Miracle-dz/UniFAR-FTUs huggingface dataset:
The origins and development of community radio in Britain under New Labour (1997-2007)

This thesis is a study of the origins and development of Community Radio in the United Kingdom under New Labour, focusing on the decade that saw Tony Blair serving as Prime Minister between 1997 and 2007. The research contributes to an enhanced understanding of Community Radio in Britain during this period, in two ways. First, it provides a factual contribution – namely, it places into the public domain hidden testimonies and evidence about how Community Radio developed. On the basis of a sample of stations, it uses case studies to examine how, if at all, New Labour policies affected actual practice on the ground. Second, it attempts to provide an intellectual argument – namely, that Community Radio in Britain today can be understood fully only in the wider context of New Labour’s period in office. While Part I of the thesis focuses on the ideals of community radio advocacy, community media theories, British local radio practice and New Labour’s social and cultural policies, Part II discusses the realities and how the community radio sector developed its policy proposals and practices after 1997. The evolution of Community Radio is studied using a mix of qualitative methods, including the review of a consistent body of ‘grey literature’, informal data gathering, oral history interviews, and a period of observational research in a selection of three case-studies: ALL FM (Manchester), Forest FM (Verwood), and Canterbury Student Radio-CSR FM (Canterbury). The original contribution to knowledge that this thesis makes, is to demonstrate how the most important factor facilitating community radio lobbying in this period was the presence of a discourse within which the arguments of community media activists could make sense, and that led to the introduction of Community Radio as a third sector of full-time radio broadcasting in the United Kingdom.
A Popular Education Handbook. An Educational Experience Taken from Central America and Adapted to the Canadian Context.

In this booklet two members of a Canadian educational development organization share their experiences during 1983 in trying to adapt the popular education they had experienced in Central America to the Canadian context. The guide is organized in five chapters. Chapter 1 defines popular education and describes its characteristics and the role of the popular educator. Chapter 2 provides three program examples of popular education: a workshop for teachers about popular education in Central America, a workshop on workins people in Canada and Central America, and a workshop on popular education for community groups. Techniques for building a popular education program are shared in Chapter 3. They include sculpturing, sociodrama, role play, drawing, and songwriting. Chapter 4 contains exercises to help the group process, such as ice breakers, group building, and relaxa+ion. Finally. Chapter 5 explains how to develop resources--in this case, a slide show--and describes four slide-tape shows produced by Rick Arnold and Bev Burke about Central America. A bibliography completes the guide, which is amply illustrated with black-and-white photographs and drawings. (KC) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ***********************************************************************
Shadow Queue Based Fair Scheduling in Multi-Hop Wireless Networks

we study the problem of flow based scheduling in multi-hop wireless networks. And propose a Max Flows First-Shadow queue based Congestion Control (MFF-SCC) algorithm for combined scheduling and congestion control that aims to solve max-min fairness problem. We give out detailed analysis of the algorithm and also conduct simulations to verify its performance. The results of simulations indicate that the proposed approach can improve fairness of scheduling.
Biological inspired pose-invariant face recognition

A small change in image will cause a dramatic change in signals. Visual system needs to ignore these changes, yet specific enough to perform recognition. Problem intended to be solved is on 2D translation and scaling invariances and 3D pose invariance without imposing strain on memory and with biological justification. In this paper, we propose a novel biologically inspired vision model for pose-invariant face recognition. The model can be divided into lower and higher visual stages. Lower visual stage models the visual pathway from retina to the striate cortex (V1), whereas the modeling of higher visual stage mainly based on current psychophysical. The feasibility of the proposed model is evidenced by the evaluation study using FERRET face database.
Relative clause based text simplification for improved English to Hindi translation

Language translation is one of the most research and development oriented topic in today's world because of its increasing demand and application. Knowledge of grammar structure of source and target languages is must for translating one language to other. Clauses are an integral part of any language and helps in constructing complex sentences in different contexts. This complication leads to a low score of translation in almost every machine translation engine existing in the world. In this work, we are focusing on relative clause identification and extraction for text simplification. The generated simple sentences are then fed to the existing translation engines for translation. Link Parser based parsing techniques are used to parse the sentence tree. In this work we have focused on achieving better quality of English-Hindi translations. The proposed approach is tested manually on a sufficiently large dataset and shows promising and better translation score than the conventional approaches.
Automatic segmentation of bladder layers in Optical Coherence Tomography images using graph theory and dynamic programming

