Miracle-dz/UniFAR-FTUs huggingface dataset:
On robustness of motion control systems

Robustness and intelligence are becoming increasingly important in motion control systems. In multi-mass electromechanical systems, the estimation of damping capability and design of robust controllers are among very important aspects. In this thesis, conventional control methods coupled with fuzzy logic and neural networks are used to address these issues. First, damping capability of multi-mass electromechanical systems is estimated. The maximal damping and complete damping cases are determined using the generalised model for a multi-mass electromechanical system. To eliminate the load variation influence and reduce elastic vibrations, robust modal control is proposed with observer-based state feedback and feedforward compensation. The use of fuzzy logic dealing with uncertainties is investigated. Good transient performance is obtained, even in the case of changing plant parameters, by fuzzy tuning of the proportional-integral (PI) controller parameters. It is shown that PI controllers with fuzzy tuning can be used in cascade control in a two-mass system. Fuzzy tuning schemes, based on expert knowledge, can be applied to sliding mode control to accelerate the reaching phase and reduce chattering for robustness enhancement. In robust modal control , taking into account uncertainties in the plant parameters and disturbance rate of change, an improvement of observer robustness is achieved via a fuzzy tuning scheme of the predictive coefficient. Insensitivity to load variations is enhanced by continuously tuning the feedforward compensation coefficients. These fuzzy tuning schemes can be applied to robust modal control of multi-mass systems in the presence of uncertainties. Since tuning is a continuous process, exponential membership functions are used. However, with Gaussian or sigmoidal membership functions, similar results can also be obtained. Observer robustness achieved by fuzzy tuning is demonstrated to be suitable for incipient fault detection in dynamic systems. Neural network-based techniques to the problem concerned are also presented. It is shown that a neural net controller can replace the role of a feedforward controller or a fuzzy logic controller. Moreover, a neural net-based controller can be used as a classifier for recognising the error and derivative-of-error patterns, and providing an appropriate control action to improve tracking performance. The proposed controller can be used in a two-mass system without a priori knowledge of the plant. Neuro-fuzzy approach is introduced with a feedforward compensation from an observer based control loop and robust enhancement from a neural network model. Tuning is a human experience to increase robustness. Fuzzy tuning is shown to be efficient thanks to the possibility of adopting this experience. Neurotuning with learning capability will be a subject for further research.
Costing the Ex Situ Conservation of Genetic Resources: Maize and Wheat at CIMMYT

Worldwide, the number of genebanks and the amount of seed stored in them has increased substantially over the past few decades. Most attention is focused on the likely benefits from conservation, but conserving germplasm involves costs whose nature and magnitude are largely unknown. In this paper we compile and use a set of cost data for wheat and maize stored in the CIMMYT genebank to address a number of questions. What is the cost of storing an accession of either crop for one more year, or, equivalently what is the benefit in terms of cost savings from eliminating duplicate accessions from the genebank? Relatedly, what is the cost from introducing a new accession into the genebank, given the decision to store it is revisited after one year? Does it make economic sense for CIMMYT to discard accessions that may be available elsewhere? As an extension of this line of inquiry it is possible to value the benefits from either consolidating genebanks or at least networking existing banks to reduce or eliminate duplicate holdings not needed for backup safety purposes. We present estimates of the size and scale economies evident in the CIMMYT operation as a basis for assessing the economics of consolidation. Genebanks represent a commitment to conserve seeds for the very long-run. In this study we report on these long-run costs for the CIMMYT genebank costs that are sensitive to the interest rate used and the protocols for periodically replenishing accessions that are shared with others or regenerating accessions whose viability gradually diminishes with age.
Public-private partnerships (PPPs) in education in the Sultanate of Oman at the basic and post-basic education levels :towards a suggested framework

This research aims to explore the public–private partnership (PPP) phenomenon at the basic education and post-basic education levels in the Sultanate of Oman. Specifically, it identifies the types of existing PPPs and probes different stakeholders’ perspectives of PPPs. It also highlights the challenges that impede the effectiveness of PPPs in the Omani context and identifies approaches to alleviate them. Finally, it suggests a PPP framework for the Omani context. This study employed a case study design with a mixed-strategy approach to elicit data from a range of sources: the public education sector, the private education sector and other sectors. The research used semi-structured interviews, focus groups and documentary analysis as key data collection instruments. The public education sector participants comprised government officials, school principals and supervisors. The private education participants included school owners, school principals and chief executive officers (CEOs). Other participants were drawn from other governmental and non-governmental sectors. A total of four focus groups with 29 participants (six to nine participants in each group) and 32 semi-structured interviews covering participants from the different sectors were conducted. The research findings reveal that a range of PPPs exist in the Omani education context. These however, are predominantly informal and voluntary. They also seem to address financial aspects and rarely tackle key quality aspects such as curricula and learning outcomes. In this study, it transpires that in Oman, PPP is envisaged as a multistakeholder approach with reciprocal and long-term benefits rather than relating to privatisation or philanthropy. The research also concludes that PPPs in Oman seem to be challenged chiefly by political and regulatory impediments, as well as some practical barriers related to capacity and evaluation mechanisms. It is hoped that these results, together with the suggested PPP framework, will serve as a guideline for the promotion of public–private collaboration in education, as well as the development of a PPP programme at the basic education and post-basic education levels in Oman.
Three-wheeled mobile platform powered by LabVIEW at energy performance index

