Miracle-dz/UniFAR-FTUs huggingface dataset:
Super-resolution reconstruction : analysis and applications

In many imaging applications, the acquisition of high resolution (HR) images/video is highly desirable, but may not be available due to various practical limitations. Even if the prices of HR sensors in many commercial digital cameras decrease, the transmission and processing of HR images/video could still be a problem. Besides, the limited number of sensors of many medical diagnostic systems or industrial nondestructive testing systems still constrains the resolution of acquired images. It is always desirable to develop some software schemes to enhance the resolution of the acquired images/video. Super-resolution reconstruction (SR) is a technique to yield one or a set of HR images from the low resolution (LR) observations. In the first part of this thesis, we develop SR algorithms based on more general degradation models. Some existing multi-frame SR methods are constructed based on the assumption that the degradation process for each LR observation is identical. This assumption is widely accepted due to its simplicity, although it may lead to poor results with real data. For handling the real scenarios, we take into account more general assumptions: the LR observations are generated from the HR image through different degree of blurring or down-sampling with different magnification factors. For dealing with different out-of-focus blurs, we propose a new SR algorithm with better intitial estimation and tighter constraint to improve the performance. For the case involving zoom motion, i.e. the LR images are captured with different magnification factors, we present a new linear model for the image capturing model and propose a MAP based algorithm. ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library
THE ELECTROMYOGRAPHY OF FATIGUE

The changes in the electrical activity of muscle during and following fatigue are discussed. There are changes in size and form of the action potential ; synchronization occurs in the motor unit discharges. In fatigue which follows a short strong contraction, the electrical changes can be shown to depend on peripheral factors, mainly the failure of the contractile mechanism to produce as much tension as in the normal state. Thus, as the contraction proceeds, the integrated electrical activity in a muscle exerting a constant tension increases gradually. When the contraction ceases, the electrical activity falls rapidly to its unfatigued level, as measured by brief test contractions of the same force. An arterial occluding cuff prevents this recovery, if inflated at the end of the contraction. Muscular tremor, as recorded both mechanically and by the grouping of action potentials, is increased during and after muscular fatigue.
Empirical validity of Baldrige criteria: New Zealand evidence

Purpose – The purpose of this paper is to empirically assess the validity of Baldrige Criteria for Performance Excellence (CPE) for New Zealand organisations and to identify methodological gaps.Design/methodology/approach – By means of data collected from a sample of 91 New Zealand organisations, through a self‐assessment instrument (as a proxy for the CPE) a structural equation model was studied using the partial least squares method. The measurement validity of the CPE as well as the implied causal relationships in the CPE framework was tested. A sensitivity analysis was conducted to gain additional insights.Findings – The measurement validity of the CPE was established; of the 13 implied causal relationships in the CPE framework, 11 were statistically significant, which compared favourably with past studies. The results endorse some salient features of quality management: reliance on measurement, analysis, and knowledge management; the involvement of people; and the role of leadership in setting direct.
Integrating Stakeholders During Community FM's Early Project Phases

Purpose – This paper's purpose is to identify successful methods used to integrate stakeholders into the early phases of strategic community facility projects.Design/methodology/approach – A two‐stage research method was used at project inception and design phases of a community facility. Project inception used action research pre‐design strategic needs analysis workshops with internal local authority stakeholders to capture the council's internal stakeholders' agreed strategic aspirations, resulting in a performance‐based brief. Subsequently, observation‐based research investigated project processes conducted by others. Owing to the nature of the brief, additional engagement was required with stakeholders internal and external to the council.Findings – The processes integrating council and municipal stakeholders are described. These included identification of stakeholders and their roles in project processes. Stakeholders were shown to be the target for individual strategies within the facility's multipl.
Design and Analysis of Gas Turbine Blade by Potential Flow Approach

The design features of the turbine segment of the gas turbine have been taken from the “preliminary design of a power turbine for maximization of an existing turbojet engine”. It was observed that in the above design, after the rotor blades being designed they were analyzed only for the mechanical stresses. As the temperature has a significant effect on the overall stress in the rotor blades, a detailed study is carried out on the temperature effects to have a clear understanding of the combined mechanical and the thermal stresses. The first stage rotor blade of the gas turbine is analyzed for the mechanical axial and centrifugal forces. Knowing the fluid conditions at exit of the gas turbines, a value of static pressure was assumed at the turbine outlet. From this the corresponding enthalpy drop required in the power turbine is calculated. The peripheral speed of rotor and flows velocities is kept in the reasonable range so to minimize losses. In which the base profiles available and is analyzed later for flow conditions through any of the theoretical flow analysis methods such as “Potential flow Approach”.
Assessing the loadability of active distribution networks in the presence of DC controllable links

