Miracle-dz/UniFAR-FTUs huggingface dataset:
Needs for Bandwidth Reconfigurable Filter Networks for Space Application

In this paper the need for in-orbit reconfigurable filters and multiplexers is discussed. Applications for Ku-band and Ka-band missions are presented and put in context with existing solutions already in orbit. Application scenarios of reconfigurable filters and multiplexers are put forward for discussion with the potential for significant mass and complexity reduction whilst achieving capacity optimisation. Technical challenges are identified. Shortcomings and the dilemma of the complex trade-off from a system engineering point of view are discussed highlighting the need of hardware developments.
Bidirectional Inductive Power Transfer System: Analysis and Control

i Acknowledgments . iii List of Figures . ix List of Tables . xv List of Abbreviations . xvii List of Symbols . xix Introduction . 1 Chapter 1 1.1. Background . 1 1.2. Motivation . 2 1.3. Research Objectives . 3 1.4. Thesis Organisation . 3 Fundamentals of Inductive Power Transfer Systems . 7 Chapter 2 2.
An Adaptive Learning Tele-Text Chatterbot

Adaptive software packages are intended to increase the lifespan of systems as well as reduce the maintenance costs of those systems. An adaptive system is one that can adjust its response to a given situation or input using new settings or information. Up to now adaptive software systems require administrative intervention in order to execute a system modification. Either its source code has to be modified or some settings have to be changed. The goal of this project is to develop a system that demonstrates a learning capability via conversations with a user. The learning ability will illustrate a change of response to the same question, i.e. situation, after new or relevant, information has been obtained through previous conversations. The system will be developed using Java as the implementation language and with SQL databases as its knowledge base.
Toward versatile structural modification for bayesian nonparametric time series models

Unsupervised learning techniques discover organizational structure in data, but to do so they must approach the problem with a priori assumptions. A fundamental trend in the development of these techniques has been the relaxation or elimination of the unwanted or arbitrary structural assumptions they impose. For systems that derive hidden Markov models (HMMs) from time series data, state-of-the-art techniques now assume only that the number of hidden states will be relatively small, a useful, flexible, and usually correct hypothesis. With unwanted structural constraints mitigated, we investigate a flexible means of introducing new, useful structural assumptions into an advanced HMM learning technique, assumptions that reflect details of our prior understanding of the problem. Our investigation, motivated by the unsupervised learning of view-based object models from video data, adapts a Bayesian nonparametric approach to inferring HMMs from data [1] to exhibit biases for nearly block diagonal transition dynamics, as well as for transitions between hidden states with similar emission models. We introduce aggressive Markov chain Monte Carlo sampling techniques for posterior inference in our generalized models, and demonstrate the technique in a collection of artificial and natural data settings, including the motivating object model learning problem.
Managerial cognition, strategic behavior and innovation: biopharmaceutical R & D

In biopharmaceutical industry, R & D managers are open to new knowledge and technology to achieve innovation. On the other hand, R & D managers keep core knowledge in confidentiality to outrun competitors in claiming intellectual properties, patents or market exclusivities. For understanding innovation in this industrial success logic, it is essential to understand R & D managerial cognitive and behavioral constructs and build a relational model for optimization in the pursuit of innovation. The cognitive belief and behavioral choice of R & D manager's remains understudied even though these managers are at the frontline of new scientific knowledge and its interpretation into new therapeutics. This study surveyed data from questionnaires completed by 88 R & D biopharmaceutical managers. The statistical analyses of the data provided R & D managerial constructs and an Innovative Managerial Model (IMM). The model draws a relational map between constructs and shows that innovation is optimized when external collaborations, strategic cognition, managerial openness to networking and managerial openness to new technologies are factored into the therapeutic development process. The study's findings offer practical implications to boost R & D managerial innovativeness while filling the missing R & D managerial input in the current R & D productivity model.
Effect of citicoline on ischemic lesions as measured by diffusion‐weighted magnetic resonance imaging