Outstanding grow in demand both of mobile platform operability performance and efficiency of project development methodology encourage to apply modern algorithms and reliable engineering tools design. Latest research results confirm that the energy performance index algorithm [1, 2] applied into strongly non-linear mechatronic object developed by use of mechatronic techniques can guarantee sufficient motion control in the reduced time design process. In this paper the authors present three wheeled mobile platform research object developed and controlled with a use of the LabVIEW software environment. In order to boost mobile platform performance and handle its real time surveillance motion process the authors implemented the NI cRIO controller (dedicated Real Time hardware powered by LabVIEW). Mathematical complexity of on-line algorithm and sophisticated model description affected all the process design. Presented paralleled design methodology approach supported by mechatronic techniques [3] (virtual prototyping, Hardware-In-the Loop Simulations and rapid prototyping on a target object) allowed authors to achieve the highest level of a mobile platform system optimisation and increased probability of the final concept success.
From the Margins to the Mainstream: Creating Value in Queensland's Music Industry

As elsewhere, the music industry in Queensland comprises two tiers. The first tier is composed of products and services engaged by major music labels and commercially successful artists who at times attract significant sales. The second tier — or what is sometimes referred to as the ‘grassroots’ (Gibson, 2002) — largely consists of independent musicians, production personnel and producers attracting both niche and at times mainstream audiences. Characterised by informally networked micro-economies, independent artists, niche markets and the exploitation of new technologies, the second tier is also of interest to cultural researchers, who have tended to concentrate on subcultural music communities and music produced outside of the mass market first tier. A mapping survey which examined the Queensland music industry in terms of size, location, income and activity is complemented by interviews with musicians, label owners, production personnel and others involved in the music ‘scene’. We explore how second-tier practices (such as a reliance on social networking to achieve recordings and performance opportunities, as well as DIY culture and innovative business approaches) offer alternative methods for ‘doing music’ and generating value in the creative industries.
Disrupted Work: Home‐Based Teleworking (HbTW) in the Aftermath of a Natural Disaster

Natural disasters disrupt the nature of work, promoting an urgent review of where work is performed. Home‐based telework (HbTW), a common form of telework, is increasingly promoted as a means to ensure continuity of operations in an emergency situation. While widely advocated, little is known of the challenges and outcomes of HbTW when employed in disaster situations. This article explores the organisational and employee experiences of HbTW in the aftermath of a disaster, drawing on data from over 240 public sector workers and their managers who worked from home following a series of earthquakes in Christchurch, New Zealand. Findings point to critical factors shaping the experiences and outcomes of HbTW in disaster situations. Significant variation in the experiences and perceptions of HbTW for team leaders highlights their pivotal role and heightened pressures to maintain control in complex disaster situations.
Approaches to relating rice root plasticity with yield stability across different drought stress and establishment conditions.

By responding to the variable soil environments in which rice crops are grown, roots are likely to contribute to yield stability across a range of soil moistures, nutrient levels, and establishment methods. In this study, we explored different approaches to quantification of root plasticity and characterization of its relationship with yield stability. Using four different statistical approaches (plasticity index, slope, AMMI, and factor analytic) on a set of 17 genotypes including several recently-developed breeding lines targeted to dry-direct seeding, we identified only very few direct relationships between root plasticity and yield stability. However, genotypes identified as having combined yield stability and root plasticity showed higher grain yields across trials. Furthermore, root plasticity was expressed to a greater degree in puddled transplanted trials rather than under dry direct seeding. Significant interactions between nitrogen and water resulted in contrasting relationships between nitrogen use efficiency and biomass stability between puddled transplanted and direct seeded conditions. These results reflect the complex interaction between nitrogen, drought, and even different types of drought (as a result of the establishment method) on rice root growth, and suggest that although rice root plasticity may confer stable yield across a range of environments it may be necessary to more narrowly define the targeted environments to which it will be most beneficial.
The Retail Revolution: How Wal-Mart Created a Brave New World of Business