This study addresses the benefits of incorporating flexible DC links into radial distribution networks, which are subject to continuous load growth and higher levels of distributed generation penetration. To compare the use of DC links with conventional network reinforcement measures, an optimisation framework is developed. The main feature of the proposed formulation is that, irrespective of the criterion chosen to quantify the benefits of adding DC links, the same objective function is handled. Maximising or minimising a single-objective function, subject to the same set of constraints, allows different planning criteria to be assessed. The proposed optimisation framework is applied to actual networks embedding distributed generation. Two- and three-terminal voltage source converter-based DC links are considered in order to numerically illustrate the potential benefits of this technology in distribution systems.
Factors effecting the development of sentinel lymph node metastasis in clinical early-stage breast cancers (cT1-2N0): Clinical significance of primary tumor - skin distance

Aim: It was aimed to determine the demographic, clinicopathological and radiological predictors that may be effective in the development of sentinel lymph node (SLN) metastasis in patients with clinical early-stage breast cancer (cT1-2N0). Materials and Methods: 178 patients were included in the study. Demographic, clinicopathological and radiological characteristics of the patients were recorded. Among these, there were age, neutrophil / lymphocyte ratio (NLR), HER2, estrogen receptor (ER) and progesterone receptor (PR), proliferation index (Ki67), morphological grade, molecular subtype, histopathological subtype, tumor size and localization, multifocality and multicentricity, nipple-areola complex (NAC) infiltration, perineural invasion (PNI), lymphatic invasion (LI), vascular invasion (VI), primary tumor -breast skin distance (DFS). Results: Larger tumor size, HER-2 positivity, grade 3 histopathology, LI, VI, PNI, and closer DFS were found to be significant in univariate regression analyzes. In ROC analysis, the optimum cut-off value for DFS was found to be 13.5mm. In multivariant regression analyzes, HER-2 positivity, LI, PNI and ≤13.5mm DFS were found as independent SLN metastasis predictors. Conclusion: Closer DFS, HER-2 positivity, LI and PNI are very strong predictors in patients with clinical early-stage breast cancer that must be taken into account in the development of SLN metastasis in cT1-2N0 breast cancers. These factors can guide clinicians to take accurate decisions in the treatment process.
The lower bound of nonlocal gradient for non-convex and non-smooth image patches based regularization

In the inverse problem of image processing, we have witnessed that the non-convex and non-smooth regularizers can produce clearer image edges than convex ones such as total variation (TV). This fact can be explained by the uniform lower bound theory of the local gradient in non-convex and non-smooth regularization. In recent years, although it has been numerically shown that the nonlocal regularizers of various image patches based nonlocal methods can recover image textures well, we still desire a theoretical interpretation. To this end, we propose a non-convex non-smooth and block nonlocal regularization model based on image patches. By integrating the advantages of the non-convex and non-smooth potential function in the regularization term, the uniform lower bound theory of the image patches based nonlocal gradient is given. This approach partially explains why the proposed method can produce clearer image textures and edges. Compared to some classical regularization methods, such as TV, non-convex and non-smooth regularization, nonlocal total variation and block nonlocal total variation, our experimental results show that the proposed method improves restoration quality.
International Year of Light 2015 opens new dimensions in optics and photonics education

The United Nations have declared 2015 as the International Year of Light (IYL2015) and light-based technologies [1]. As a main result, the public interest is focused on both the achievements and the new frontiers of optics and photonics. This opens up new perspectives in the teaching and training of optics and photonics. In the first part of the paper, the author presents the numerous anniversaries occurring in the International Year of Light 2015 together with their importance to the development of science and technology. In the second part, we report on an interactive video projection at the opening ceremony of the IYL2015 in Paris on January 19-20, 2015. Students of Offenburg University have established an interactive video projection which visualizes Twitter and Facebook messages posted with the hashtag #iyl2015 in a mapping technique. Thus, the worldwide community can be interactively part of the opening ceremony. Finally, upcoming global community projects related to optics and astronomy events are presented.
Statistics of atomic frequency standards