We examined the effect of the neuroprotective and neuroreparative agent citicoline on the growth of cerebral ischemic lesions in a double‐blind placebo‐controlled study involving patients with acute ischemic stroke using diffusion‐weighted magnetic resonance imaging (DWI). Patients with acute ischemic stroke symptom onset 24 hours or less before the start of treatment, National Institutes of Health Stroke Scale (NIHSS) scores of 5 or higher, and lesions of 1 to 120 cc in cerebral gray matter by DWI were enrolled. DWI, T2‐weighted magnetic resonance imaging (MRI), perfusion‐weighted MRI, and magnetic resonance angiography were obtained at baseline, week 1, and week 12. Citicoline (500 mg/day) was administered orally for 6 weeks, and patients were followed for 12 weeks. The primary assessment was progression of ischemic lesion volume from baseline to 12 weeks as measured by MRI. A total of 100 patients entered the study. The primary MRI analysis included 40 placebo‐treated patients and 41 citicoline‐treated patients with both baseline and week 12 MRI data and failed to demonstrate a significant difference in lesion volume change from baseline to week 12. From baseline to week 12, ischemic lesion volume [all values mean (SE)] expanded by 180% (107) among placebo‐treated patients compared with 34% (19) among citicoline‐treated patients. In a secondary analysis, lesion volume decreased from week 1 to week 12 by 6.9 cc (2.8) on placebo versus 17.2 cc (2.6) on citicoline. Baseline variables that were predictors of change in lesion size over 12 weeks were the volume of hypoperfusion (strongest association), baseline NIHSS score, lesion volume on DWI, arterial lesion by magnetic resonance angiography, and categorized elapsed time (≤12 or >12 hours) from stroke onset to first dose. A marked association between lesion volume reduction and improvement of NIHSS score by seven or more points was observed. Significant correlations between lesion volumes and clinical measures were found, replicating values reported in the literature for smaller case series. We observed a reduction in lesion volume growth from baseline to week 12 with citicoline treatment, with a significantly greater reduction in volume from week 1 to week 12 with citicoline. We found a significant inverse relationship between lesion volume change over 12 weeks as measured by MRI and clinical outcome for ischemic stroke. This relationship supports the role of DWI as a surrogate marker of clinically meaningful lesion progression in stroke clinical trials. The hypothesis that citicoline reduces lesion growth and improves clinical outcome will be tested further. Ann Neurol 2000;48:713–722
The Relationship between Income and Well-Being, an Irish Study

Neoclassical economists traditionally derive utility purely from income as arbitrated by consumer preferences and choice [1]. Utility theory presumes that individuals are rational and insatiable consumers, always favouring more over less and thus, higher income results in higher well-being. In other words, the degree of individual preferences that are fulfilled is directly correlated with individual utility within a rational individual’s monetary budget constraint. Despite this, the correlation between income and well-being has vastly been debated within economic literature since the 1970s [2]. Literature in the area of behavioural economics has found that individuals often make decisions that somewhat compromise their own well-being and thus, depart from the standard model of the rational economic agent [3]. If indeed, individuals display limited rationality when maximizing utility, then choices made do not necessarily mirror individual’s true preferences. As a result of this, economists have become increasingly apprehensive with regards to the traditional preference theory when measuring utility [4]. These concerns have been intensified by the frequent discrepancies which occur between individual reported well-being and income levels in numerous economic literatures. Easterlin RA [5] pioneered the economics of happiness in the 1970s. Easterlin RA [5-7] finds that well-being levels across individuals within a specified nation fluctuate directly with income however; national income increases do not result in greater national well-being levels. Easterlin’s [5-7] finding was confirmed by subsequent studies based on time series analysis for one nation [8]. Diversely, cross-sectional micro-empirical analyses, using individual level data from a single nation, find mixed results. Primarily however, studies using such data find positive, albeit largely weak, correlations between income and well-being. Micro-empirical analyses, using data from same individuals over time, find statistically significant positive relationships between income and well-being with correlation coefficients ranging from 0.12 [9] and approximately 0.2 [7]. Cross sectional analyses on numerous nations find a lower income well-being correlation when regarding within nation results as when regarding between nation results.
Multiphase computer-generated holograms for full-color image generation