Segmentation of anatomical and pathological structures in bladder wall images is crucial for diagnosis and study of bladder diseases. Manual segmentation, which is commonly used in this field, is often a time-consuming and subjective process. Those methods that have proposed normally are not suitable for bladder wall SDOCT (Spectral Domain Optical Coherence Tomography) images, although they do have really good effect in ophthalmic images. This paper presents an automatic approach for segmenting normal adult pig's bladder wall layers whose structure is similar to people's bladder wall in SDOCT images using graph theory and dynamic programming. Several other algorithms are implemented to segment the same images in order to compare the effect. The results show that our method accurately segments three bladder wall layer boundaries in normal pig bladder and significantly reduces the processing time required for image segmentation and feature extraction.
User-centric pre-selection and scheduling for coordinated multipoint systems

The data traffic volumes are constantly increasing in cellular networks. Furthermore, a larger part of the traffic is generated by applications that require high data rates. Techniques including Coordinated Multipoint transmission (CoMP) can increase the data rates, but at the cost of a high overhead. The overhead can be reduced if only a subset of the users is served with CoMP. In this paper, we propose a user selection approach, including pre-selection of CoMP users and short term scheduling, that takes user requirements into account. Users that require a high data rate to reach an acceptable level of service satisfaction are selected to use coherent joint processing CoMP in some of their downlink transmission bandwidth. Simulation results show that both the number of satisfied users and fairness are improved with the proposed user selection as compared to user selection that does not consider individual user requirements.
Detection of a Moving Source in Speckle Noise. Application to Exoplanet Detection

Astronomical instruments able to detect the direct light of extra solar planets are currently under development. This paper focuses on instruments that will acquire a set of successive images where the planet (the source in more general purposes) moves in a known manner on a speckled background. Performant signal processing tools are required to account for the very low signal-to-noise ratio of the data. In the astrophysical context, the background arises mainly from the light scattered by the parent star. An accurate-but general-data model has been proposed in previous works to statistically describe optical images taking into account the spatial correlation of the wavefront complex amplitude. First, an estimator of the position and the intensity of the potential source is proposed. Because of several kinds of numerical constraints, it is derived from a simplified Gaussian data model. Under reasonable constraints on the motion of the source, the estimators are proved to be consistent, even under the accurate data model. For the detection test, we propose to threshold a linear statistics that arises from the intensity estimation. The threshold needs to be precisely related to the probability of false alarm (PFA) and the probability of detection (PD). Under the detailed model, the distribution of the data is only reachable through its moment generating function. We propose therefore to estimate analytically PFA and PD using the saddlepoint approximation. To evaluate the quality of these estimations, a Monte Carlo analysis is applied to monodimensional simulated data. The saddlepoint approximation proves to be very accurate, unlike the Gaussian approximation or even a low-order Gram-Charlier series approximation.
Challenges in the context-aware management of business processes: a multiple case study

Current conceptualizations of organizational processes consider them as internally optimized yet static systems. Still, turbulences in the contextual environment of a firm often lead to adaptation requirements that these processes are unable to fulfil. Based on a multiple case study of the core processes of two large organizations, we offer an extended conceptualisation of business processes as complex adaptive systems. This conceptualization can enable firms to optimise business processes by analysing operations in different contexts and by examining the complex interaction between external, contextual elements and internal agent schemata. From this analysis, we discuss how information technology can play a vital goal in achieving this goal by providing discovery, analysis, and automation support. We detail implications for research and practice.
Semantical Expansion of Two-Level Boolean Formulas for Minimisation

Semantical expansion aims at boosting minimisation heuristics for Boolean formulas. It provides an easy way of deciding whether or not a given minterm, resp. clause, can be added safely to a formula in DNF, resp. CNF. We suggest to use incremental and complete SAT solvers and instances of UNSAT for these decisions, and report on some preliminary empirical results.
Financial market development and economic growth in Hong Kong: a Post-Keynesian approach

