Miracle-dz/UniFAR-FTUs huggingface dataset:
A PORTABLE DUAL LINE SCANNER FOR IMAGING OF STEEL BRIDGE COMPONENTS

The cost-effective maintenance of bridges requires quantitative information on size, location and orientation of defects in structural members. This is especially true for such fracture-critical bridge components as pins, anchor bolts, and trunnion shafts. In this paper a combination of an angular and a radial ultrasonic scan is proposed for cost-effective inspection of bridge components. This scanning procedure substantially reduces inspection time and cost of instrumentation while providing an adequate level of the information for defect characterization. First, the angular scan is used to detect and locate cracks. In areas with detected cracks the radial scan is subsequently applied. Images from both scans are combined to characterize the defects. A portable scanning unit has been developed to inspect bridge pins without disassembly. Scanning capabilities of the unit are suitable for a wide range of sizes and configurations. A modular design makes it possible to integrate the unit with various data acquisition systems and to deploy it for a wide range of components. The portable ultrasonic inspection system has successfully been tested at bridge sites.
A human-centred approach to the design of in-vehicle information systems: a case study in usability assessment

The potential of in-vehicle information systems (IVIS) to cause driver distraction highlights the need to ensure that such systems are designed in such a way that driver safety is not compromised. The human-centred design approach has much to offer in this regard. Central to this approach is that interface design is an iterative process, and that information on usability is collected as part of this process thus helping to inform system design. As a case study, the usability of three IVIS display presentation concepts for music selection was compared in each of two phases of design iteration. In Phase 1, data on usability were collected through a cognitive walkthrough approach involving experts. In Phase 2, data were collected as part of an experimental, lab-based study involving potential users. The method was effective in highlighting areas for design improvement and was sufficiently sensitive in differentiating the concepts on the basis of their usability.
The parametric sensitivity analysis of solidification process

In the paper the new results concerning the application of sensitivity analysis in the numerical modelling of solidification process is presented. This approach allows to investigate the influence of external conditions (thermophysical parameters of the mould, pouring temperature, initial mould temperature etc.) on the course of casting solidification. The model of thermal processes proceeding in the casting domain can b e constructed both in the macro scale (the I generation model) and in the macro/micro scale (the II generation model). As an example of the macro approach the continuous casting technology is considered and the sensitivity with respect to the substitute heat transfer coefficient in the continuous casting mould region is analyzed. In the second part of the paper the macro/micro model is introduced and the similar problem is solved again.
A Modified Homotopy-Based Tensor Eigenpairs Algorithm for Remote Sensing Feature Extraction

Independent component analysis (ICA) is one of the widely used techniques in remote sensing feature extraction. When selecting high-order statistics (HOS) as non-Gaussian metric, the determination of independent components (ICs) can be attributed to calculating the eigenpairs of HOS tensors of the mixed data. However, previous algorithms can only obtain approximate solutions for eigenpairs, and the accuracy of ICs may be unavoidably affected. Recently, a homotopy-based tensor eigenpairs (HTE) method that can obtain accurate solutions has been proposed. In this letter, we introduce it into the ICA field and further propose a modified version, termed modified HTE (MHTE). MHTE incorporates the concept of the projected Hessian matrix into HTE, which can further improve the accuracy of ICs and also intellectually determine the number of ICs. Experiments with both simulated image and remote sensing image demonstrate that it is more accurate and parameter adaptive than other compared feature extraction algorithms.
Decision shaping and strategy learning in multi-robot interactions

Recent developments in robot technology have contributed to the advancement of autonomous behaviours in human-robot systems; for example, in following instructions received from an interacting human partner. Nevertheless, increasingly many systems are moving towards more seamless forms of interaction, where factors such as implicit trust and persuasion between humans and robots are brought to the fore. In this context, the problem of attaining, through suitable computational models and algorithms, more complex strategic behaviours that can influence human decisions and actions during an interaction, remains largely open. To address this issue, this thesis introduces the problem of decision shaping in strategic interactions between humans and robots, where a robot seeks to lead, without however forcing, an interacting human partner to a particular state. Our approach to this problem is based on a combination of statistical modeling and synthesis of demonstrated behaviours, which enables robots to efficiently adapt to novel interacting agents. We primarily focus on interactions between autonomous and teleoperated (i.e. human-controlled) NAO humanoid robots, using the adversarial soccer penalty shooting game as an illustrative example. We begin by describing the various challenges that a robot operating in such complex interactive environments is likely to face. Then, we introduce a procedure through which composable strategy templates can be learned from provided human demonstrations of interactive behaviours. We subsequently present our primary contribution to the shaping problem, a Bayesian learning framework that empirically models and predicts the responses of an interacting agent, and computes action strategies that are likely to influence that agent towards a desired goal. We then address the related issue of factors affecting human decisions in these interactive strategic environments, such as the availability of perceptual information for the human operator. Finally, we describe an information processing algorithm, based on the Orient motion capture platform, which serves to facilitate direct (as opposed to teleoperation-mediated) strategic interactions between humans and robots. Our experiments introduce and evaluate a wide range of novel autonomous behaviours, where robots are shown to (learn to) influence a variety of interacting agents, ranging from other simple autonomous agents, to robots controlled by experienced human subjects. These results demonstrate the benefits of strategic reasoning in human-robot interaction, and constitute an important step towards realistic, practical applications, where robots are expected to be not just passive agents, but active, influencing participants.
View-Invariant Human Action Recognition Via View Transformation Network (VTN)