Multi-phase and binary-phase computer-generated holograms were designed and demonstrated for full-color image generation. Optimize a phase profile of the hologram that achieves each color image, we employed a simulated annealing method. The design binary phase hologram had the diffraction efficiency of 33.23 percent and the reconstruction error of 0.367 X 10-2. And eight phase hologram had the diffraction efficiency of 67.92 percent and the reconstruction error of 0.273 X 10-2. The designed BPH was fabricated by micro photolithographic technique with a minimum pixel width of 5micrometers . And the it was reconstructed using by two Ar-ion lasers and a He-Ne laser. In addition, the color dispersion characteristic of the fabricate grating and scaling problem of the reconstructed image were discussed.
Non-Local Regularized Variational Model for Image Deblurring under Mixed Gaussian-Impulse Noise

The presence of mixed Gaussian-impulse noise makes image deblurring much more challenging in real-world applications. To guarantee high-quality deblurred images, a non-local regularized variational model is proposed in this paper for restoration of blurred images corrupted by mixed Gaussian-impulse noise. The proposed image restoration model is mainly composed of a mixed L^(1,2) data-fidelity term and a non-local total variation regularizer. The nonlocal regularizer is capable of suppressing staircase-like artifacts and preserving fine structures since it takes full advantage of high degree of self-similarity and redundancy within images. However, the mixed data-fidelity term and non-local regularizer make the image deblurring problem arithmetically difficult to solve. To guarantee solution stability and efficiency, an alternating minimization algorithm is developed to solve the resulting optimization problem. In particular, the original optimization problem can be decomposed into two simpler subproblems. Each subproblem is then efficiently solved using existing numerical method. Comprehensive experiments on grayscale and color test images have been carried out to compare our proposed method with several state-of the- art image restoration methods. Experimental results demonstrated that our proposed method was more capable of removing both blurring effect and mixed Gaussian-impulse noise, as well as preserving fine image details.
Ensemble features selection method as tool for breast cancer classification

This work aims to gather experimental evidence of features relevance, as well as finding a breast cancer classification scheme that provides the high performance over the area under receiver operating characteristic curve (AUC). An ensemble feature selection method (named RMean) based on the mean criteria for indexing relevant features is presented. The proposed method provided better classification performances (statistically significant) than those who constitute the baseline, attaining AUC scores of 0.7775 with the support vector machine on microcalcifications dataset and 0.9440 with the feed-forward-backpropagation neural network classifier on masses dataset. The most relevant features for microcalcifications classification were: mammographic stroma distortion, density, right bottom quadrant, perimeter, standard deviation, entropy, and angular second moment. Meanwhile, to classify masses were: mammographic stroma distortion, mammographic calcification, mammographic nodules, density, circularity, roughness, and shape.
Development of a Thai version of the neutropenia subscale for the Functional Assessment of Cancer Therapy–Neutropenia questionnaire