[Extract] Recent years have witnessed an increasing interest in the role of the financial sector in economic development. In the aftermath of the financial crises of 1997–98, it is becoming increasingly clear that a sound understanding of the interaction between financial markets and real sector is essential for economic growth and long-term prosperity. This clearly calls for further research on this important issue. The objective of this study is to examine the role of financial market development in producing a virtuous circle of high aggregate demand in Hong Kong. In this study, first, we develop a long run macroeconomic framework, following Onaran and Stockhammer (2003), which is a dynamic Post Keynesian and open economy model. Second, we account for economic theory by developing structural VAR format. The empirical analysis of this study provides insights into the functioning of the Hong Kong macroeconomy, and by investigating the dynamic responses of the model to shocks in indicators of financial development and determining whether the effects of such shocks on the long run relations disappear.
Interplay between population firing stability and single neuron dynamics in hippocampal networks

Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi. org/10.7554/eLife.04378. 001
Cooperative Behaviour of Location Aware Nodes in Ad-hoc Networks

This paper presents a method for packet delivery around voids in ad-hoc networks that use geographic forwarding. The use of local cooperative behaviours to transport packets around network voids features no global coordination. By changing goals, an individual node can create or join in a transient group that generates and holds local knowledge of the void, and which triggers modified behaviour for packet delivery. It is envisaged that additional behaviours may be developed to handle network operation at multiple protocol layers.
A technical study and analysis on fuzzy similarity based models for text classification

In this new and current era of technology, advancements and techniques, efficient and effective text document classification is becoming a challenging and highly required area to capably categorize text documents into mutually exclusive categories. Fuzzy similarity provides a way to find the similarity of features among various documents. In this paper, a technical review on various fuzzy similarity based models is given. These models are discussed and compared to frame out their use and necessity. A tour of different methodologies is provided which is based upon fuzzy similarity related concerns. It shows that how text and web documents are categorized efficiently into different categories. Various experimental results of these models are also discussed. The technical comparisons among each model's parameters are shown in the form of a 3-D chart. Such study and technical review provide a strong base of research work done on fuzzy similarity based text document categorization.
Optimizing portfolio construction using artificial intelligence

The aim of this research is to enhance the practicability of Artificial Intelligence using Neural Network (NN) in the actual market. This paper generalized the standard Markowitz Theory's Efficient Frontier to mimic and optimise the portfolio construction and develop a neural network heuristic to better understand the chemistry of how Artificial Intelligence can construct optimal portfolio ability and provide advantages to all levels of investors.
Study of SIR for designing filters with arbitrary resonant positions

Stepped impedance resonators are a structure consisting of several transmission lines with different admittances. They are used for control the spurious response and insertion loss of filters by changing the impedance/admittance ratio of the stepped impedances. The multiple mode resonator, which is implemented in form of stepped impedance resonator, can be used, either to widen pass/stop bands or to separate pass bands and stop bands from each other. In this work, we study a stepped impedance structure consisting of two transmission line segments, which have the general form of arbitrary ratio between the admittances and arbitrary ratio of lengths. We observe the appearance and movement of the resonances and verify them through computer simulation in microstrip technology. Variation of these ratios lead to appearance and moving of resonant positions. This approach was numerically verified by means of computer simulation with a commercial software. The accuracy of the predicted resonant positions is very good, i.e. about 48 MHz at 4.6 GHz and about 76 MHz at 6.8 GHz.
COP: To compress and protect main memory

Protecting main memories from soft errors typically requires special dual-inline memory modules (DIMMs) which incorporate at least one extra chip per rank to store error-correcting codes (ECC). This increases the cost of the DIMM as well as its power consumption. To avoid these costs, some proposals have suggested protecting non-ECC DIMMs by allocating a portion of memory space to store ECC metadata. However, such proposals can significantly shrink the available memory space while degrading performance due to extra memory accesses. In this work, we propose a technique called COP which uses block-level compression to make room for ECC check bits in DRAM. Because a compressed block with check bits is the same size as an uncompressed block, no extra memory accesses are required and the memory space is not reduced. Unlike other approaches that require explicit compression-tracking metadata, COP employs a novel mechanism that relies on ECC to detect compressed data. Our results show that COP can reduce the DRAM soft error rate by 93% with no storage overhead and negligible impact on performance. We also propose a technique using COP to protect both compressible and incompressible data with minimal storage and performance overheads.
Financial valuation and optimal strategy for retirement benefits in a jump diffusion model