A theoretical development is presented which results in a relationship between the expectation value of the standard deviation of the frequency fluctuations for any finite number of data samples and the infinite time average value of the standard deviation, which provides an invariant measure of an important quality factor of a frequency standard. A practical and straightforward method of determining the power spectral density of the frequency fluctuations from the variance of the frequency fluctuations, the sampling time, the number of samples taken, and the dependence on system bandwidth is also developed. Additional insight is also given into some of the problems that arise from the presence of "flicker noise" (spectrum proportional to |ω|-1) modulation of the frequency of an oscillator. The theory is applied in classifying the types of noise on the signals of frequency standards made available at NBS, Boulder Laboratories, such as: masers (both H and N15H 3 ), the cesium beam frequency standard employed as the U. S. Frequency Standard, and rubidium gas cells. "Flicker noise" frequency modulation was not observed on the signals of masers for sampling times ranging from 0.1 second to 4 hours. In a comparison between the NBS hydrogen maser and the NBS III cesium beam, uncorrelated random noise was observed on the frequency fluctuations for sampling times extending to 4 hours; the fractional standard deviations of the frequency fluctuations were as low as 5 parts in 1014.
Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications

Performance measures and metrics are essential for effectively managing logistics operations, particularly in a competitive global economy. The global economy is featured with global operations, outsourcing and supply chain and e-commerce. The real challenge for managers of this new enterprise environment is to develop suitable performance measures and metrics to make right decisions that would contribute to an improved organizational competitiveness. Now the question is whether traditional performance measures can be used and out of them which ones should be given priority for measuring the performance in a new enterprise environment. Some of the traditional measures and metrics may not be suitable for the new environment wherein many activities are not easily identifiable. Measuring intangibles and nonfinancial performance measures pose the greater challenge in the so-called knowledge economy. Nevertheless, measuring them is so critical for the successful operations of companies in this environment. Considering the importance of nonfinancial measures and intangibles, an attempt has been made in this paper to determine the key performance measures and metrics in supply chain and logistics operations. This is based on a literature survey and some of the reported case experiences. Suggestions for future research directions are also indicated.
Teachers as designers of learning in diverse, bilingual classrooms in England: an ADiBE case study

ABSTRACT This ADiBE case study explores an innovative, integrated approach to addressing diversity in secondary classrooms in England, where more than one language is used and learned. We position diversity in multilingual and multicultural communities where schooling seeks to provide meaningful learning experiences for all students and guide learners towards being and becoming global citizens. Within a UK context, underpinning values emphasise social justice and inclusion embodied in classroom practices that actively involve teachers as researchers with their learners – in terms of ‘curriculum-making’ and reinterpreting the impact of diversity on ‘successful’ learning communities. This research analyses contextual and exploratory factors that enable diverse learners with diverse needs to engage in learning partnerships with each other and their teachers. Using a framework to capture collaborative professional learning, synergies are explored between two different approaches to bilingual learning – English as an Additional language (EAL) and Content and Language Integrated Learning (CLIL). The case study identifies potentially rich sites for building pedagogic capital and explores how diversity can enable more young people to feel valued, respected and successful bilingual learners in formal schooling.
Automatic Electrocardiographic Analysis Using Artificial Neural Network Models

In this paper, the artificial neural network method was used for Electrocardiogram (ECG) pattern analysis. The analysis of the ECG can benefit from the wide availability of computing technology as far as features and performances as well. This paper presents some results achieved by carrying out the classification tasks by integrating the most common features of ECG analysis. Four types of ECG patterns were chosen from the MIT-BIH database to be recognized, including normal sinus rhythm, long term atrial fibrillation, sudden cardiac death and congestive heart failure. The R-R interval features were performed as the characteristic representation of the original ECG signals to be fed into the neural network models. Two types of artificial neural network models, SOM (Self- Organizing maps) and RBF (Radial Basis Function) networks were separately trained and tested for ECG pattern recognition and experimental results of the different models have been compared. The trade-off between the time consuming training of artificial neural networks and their performance is also explored. The Radial Basis Function network exhibited the best performance and reached an overall accuracy of 93% and the Kohonen Self- Organizing map network reached an overall accuracy of 87.5%.
A Low Power Multiplier Using Adiabatic Charging Binary Decision Diagram Circuit

An adiabatic charging binary decision diagram circuit (AC-BDD) is proposed that uses pass transistor logic based on a BDD and is operated by four power clocks. The AC-BDD circuit has the characteristics of a gate-level pipeline. Also proposed is a simplified switched capacitor regenerator that operates stably at any time even if the load capacitance changes variously. An 8×8 bit multiplier was designed using 0.25-µm CMOS/SIMOX (Complementary MOS/Separation by IMplanted OXygen) technology to confirm charging recovery. We found that the multiplier operates at 0.2 V and 1 MHz and its power consumption can be decreased to less than 10% that of CMOS logic.
Taxonomic description and pollination ecology of Cyrtorchis okuensis (Orchidaceae, Angraecinae), a new species endemic to the Cameroon Volcanic Line