Abstract Background There is a need for a validated translation of the neutropenia subscale (NS) of the Functional Assessment of Cancer Therapy-Neutropenia (FACT-N) questionnaire used to assess neutropenia-specific concerns and health-related quality of life for Thai patients receiving cancer chemotherapy. Objectives To translate the NS of the FACT-N questionnaire into Thai and examine the psychometric properties of the Thai version. Methods The 19 item NS was translated into Thai in accordance with the guidelines of the Functional Assessment of Chronic Illness Therapy (FACIT) translation methodology. The psychometric properties of the translated version were then tested. We randomly selected 260 patient participants with hematological malignancies from four hospitals in Thailand. All participants completed the Thai version of FACT-N at the time of expected neutropenia (7-14 days after receiving chemotherapy). The Thai NS content validity was evaluated by a panel of 5 experts. The construct validity of the Thai NS was tested by confirmatory factor analysis (CFA). The internal consistency of the Thai NS was tested with Cronbach’s α coefficients. Results The Thai version of the NS was semantically equivalent to the English version. The content validity index was good at 0.95. The CFA of the Thai NS indicated acceptable construct validity. All 19 items on the Thai NS had significant estimated factor loadings (P < 0.05). Cronbach’s α coefficient was 0.82. Conclusions The Thai NS, as part of FACT-N, is appropriate in terms of translation and psychometric properties for assessing specific neutropenia-related concerns in Thai patients undergoing cancer chemotherapy
An Analytical Approach to Evaluation of SSD Effects under MapReduce Workloads

As the cost-per-byte of SSDs dramatically decreases, the introduction of SSDs to Hadoop becomes an attractive choice for high performance data processing. In this paper the cost-perperformance of SSD-based Hadoop cluster (SSDHadoop) and HDD-based Hadoop cluster (HDDHadoop) are evaluated. For this, we propose a MapReduce performance model using queuing network to simulate the execution time of MapReduce job with varying cluster size. To achieve an accurate model, the execution time distribution of MapReduce job is carefully profiled. The developed model can precisely predict the execution time of MapReduce jobs with less than 7% difference for most cases. It is also found that SSD-Hadoop is 20% more cost efficient than HDD-Hadoop because SSD-Hadoop needs a smaller number of nodes than HDD-Hadoop to achieve a comparable performance, according to the results of simulation with varying the number of cluster nodes.
Targeted cytotoxic analog of luteinizing hormone‐releasing hormone AN‐207 inhibits the growth of PC‐82 human prostate cancer in nude mice

Receptors for luteinizing hormone‐releasing hormone (LH‐RH) found in prostate cancers might be used for targeting of chemotherapeutic agents. Doxorubicin derivative 2‐pyrrolinodoxorubicin (AN‐201) can be linked to carrier analog [D‐Lys6]LH‐RH to form the targeted cytotoxic analog of LH‐RH, AN‐207.
Machine Learning in Automatic Speech Recognition: A Survey

ABSTRACT Over the past few decades, there has been tremendous development in machine learning paradigms used in automatic speech recognition (ASR) for home automation to space exploration. Though commercial speech recognizers are available for certain well-defined applications like dictation and transcription, many issues in ASR like recognition in noisy environments, multilingual recognition, and multi-modal recognition are yet to be addressed effectively. A comprehensive review of common machine learning techniques like artificial neural networks, support vector machines, and Gaussian mixture models along with hidden Markov models employed in ASR is provided. A thorough review on the recent developments in deep learning which has provided significant improvements in ASR performance, along with its relevance in the future of ASR, is also presented.
Accuracy Analysis of Extraction Methods for Effective Channel Length in Deep-Submicron MOSFETs

A comparative study of two capacitance methods to measure the effective channel length in deep-submicron MOSFETs has been made in detail. Since the reduction of the overlap capacitance in the accumulation region is smaller than the addition of the inner fringe capacitance at zero gate voltage, the capacitance method removing the parasitic capacitance in the accumulation region extracts a more accurate effective channel length than the method removing that at zero gate voltage.
Learning online: massive open online courses (MOOCs), connectivism, and cultural psychology

In this reflection, we discuss the connectivist conception of learning in Web 2.0 environments, which underpins the pedagogy of what are known as cMOOCs (connectivist massive open online courses). We argue that this conception of learning is inadequate and problematic, and we propose that cultural psychology is best suited to address the explanatory challenges that Web 2.0 poses on learning, and therefore, it is also best suited to provide massive open online courses with more adequate and less problematic pedagogy. We suggest two initial and general pedagogical principles based on cultural psychology upon which to begin building this new pedagogy for massive open online courses.
Color atlas of endodontics