Since the human body is non-rigid, actions captured in different views always involve action occlusion and information loss. Recently, view-variation-related human action recognition is still a challenging problem. To address the problem, we propose a View Transformation Network (VTN) that realizes the view normalization by transforming arbitrary-view action samples to a base view to seek for a view-invariant representation. an attention learning module is designed to learn a co-attention for action samples of different views, that contributes to output a similar feature representation to erase the view diversity in different views. Extensive and fair evaluations are performed on the UESTC varying-view RGB-D dataset, the NTU RGB-D 60 dataset, and the NTU RGB-D 120 dataset, where three evaluation types, i.e. X-subject, X-view, and A-view recognition, are performed. Experiments illustrate that our VTN model achieves outstanding performance.
Stochastic optimal control with learned dynamics models

The motor control of anthropomorphic robotic systems is a challenging computational task mainly because of the high levels of redundancies such systems exhibit. Optimality principles provide a general strategy to resolve such redundancies in a task driven fashion. In particular closed loop optimisation, i.e., optimal feedback control (OFC), has served as a successful motor control model as it unifies important concepts such as costs, noise, sensory feedback and internal models into a coherent mathematical framework. Realising OFC on realistic anthropomorphic systems however is non-trivial: Firstly, such systems have typically large dimensionality and nonlinear dynamics, in which case the optimisation problem becomes computationally intractable. Approximative methods, like the iterative linear quadratic gaussian (ILQG), have been proposed to avoid this, however the transfer of solutions from idealised simulations to real hardware systems has proved to be challenging. Secondly, OFC relies on an accurate description of the system dynamics, which for many realistic control systems may be unknown, difficult to estimate, or subject to frequent systematic changes. Thirdly, many (especially biologically inspired) systems suffer from significant state or control dependent sources of noise, which are difficult to model in a generally valid fashion. This thesis addresses these issues with the aim to realise efficient OFC for anthropomorphic manipulators. First we investigate the implementation of OFC laws on anthropomorphic hardware. Using ILQG we optimally control a high-dimensional anthropomorphic manipulator without having to specify an explicit inverse kinematics, inverse dynamics or feedback control law. We achieve this by introducing a novel cost function that accounts for the physical constraints of the robot and a dynamics formulation that resolves discontinuities in the dynamics. The experimental hardware results reveal the benefits of OFC over traditional (open loop) optimal controllers in terms of energy efficiency and compliance, properties that are crucial for the control of modern anthropomorphic manipulators. We then propose a new framework of OFC with learned dynamics (OFC-LD) that, unlike classic approaches, does not rely on analytic dynamics functions but rather updates the internal dynamics model continuously from sensorimotor plant feedback. We demonstrate how this approach can compensate for unknown dynamics and for complex dynamic perturbations in an online fashion.
Predicting Asphalt Concrete Fatigue Life Using Artificial Neural Network Approach

The fatigue behavior of asphalt concrete is very complicated that a comprehensive fundamental theoretical model is not available. Therefore, a reliable empirical method for predicting fatigue life based on experimental data remains a desirable approach. However, the complexity of the fatigue process and the noise associated with the fatigue test results make even the traditional empirical methods, such as regression analysis, handicapped in producing a sufficiently accurate model. Artificial neural networks (ANNs) have the ability to derive considerable complex relationships and associations from experimental data while filtering out the effect of noisy data. In this study, the potential use of ANNs for fatigue life prediction was explored and the comparisons between ANN-based model predictions and predictions via multi-linear as well as other published models showed that ANN-based models provide much more accurate predictions.
Wind-tunnel investigation of a Fowler flap and spoiler for an advanced general aviation wing