We consider a defined benefit pension plan with the option of early retirement in a jump-diffusion model. The retirement benefits depend on the salary at the time of retirement, but with guaranteed minimum. The underlying salary follows a jump-diffusion process. In this note, we study the financial valuation of the retirement benefits and discuss the optimal retirement strategy. The valuation of retirement benefits can be characterized as the solution of an optimal stopping time problem. It is also related to a variational inequality or a free boundary problem of an integro-differential operator of the parabolic type. We prove that the valuation of the retirement benefits is the unique solution of the variational inequality and derive some properties of the free boundary, which correspond to the optimal retirement strategy.
Close target reconnaissance using autonomous UAV formations

In this paper the problem of close target reconnaissance by a formation of 3 unmanned aerial vehicles (UAVs) is considered. The overall close target reconnaissance (CTR) involves subtasks of avoiding obstacles or no-fly-zones, avoiding inter-agent collisions, reaching a close vicinity of a specified target position, and forming an equilateral triangular formation around the target. The UAVs performing the task fly at constant speeds. A decentralized control scheme is developed for this overall task considering unidirectional sensing/control architecture. Relevant analysis and simulation test results are provided.
Molecular and morphological evaluation of the aphid genus Hyalopterus Koch (Insecta: Hemiptera: Aphididae), with a description of a new species

Aphids in the genus Hyalopterus Koch (Hemiptera: Aphididae) are pests of stone fruit trees in the genus Prunus globally, causing damage directly through feeding as well as transmission of plant viruses. Despite their status as cosmopolitan pests, the genus is poorly understood, with current taxonomy recognizing two, likely paraphyletic, species: Hyalopterus pruni (Koch) and Hyalopterus amygdali (Blanchard). Here we present a systematic study of Hyalopterus using a molecular phylogeny derived from mitochondrial, endosymbiont, and nuclear DNA sequences (1,320 bp) and analysis of 16 morphometric characters. The data provides strong evidence for three species within Hyalopterus, which confirms previous analyses of host plant usage patterns and suggests the need for revision of this genus. We describe a new species H. persikonus Miller, Lozier & Foottit n. sp. , and present diagnostic identification keys for the genus.
Crystal Structures of Archaemetzincin Reveal a Moldable Substrate-Binding Site

Background Archaemetzincins are metalloproteases occurring in archaea and some mammalia. They are distinct from all the other metzincins by their extended active site consensus sequence HEXXHXXGXXHCX4CXMX17CXXC featuring four conserved cysteine residues. Very little is known about their biological importance and structure-function relationships. Principal Findings Here we present three crystal structures of the archaemetzincin AfAmzA (Uniprot O29917) from Archaeoglobus fulgidus, revealing a metzincin architecture featuring a zinc finger-like structural element involving the conserved cysteines of the consensus motif. The active sites in all three structures are occluded to different extents rendering the enzymes proteolytically inactive against a large variety of tested substrates. Owing to the different ligand binding there are significant differences in active site architecture, revealing a large flexibility of the loops covering the active site cleft. Conclusions The crystal structures of AfAmzA provide the structural basis for the lack of activity in standard proteolytic assays and imply a triggered activity onset upon opening of the active site cleft.
Integrating Hot and Cool Intelligences: Thinking Broadly about Broad Abilities

Although results from factor-analytic studies of the broad, second-stratum abilities of human intelligence have been fairly consistent for decades, the list of broad abilities is far from complete, much less understood. We propose criteria by which the list of broad abilities could be amended and envision alternatives for how our understanding of the hot intelligences (abilities involving emotionally-salient information) and cool intelligences (abilities involving perceptual processing and logical reasoning) might be integrated into a coherent theoretical framework.
BPROMPT: a consensus server for membrane protein prediction

Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner. ac.uk/BPROMPT.