Chapter 1 Diagnosis and Treatment Planning Chapter 2 Access Opening Chapter 3 Length Determination Chapter 4 Canal Preparation Chapter 5 Rotary Canal Preparation Chapter 6 Sonic and Ultrasonics in Endodontics Chapter 7 Obturation Chapter 8 Retreatment Chapter 9 Restoration of the Endodontically Treated Tooth Chapter 10 Endodontic Surgery Chapter 11 Treatment of Traumatic Injuries Chapter 12 Legal Considerations in Endodontic Treatment
Combining IS Research Methods: Variety Is (Not) the Spice of Life

This research in progress paper reports the results of a survey of the main IS journals to discover the extent of research that uses multiple methods. The preliminary results show that such multimethod research is rare, and where it does occur generally consists only of a survey combined with interviews/case studies. A more detailed discussion of the methodology and results will be available at the conference.
A NOVEL RANGE -FREE LOCALIZATION SCHEME FOR WIRELESS SENSOR NETWORKS

This paper present a low-cost yet effective localization scheme for the wireless sensor networks. There are many studies in the literature of locating the sensors in the wireless sensor networks. Most of them require either installing extra hardware or having a certain amount of sensor nodes with known positions. The localization scheme we propose in this paper is range-free, i.e., not requiring extra hardware devices, and meanwhile it only needs two anchor nodes with known position. Firstly, we install the first anchor node at the lower left corner (Sink X) and the other anchor node at the lower right corner (Sink Y). Then we calculate the minimum hop counts for each unknown node to both Sink X and Sink Y. According to the minimum hop count pair to Sink X and Sink Y of each node, we can virtually divide the monitored region into zones. We then estimate the coordinate of each sensor depending on its located zone. Finally, we adjust the location estimation of each sensor according to its relative position in the zone. We simulate our proposed scheme and the well-known DV-Hop method. The simulation results show that our proposed scheme is superior to the DV-Hop method under both low density and high density sensor deployments.
An application of XML to the creation of an interactive resource for authentic language learning tasks

There has of late been a call among language practitioners for the sophisticated new markup language XML to be used in Web-based tools for language learning (Mills, 1999; Riley, 2001; Godwin-Jones, 2000). This paper describes just such an application: the development of an interactive electronic resource book of learning tasks for English Language Teaching (ELT). The electronic resource book incorporates an authenticity-centred approach to language learning materials design, viz language learning based on authentic texts complemented by authentic tasks. The paper covers a general introduction to XML, describes the pedagogical model (i.e. the authenticity-centred approach) that it was used to realise, and describes the development of the XML-based system operating the electronic resource book. Among the conclusions of this paper are that this trial application reveals XML to be ideally suited to the realisation of such pedagogical models and that its greatly enhanced information management and linking potential promises an exciting future in the field of language teaching by providing the possibility for pedagogy-led technology rather than technology-led pedagogy.
A robotic brain scheme: proposal originated by a modular robotic control

A robot brain scheme has been implemented, based on and controlled by analog circuits and micro-controllers. The modules have been classified as: a world signal processing, b world signal relevance assessing, c pre-motor decisions, d motor behavior, and e planning and sequencing motor behaviors. There are two types of pre-motor processing: main and world signal tracking. Motor behavior includes all the final motion units. Each of these five classes roughly corresponds to areas in a vertebrate's brain and proved to be an effective robotic brain scheme as they assist in the development of greater complexity in robotic brains and a means to compare different implementations. The scheme stresses the importance of motor behavior modules fed by pre-motor decision modules. The pre-motor decision modules aim the movement while the motor behavior module creates the behavior. Finally, the planning and sequencing modules are imperative implementations in a robotic brain.