait Foundation for Advancement of Sciences (KFAS), Kuwait University (KU), and the Kuwaiti Ministry of Education (MoE).
Impact of Usability Mechanisms: A Family of Experiments on Efficiency, Effectiveness and User Satisfaction

Context: The usability software quality characteristic aims to improve system user performance. In a previous study, we found evidence of the impact of a set of usability features from the viewpoint of users in terms of efficiency, effectiveness and satisfaction. However, the impact level appears to depend on the usability feature and suggest priorities with respect to their implementation depending on how they promote user performance. Objectives: We use a family of three experiments to increase the precision and generalization of the results in the baseline experiment and provide findings regarding the impact on user performance of the Abort Operation, Progress Feedback and Preferences usability mechanisms. Method: We conduct two replications of the baseline experiment in academic settings. We analyse the data of 366 experimental subjects and apply aggregation (meta-analysis) procedures. Results: We find that the Abort Operation and Preferences usability mechanisms appear to improve system usability a great deal with respect to efficiency, effectiveness and user satisfaction. Conclusions: We find that the family of experiments further corroborates the results of the baseline experiment. Most of the results are statistically significant, and, because of the large number of experimental subjects, the evidence that we gathered in the replications is sufficient to outweigh other experiments.
Logistics cost, consumer demand, and retail establishment density*

This article develops models to formulate the optimal density of retail establishments by considering interactions between logistics cost and consumer demand. Commodities are assumed to be distributed from a depot directly or through single intermediate terminal to many retail establishments. Average logistic cost per item, consumer demand, and the interrelationship between them are analyzed. The optimal density of retail establishments and local terminals are determined by minimizing average logistic cost, or maximizing total supply subject to the demand-supply equality. The envelope curves for the optimal configuration strategies corresponding to different values of total market area and terminal cost are derived.
Single Buccal Injection for Anesthesia of Upper First Molar

Aims: A clinical trial was carried out to assess the efficiency of a single buccal injection to achieve anesthesia of the buccal aspect of the upper first molar instead of the traditional two injections. Materials and Methods: The subjects included in the clinical assessment were those needing extraction of an upper first molar of either side. For the purpose of comparison, the sample was randomly divided into two main groups: Group I (control group) which included 100 subjects who were to receive two buccal injections and a single palatal injection before extraction. While Group II (trial group) included 100 subjects who were to receive a single buccal injection and a single palatal injection before extraction. The following data were recorded: Pain on needle insertion, pain on deposition of solution, onset of surgical anesthesia and adequate surgical anesthesia. Results: The first criterion recorded was pain on needle insertion where the results showed no significant difference between both groups. The second criterion was pain on deposition of solution. Here the results also showed no significant difference between both groups in this aspect. For onset of surgical anesthesia, no significant difference was shown between both groups. In regard to pain grade experienced during surgery for both groups, the results showed that grade A anesthesia was recorded in 95% of patients in group I , whereas in 93% of patients in group II. Grade B anesthesia was recorded in 5% of patients in group I and in 7% of patients in group II. Statistically speaking, no significant difference was disclosed in regard to pain assessed during the extraction of the tooth between both groups. Conclusions: The achievement of successful local anesthesia is a continual challenge in dentistry. Any suggested new approach for achieving adequate anesthesia for either the maxilla or mandible as long as it is safe and effective can be recommended for routine dental care.
Comparison of the thickness of the gastrocnemius through ultrasonography during heel-drop exercise performance

Objective: This study was aimed to compare the thickness and pennation angle of gastrocnemius through ultrasonography during the heel-drop exercise on ankle dorsiflexion angle. Design: Cross-sectional study. Methods: Nineteen normal adults in their 20s had voluntarily participated in this study. All subjects performed the ankle heel-drop exercise with ankle dorsiflexed to , , and : heel-drop exercise with ankle dorsiflexed to was executed on floor-level, heel-drop exercise with ankle dorsiflexed to on a wooden-block of 2.3 cm in height, and heel-drop exercise with ankle dorsiflexed to on a wooden-block of 5.5 cm in height. In each regimen, the subjects completed a session of 100 heel-drop exercises (10 repetitions10 sets; with 30 seconds rest following each set; with 24 hours rest following each exercise). Before and immediately after each heel-drop exercise, the thickness and pennation angle of gastrocnemius were measured using an ultrasonography. Results: After the performance of the heel drop exercises with ankle dorsiflexed to , , and , the thickness of the gastrocnemius was significantly higher than pre-exercise (p was significantly higher than exercise with the ankle dorsiflexed to (p, , and is effective on the strengthening of the gastrocnemius. Furthermore, the heel-drop exercise with the ankle dorsiflexed to is more effective than with the ankle dorsiflexed to .
Outcome of subtrochanteric fracture of the femur managed with proximal femoral nail

Background: Subtrochanteric fractures of the femur remain some of the most challenging fractures facing Orthopaedic surgeons. Internal fixation of these fractures has gained widespread acceptance but the problems i.e. malunion, nonunion, implant failure, refracture and infection encountered after surgical treatment of these fractures have prompted continued development of new devices and treatment programs. We study the outcome of these fractures treated with long proximal femoral nail. Methods: All patients above 16 years of age who presented to our emergency department with subtrochanteric fracture of the femur were included in the study. Radiographs were taken and all the fractures were classified according to the Seinsheimers classification. All patients underwent fixation with the proximal femoral nail. The functional outcomes of the patients were assessed using the Harris hip score. Results: There were 20 males and 6 females in our study. According to the Seinsheimers classification we had 10 patients with type II fracture, 11 patients with type III fracture, 3 patients with type IV fracture and 2 with type V fracture. The average Harris hip score at the end of 1 year follow up was 82. There were 10 patients with an excellent Harris hip score, 9 patients with a good score, 4 with fair score and 3 had poor scores. We had 8 minor complications in our study, all fractures went on to unite and there was no implant failure. Conclusions: In our study we had good results with the proximal femoral nail, it requires minimal exposure and achieves biological fixation. It allows early weight bearing which is beneficial and has fewer implant related complications. Proximal femoral nail is a good choice of implant for fixation of subtrochanteric fractures.
The Impact of the Originate-to-Distribute Model on Banks Before and During the Financial Crisis

The growth of securitization made it easier for banks to sell home mortgage loans that they originated. I explore how mortgage sales affected banks in the years leading up to the financial crisis that began in 2007 and how their pre-crisis mortgage sales affected banks during the crisis. Loan sales are important because most banks sell mortgages as part of the securitization process, but few actually do the securitization. I find that stock returns increase when banks increase sales of mortgages used for refinancing rather than home purchase, suggesting that some banks scale up lending during refi booms. It is this flexibility that is both a plus and a potential minus of this model, since banks profited by scaling up during refi booms, but borrowers during refi booms were riskier than at other times, possibly adding risk to the financial system. I also find that losses during the financial crisis were related to pre-crisis mortgage sales, with the losses being roughly of the same magnitudes as the gains due to mortgage sales from 2001-2006.