The wing was tested without fuselage or empennage and was fitted with approximately three-quarter span Fowler flaps and half span spoilers. The spoilers were hinged at the 70 percent chord point and vented when the flaps were deflected. Static longitudinal and lateral aerodynamic data were obtained over an angle of attack range of -8 deg to 22 deg for various flap deflections and positions, spoiler geometries, and vent lip geometries. Lateral characteristics indicate that the spoilers are generally adequate for lateral control. In general, the spoiler effectiveness increases with increasing angle of attack, increases with increasing flap deflections, and is influenced by vent lip geometry. In addition, the data show that some two-dimensional effects on spoiler effectiveness are reduced in the three-dimensional case. Results also indicate significant increase in lift coefficient as the Fowler flaps are deflected; when the flap was fully deflected, the maximum wing lift coefficient was increased about 96 percent.
Association of Sociodemographic Characteristics and Lifestyle with Type 2 Diabetes Mellitus and Glycemic Control: A Cross-Sectional Study

Introduction/Aim: Type 2 diabetes mellitus is a major global public health problem affecting huge number of the population and Qatar is ranked among the top 10 countries with high diabetes prevalence. Identification of factors associated with poor glycemic control may help in planning for more comprehensive strategy of care, and better quality of life of diabetic patients. Materials and Methods: A cross sectional study was conducted and included 510 type 2 diabetic patients attending non-communicable disease clinics at nine primary health care centers in Qatar aiming to explore sociodemographic factors and lifestyle patterns associated with poor glycemic control among them. A stratified cluster
Fake news detection on Twitter using a data mining framework based on explainable machine learning techniques

Online social networks are a powerful communication and information dissemination tool, particularly useful in complex scenarios such as social crises, natural disasters, and pandemics. However, one of the main problems, especially in socio-political crises, is the automatic detection of fake news. This problem is usually addressed with greater or lesser success using supervised machine learning techniques. In this work, we propose a mixed approach, using unsupervised learning for feature extraction, and supervised learning for the prediction of fake news on microblogging networks. We consider Twitter news with linguistic and network features. To identify hidden patterns in the data, we use Principal Component Analysis and t-Distributed Stochastic Neighbor Embedding. The results show that the data can be better classified using non-linear rather than linear separability. Moreover, when using Extreme Gradient Boosting (XGBoost), an accuracy of 99.26% is obtained, and the most relevant features are identified.
Mitigation of the Impact of the Covid 19 Pandemic on Poverty and Income Distribution: A Case Study in Wonogiri Regency

The Covid pandemic had a significant impact on the economy because almost all sectors are affected. Food and Agriculture Organization (FAO) warned countries to be alert to the potential food crisis due to the COVID-19 pandemic. The research objectives are to (1) identify the income of the people affected by Covid 19, (2) analyze the changes in income, (3) formulate a mitigation model. The research method used is a survey with 240 respondents from rural communities affected by Covid 19, especially farmers and Micro, Small and Medium Enterprises (MSMEs). The analytical method used is cost and income analysis, SWOT analysis, poverty analysis and income distribution with the Gini Index approach. Covid 19 has impacted decreasing income and increasing poverty by 48.44% and the GI value of 0.604. The income distribution is increasingly widening and low/poor. Based on the SWOT analysis, the people affected by Covid 19 are in quadrant II, the point of growth and development. Mitigation model to prevent poverty and increase equity level with intensive strategy and integrative strategy. The strategy is to maintain product quality and continuity and optimization and development of marketing by utilizing government support and institutional strengthening.
A Case Study of Drivers and Barriers to E-Government Initiative in Jordan

AbstractThe University of ManchesterSahar Safwan Khasawneh-JalghoumDoctor of PhilosophyA Case Study of Drivers and Barriers to e-government initiative in Jordan17 May 2011E-government, in both developed and developing countries, has become the focus of governments? agenda because it offers enormous opportunities to reform the public sector and improve its performance. However, the evolution of e-government initiatives in developing countries is not at a satisfactory level which indicates that there are still enormous barriers and concerns that need to be addressed and solved.The major aim of this research is to investigate the supply-side stakeholders? perspectives of drivers and barriers forces that stimulate or impede the development of e-government initiative in Jordan and recommend strategies to e-government leaders on how to overcome and manage the encountered forces.This is a case study based qualitative research that employs semi-structured interviews as the primary source for data collection. In addition, template analysis approach and NVivo qualitative software have been used to analyze the gathered data. Moreover, a novel conceptual framework was initially developed by the researcher in order to be used as a helpful guide in the process of data collection and analysis. The framework was then applied to the research context to establish an overall view of the key drivers and barriers that influence the implementation of e-government at national level in Jordan.Research findings indicate that there are various drivers and barriers that affect the development of e-government initiative in Jordan. Most of the research findings confirmed what was already revealed by previous studies. However, this study added new and unique findings that were not discovered before including; The Holy Month of Ramadan, Ministers Reshuffling, Religious Beliefs, Preach Without Practicing, Wasta, and Improper Use of Technology. These new findings emerged distinctively from the Jordanian, Arabic and Islamic contexts. Finally, various recommendations have been proposed to demonstrate how challenges could be handled in practice.The value of this study is threefold. First, it contributes as new reference in e-government literature with respect to drivers and barriers to e-government in developing countries in general and in Arab nations in particular. Second, it proposes a conceptual framework that could be used as a tool to understand drivers and barriers that affect the development of e-government and their correlation to e-government initiatives success or failure. Third, it motivates changes in practice as it provides practical recommendations and guidance for practitioners and leaders of e-government in Jordan on how they should take actions to overcome and manage the encountered forces in order to reduce the possibility of the initiative failure and enhance the chance of its success.
The ecology and integrated management of broom (Cytisus scoparius) in New Zealand plantation forests : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecology at Massey University, Manawatu, New Zealand