Background and aims – A recent taxonomic and molecular study of the genus Cyrtorchis revealed three new species. Here, we describe one of these new species, endemic to the Cameroon Volcanic Line (CVL), and compare it to its closest relatives. Its conservation status is provided along with detailed information on its ecology and reproductive biology.Material and methods – A detailed examination of 21 herbarium specimens was performed using standard practices of herbarium taxonomy. The conservation status of the new species was assessed using the IUCN Red List Categories and Criteria. Furthermore, we investigated the reproductive biology of the new species in an easily accessible subpopulation in Cameroon and tested the hypothesis of hawkmoth pollination in the genus Cyrtorchis. Key results – The newly discovered species, here named C. okuensis, is restricted to the montane forest (1600 to 2500 m elevation) of the CVL and is currently assessed as Near Threatened (NT). Among angraecoid orchids in which hawkmoth pollination is recorded (~16 species), C. okuensis has the shortest nectar spur (19–40 mm). In situ observations revealed hawkmoths with short proboscis of the genus Hippotion (H. celerio, H. eson, and H. osiris) as the main pollinators. The rate of pollination and fruiting under natural conditions was low and among the 448 surveyed flowers only 38.8% (174/448 flowers) had their pollinia removed, 19% produced fruits (87/448 flowers), and 16% (70/448 flowers) set mature fruits. Conclusion – Cyrtorchis okuensis is clearly differentiated from C. submontana by its longer and wider floral bracts, longer anther caps, and wider triangular dorsal sepal.
Where is research on fossil fuels going in times of climate change? A perspective on chemical enhanced oil recovery

In a society where the global search for renewable and sustainable sources of energy, chemicals and materials has rapidly become a priority, due to the challenges posed by climate change, one may think that there is no place anymore for research regarding extraction and production of fossil fuels. However, there is no denying that coal, oil and gas still constitute the major source of energy worldwide by far, and humanity will be dependent on them still for decades. As a matter of fact, the global demand of fossil fuels is still increasing rather than decreasing. However, fossil resources are consumed at a much higher rate than they are generated. Only focusing on crude oil, the chances of finding new conventional reservoirs are nowadays low, and this conventional sources are quickly depleting, therefore it is necessary to turn more and more the attention to unconventional sources, such as carbonate reservoirs, tar sands, oil shales and deep off-shore reservoirs. Chemical enhanced oil recovery (cEOR) techniques are already well established in improving macroscopic and microscopic oil displacement, increasing oil production after primary and secondary methods are exhausted. However, these are mostly implemented in reservoirs that normally possess favorable conditions. Research can still contribute in making these processes more efficient and sustainable, especially for unconventional oil, for as long as we will need to extract fossil fuels. After supporting the idea that exploitation of fossil resources cannot stop just yet, this perspective article will highlight recent advances in the field of cEOR, mentioning new developments in traditional methods, such as polymer and surfactant flooding, as well as newer methods, such as nanoparticles, preformed particle gels, and smart waterflooding, plus the various possible new combinations (hybrid EOR). This paper will finally try to shortly outline future directions of cEOR research, with emphasis on sustainable methods, such as CO2 flooding combined with carbon capture and storage strategies, and newly available research tools, such as reservoir-on-a-chip and machine learning.
Deep Residual Feature Quantization for 3D Face Recognition

3D face recognition (FR) has been successfully applied using Convolutional neural networks (CNN) which have demonstrated stunning results in diverse computer vision and image classification tasks. Learning CNNs, however, need to estimate millions of parameters that expect high-performance computing capacity and storage. To deal with this issue, we propose an efficient method based on the quantization of residual features extracted from ResNet-50 pre-trained model. The method starts by describing each 3D face using a convolutional feature extraction block, and then apply the Bag-of-Features (BoF) paradigm to learn deep neural networks (we call it Deep BoF). To do so, we apply Radial Basis Function (RBF) neurons to quantize the deep features extracted from the last convolutional layers. An SVM classifier is then applied to classify faces according to their quantized term vectors. The obtained model is lightweight compared to classical CNN and it allows classifying arbitrary-sized images. The experimental results on the FRGCv2 and Bosphorus datasets show the powerful of our method compared to state of the art methods.
Advanced Metering Infrastructure for Distributed Generation Energy Cooperation Management

An AMI platform for DG energy management is proposed to provide service both utilities and customers in this paper. By enabling the interactive and efficient communication platform, the proposed AMI facilitates utilities to perform the energy management of DGs, economic dispatch and demand response effectively. Base on the CIM model, OSGi platform leads the AMI extendibility and Interoperability. The communication network includes several advanced communication technology which are used in distributed systems, if the AMI for DG can share the communication network and smart terminal even some advance application software in the utility information platform, it will work more powerfully and effectively.