The definitive account of how a small Ozarks company upended the world of business and what that change meansWal-Mart, the world's largest company, roared out of the rural South to change the way business is done. Deploying computer-age technology, Reagan-era politics, and Protestant evangelism, Sam Walton's firm became a byword for cheap goods and low-paid workers, famed for the ruthless efficiency of its global network of stores and factories. But the revolution has gone further: Sam's proteges have created a new economic order which puts thousands of manufacturers, indeed whole regions, in thrall to a retail royalty. Like the Pennsylvania Railroad and General Motors in their heyday, Wal-Mart sets the commercial model for a huge swath of the global economy. In this lively, probing investigation, historian Nelson Lichtenstein deepens and expands our knowledge of the merchandising giant. He shows that Wal-Mart's rise was closely linked to the cultural and religious values of Bible Belt America as well as to the imperial politics, deregulatory economics, and laissez-faire globalization of Ronald Reagan and his heirs. He explains how the company's success has transformed American politics, and he anticipates a day of reckoning, when challenges to the Wal-Mart way, at home and abroad, are likely to change the far-flung empire. Insightful, original, and steeped in the culture of retail life, "The Retail Revolution" draws on first hand reporting from coastal China to rural Arkansas to give a fresh and necessary understanding of the phenomenon that has transformed international commerce.
Development of a sensitive diagnostic multiplex platform based on digitally encoded microcarriers

In answer to the ever-increasing need in biomolecular research and clinical diagnostics to carry out many assays simultaneously in on tube, several microcarrier-based multiplex technologies (suspension arrays) have arisen in the past few years. Simultaneous detection of different target molecules that are present in one sample is possible by incubating the sample with a mixture of differently encoded microcarriers, each carrying another probe which can specifically interact with one of the targets. This means that each target will bind to a differently encoded microcarrier. When the targets are caught, several methods exist to label those 'positive' microcarriers. By means of this label, and by means of the code, it becomes possible to verify whether a target was caught at its surface, and which target was caught, respectively. Those multiplex measurements work quantitatively, because the more a target is present in the sample, the more targets will bind to their corresponding microcarrier. Five years ago, our research group proposed the use of spatial selective photobleaching, as an alternative method for the development of digitally encoded microcarriers, which were called 'memobeads'. It was suggested that this method could overcome the multiplexing limitations of existing technologies. The present study aimed to optimize the surface characteristics of t hose memobeads, and to verify whether they could then be applied to multiplex protein tests and nucleic acid tests. Furthermore, it was investigated in which way these memobead assays (and in general the assays performed with every kind of suspension arrays) could be improved to make them more efficient and sensitive.
Piezoelectric Materials and Devices: Applications in Engineering and Medical Sciences

Introduction Classification of Dielectric Materials Important Dielectric Parameters Electrostrictive Effect Piezoelectric Effect Pyroelectric Effect Ferroelectric Materials Poling Applications of Ferroelectric Materials Piezoelectric Characteristics Piezoelectric Coefficients Tensor Form of Piezoelectric Equations Independent Components of Piezoelectric, Elastic, and Dielectric Matrices Generator and Motor Actions of Piezoelectric Materials Strain versus Electric Field in Piezoelectric Materials Piezoelectric Coupling Coefficient k Dynamic Behaviour of a Piezoelectric Material Piezoelectric Materials Quartz Lead Zirconate Titanate (PZT) Fabrication of PZT Polymer Piezoelectric Materials Other Piezoelectric Materials Composite Piezoelectric Materials Engineering Applications of Piezoelectric Materials Gas Lighter Pressure Sensor Accelerometer Piezoelectric Gyroscope-Angular Rate Sensors Piezoelectric Microphone Piezoelectric Ultrasonic Transducers for Sound Navigation and Ranging (SONAR) Piezoelectric Tactile Sensor Energy Harvesting Piezoelectric Electronic Buzzer and Tweeter Piezoelectric Actuators Piezoelectric Motor Piezoelectric Micro Pump Piezoelectric Ultrasonic Drill Ultrasonic Cleaner Quartz Crystal Oscillator Quartz Crystal Balance Quartz Tuning Fork in Atomic Force Microscope Piezoelectric Transformer Nondestructive Testing (NDT) of Materials Using Ultrasonics Noise and Vibration Control Structural Health Monitoring Piezoelectric Sensors and Actuators in Smart Systems and Robots Medical Applications of Piezoelectric Materials Blood Pressure Monitor Piezoelectric Heartbeat Monitor Piezoelectric Tactile Sensor-Endoscopic Grasper and Minimal Invasive Surgical Instrument Piezoelectric Accelerometer-Monitoring Patient Activity and Detecting Tremors Piezoelectric Pump-Drug Delivery and Biomedical Analyses Ultrasonic Imaging Bone Density Measurement Using Ultrasound Ablation of Tumour Cells Using High-Intensity Focused Ultrasound (HIFU) Ultrasound for Drug Delivery Ultrasonic-Induced Transdermal Drug Delivery Phaco Emulsification-Cataract Surgery Therapeutic Ultrasound-Treatment of Injury, Muscular Pain, and Bone Fracture Modelling and Virtual Prototyping of Piezoelectric Devices Using Finite Element Software Tools Finite Element Method Theory of Coupled Field Finite Element Analysis for Piezoelectric Structure Introduction to FE Analysis of Piezoelectric Devices Using a Software Tool Examples of FE Analyses of Piezoelectric Devices
Sex Differences in Arrest for Juvenile Assaults