Broom (Cytisus scoparius) is a major weed of radiata pine (Pinus radiata) plantations in New Zealand. The objective of this work was to determine how best to discourage broom establishing successfully within newly planted pine forests. Measurements of seed banks under pine forests showed that broom seeds can accumulate in the soil prior to the trees being harvested, with over 3500 seeds m of high viability being found in some forest soils. Seeds germinate immediately once scarified, but unscarified seeds break dormancy over time, and temperature fluctuations within bare soil are thought to help break seed coats. A field trial in which several different grass species were sown at different rates showed that grasses establishing at the same time as broom seedlings have little detrimental effect on broom establishment, regardless of whether planted in spring or autumn. However, if grasses had been established for six months prior to broom seeds germinating, no broom survived. A range of herbicides were tested for their ability to control broom from three months to 12 months in age. Most herbicides tested gave good control of broom seedlings, including hexazinone, terbuthylazine, and several combinations of clopyralid, triclopyr and picloram, though some herbicides were better than others on older plants. Herbicides were also assessed to determine how persistent they are within soil for controlling broom seedlings that begin establishing several months after a herbicide was applied. Three of the most persistent treatments were hexazinone, clopyralid and a triclopyr/picloram mixture. A range of herbicide and ground cover treatments were assessed in a newly planted pine forest in Hawkes Bay for their effect on broom establishment. The most effective strategy for discouraging broom problems in pine forests is thought to involve planting grass ground covers then using a herbicide mixture based on clopyralid with some picloram and triclopyr added to selectively remove broom from among young pines and the grass sward within the first 12 months. Following this herbicide application, subsequent establishment of further broom seedlings should be prevented initially by residues from the herbicide then later by the grass sward.
THE CAR BOOK

This book provides consumer information on 1982 model domestic and imported cars. The first section, referred to as a "Purchasing Guide", provides an overall comparison of cars in terms of safety, fuel economy, maintenance, and insurance costs. The following chapters cover individual topics, among which are: safety with information on crash test results, child safety seats and safety belts; fuel economy; maintenance costs with information on service contracts and special tips for dealing with a mechanic; warranties; insurance costs; tires with data on fuel economy and expected mileage; a used car purchasing guide with information on safety defects and recalls for 1977-1981; and a "complaint" chapter with advice on how to resolve complaints and who to contact. A Shopping Guide or Checklist is provided for the purchaser to use when taking notes on the cars he is interested in comparing.
Terahertz polarization rotator based on silicon asymmetrical structure

Terahertz polarization control has a wide range of applications in imaging, communication, biology, and analytical chemistry. Polarization rotator is of great significance as one of the main units of a polarization controller. In this paper, we propose and simulate a terahertz polarization rotator based on silicon asymmetrical structure, whose polarization extinction ratio reaches up to 35 dB and 26 dB for transverse electronic and transverse magnetic modes, respectively. Its 15-dB bandwidth is 40 GHz for a conversion length of 4.4 mm. The results show that the integrated scheme can achieve the function of polarization rotation with high conversion efficiency. We believe it will play an important role in terahertz polarization management.
An Iterative Parameter Estimation Method for Observation Models with Nonlinear Constraints

This article presents a parameter estimation algorithm for observation models with nonlinear constraints. A prominent example that belongs to this category is the continuous auto-calibration of stereo cameras. Here, our knowledge of the relation between the available measurements and the desired parameters is given by a nonlinear implicit constraint equation. An estimation method derived from an Iterated Extended Kalman Filter is designed for this application. Experiments are conducted with synthetic and real data. The proposed algorithm provides very good results and is readily applicable to a wider range of applications.