Abstract This study examines sex differences in assault, as well as the differences in arrest likelihood, for girls and boys in a sample of juvenile assaults from the National Incident-Based Reporting System. Using contingency tables, we compare dimensions of assault severity, victim characteristics, and victim–offender relationship across offender sex to identify patterns in boys and girls violence. Further, we employ logistic regression to analyze the effect of offender sex on the probability arrest, while controlling for these differences. The results indicated that the proportion of girls' offenses committed against older family members was greater than the proportion of boys' offenses. Furthermore, while controlling for victim, offender, and offense characteristics, log odds of arrest for girls were 11% higher than that for boys, a statistically significant effect. These results suggest that mandatory arrest policies for domestic violence may disproportionately affect girls, as a greater proportion o.
Evaluation of a Low Protein Distillers By-product for Finishing Cattle

Summary An experiment was conducted to evaluate the effect of level of a low protein distillers by-product, Dakota Bran Cake (DBRAN), on feedlot performance and carcass characteristics of yearling steers. Diets contained 0, 15, 30, 45% DBRAN, or 30% dried distillers grains plus solubles (DDGS), replacing corn (DM basis). Final BW, ADG, and F:G improved linearly and daily DMI had a quadratic positive response as level of DBRAN in the diet increased. With the exception of HCW, there were no significant differences for carcass characteristics. The DBRAN had feeding performance similar to DDGS at the same inclusion level. Feeding DBRAN in this trial, up to 45% of the diet, resulted in improved performance compared to feeding high-moisture/dry-rolled corn, suggesting DBRAN has 100 - 108% of the energy value of corn.
Optimal DG allocation and sizing in presence of storage systems considering network configuration effects in distribution systems

Optimal performance of power distribution networks greatly depends on network configuration, location and size of distributed generations (DGs) units and storage systems. That is, for different configurations, different optimal locations and sizes of DGs can be found and vice versa. Therefore, the impact of both location and size of DG and network configuration should be considered in the planning process, simultaneously. Also, the presence of storage systems in the distribution system leads to some loads to be supplied even in fault conditions. In this study, distribution system reconfiguration (DSR), for considering network configuration effect that runs in offline mode with constant loads, and optimal DG allocation and sizing problems are studied simultaneously to find an optimal condition for distribution network based on operational thresholds and reliability improvements. Non-dominated Sorting Genetic Algorithm is used to solve these problems simultaneously. Power losses, energy not supplied (ENS) and the costs associated with DG are the objectives that are studied. The method of calculating ENS in DSR problem in the presence of DGs with storage systems is explained and the impact of protective equipment is considered, as well. The proposed approach is applied on different test systems, and its effectiveness is shown in various conditions.
Predicting student performance in a blended learning environment using learning management system interaction data

PurposeStudent attritions in tertiary educational institutes may play a significant role to achieve core values leading towards strategic mission and financial well-being. Analysis of data generated from student interaction with learning management systems (LMSs) in blended learning (BL) environments may assist with the identification of students at risk of failing, but to what extent this may be possible is unknown. However, existing studies are limited to address the issues at a significant scale.Design/methodology/approachThis study develops a new approach harnessing applications of machine learning (ML) models on a dataset, that is publicly available, relevant to student attrition to identify potential students at risk. The dataset consists of the data generated by the interaction of students with LMS for their BL environment.FindingsIdentifying students at risk through an innovative approach will promote timely intervention in the learning process, such as for improving student academic progress. To evaluate the performance of the proposed approach, the accuracy is compared with other representational ML methods.Originality/valueThe best ML algorithm random forest with 85% is selected to support educators in implementing various pedagogical practices to improve students’ learning.