Miracle-dz/UniFAR-FTUs huggingface dataset:
Tetanus death and aerobics: the evaluation of disease-specific public health interventions.

This paper provides a theoretical and empirical investigation of the positive complementarities between disease-specific policies introduced by competing risks of mortality. The incentive to invest in prevention against one cause of death positively on the level of survival from other causes. This means that a specific public health intervention has benefits other than the direct medical reduction in mortality: it affects the incentives to fight other diseases so the overall reduction in mortality will in general be larger than the predicted by the direct medical effects. We discuss evidence of these cross-disease effects by using data on neo-natal tetanus vaccination through the Expanded Programme on Immunization of the World Health Organization. (authors)
Independent Verification and Validation ( IV & V ) Techniques for Object Oriented Software Systems

This paper presents an Independent Verification and Validation (IV&V) framework for the emerging use of Object Oriented (OO) techniques for large-scale NASA systems. The paper is focused on use case analysis. IV&V is most beneficial if the analysis is performed during early phases of the software development. This paper presents IV&V framework with an emphasis on use case prioritization and use case complexity analysis techniques. A full report by authors [4] describes a complete set of suggested techniques for use case analysis.
Determinant of Health Development Performance after Decentralization and Regional Autonomy Program in West Nusa Tenggara Indonesia

The objective of this study is to verify factors contributing to the improvement of health status in West Nusa Tenggara. In addition, this paper is also intended to analyze dominant factors influencing health development since the initiation of decentralization and regional autonomy program. Data used in the analysis consist of secondary data (time series) over the period of 2000-2011. Data are obtained from various sources and have been documented and published. Several variables identified as variables that affect the performance of health development consist of education, economic, infrastructure, and health resources variable. Each variable is categorized as latent variable in which each variable has its own indicators. Collected data will be analyzed using quantitative analysis by applying structural equation models (SEM) with Partial Least Square (PLS). The result findings indicate that health performance is influenced simultaneously by variables including in the model such as social, economic, infrastructure, and health resources. The dominant factors influencing health development are social and economic factor representing the willingness to pay and the ability to pay for health services. Keywords: health development performance, decentralization, structural equation modelling, willingness to pay, ability to pay.
Online stability validation using sector analysis

Our previous work has explored the use of compositional stabilization techniques for embedded flight control software[9] based on passivity properties of controller components and systems. Zames[21] presented a compositional behavior-bounding technique for evaluating stability of nonlinear systems based on real intervals representing cones (sectors) that bound possible component behaviors. Many innovations in control theory have developed from his insights. We present a novel use of his sector bound theory to validate the stability of embedded control implementations online. The sector analysis can be implemented as a computationally efficient check of stability for different parts of a control design. The advantage of the online application of this technique is that it takes into account software platform effects that impact stability, such as time delays, quantization, and data integrity. We present a brief overview of the sector concept, our compatible control design approach, application of the technique to model-based embedded control software design, an example of its use to find design defects, and insights that may be drawn from our investigation so far. In the present work we only consider software (discrete-time) control of nonlinear continuous-time systems without switching.
The Nature of the Red Giant Branches in the Ursa Minor and Draco Dwarf Spheroidal Galaxies

Spectra for stars located redward of the fiducial red giant branches (RGBs) of the Ursa Minor and Draco dwarf spheroidal galaxies have been obtained with the Hobby‐Eberly telescope and the Marcario Low Resolution Spectrometer. From a comparison of our radial velocities with those reported in previous medium‐resolution studies, we find an average difference of 10 km s−1 with a standard deviation of 11 km s−1. On the basis of these radial velocities, we confirm the membership of five stars in Ursa Minor and find two others to be nonmembers. One of the confirmed members is a known carbon star that lies redward of the RGB; three others are previously unidentified carbon stars. The fifth star is a red giant that was found previously by Shetrone and coworkers to have [Fe/H] = -1.68 ± 0.11 dex. In Draco, we find eight nonmembers, confirm the membership of one known carbon star, and find two new members. One of these stars is a carbon star, while the other shows no evidence for C2 bands or strong atomic bands, although the signal‐to‐noise ratio of the spectrum is low. Thus, we find no evidence for a population of stars more metal‐rich than [Fe/H] ≃ -1.45 dex in either of these galaxies. Indeed, our spectroscopic survey suggests that every candidate suspected of having a metallicity in excess of this value based on its position in the color‐magnitude diagram is, in actuality, a carbon star. Based on the census of 13 known carbon stars in these two galaxies, we estimate the carbon star specific frequency to be ϵdSph≃2.4 × 10-5 L-1V,⊙, 25–100 times higher than that of Galactic globular clusters.
EM-based Channel Estimation for Space Time Block Coded MIMO OFDM Systems

We propose a channel estimation technique based on an expectation maximization (EM) algorithm, for space-time block coded (STBC) multi-input multi-output (MIMO) OFDM systems. The channel estimation is done by decomposing the superimposed received signals, into their signal components and estimating the channel parameters of each signal component separately
A comparative study of linear encoding in Genetic Programming

Genetic Programming is a widely used technique to solve many optimization problems. The original representation of a solution is a tree structure. To improve its search capability there are many proposals for encoding data structure of a solution of Genetic Programming as a linear code. However there are a few work in comparing between these proposals. This work presents a systematic way to compare three popular techniques for linear encoding in Genetic Programming. They are Linear Genetic Programming, Gene Expression Programming and Multi-Expression Programming. Ten problems in Symbolic Expressions are defined and are used as benchmarks to compare the effectiveness of these proposals against the baseline standard Genetic Programming. The metrics of comparison are the Success Rate and the absolute error. The discussion and comparison of the strength and weakness of each method are also presented.
Wide Area Network Fault Detection and Routing Model for Wireless Sensor Networks

In a wireless sensor network (WSN), random occurrences of faulty nodes degrade the quality of service of the network. In this paper, we propose efficient fault detection and routing (EFDR) scheme to manage a large size WSN. The faulty nodes are detected by neighbor node’s temporal and spatial correlation of sensing information and heart beat message passed by the cluster head. In EFDR scheme, three linear cellular automata (CA) are used to manage transmitter circuit/ battery condition/microcontroller fault, receiver circuit fault and sensor circuit fault representation. On the other hand, Lsystem rules based data routing scheme is proposed to determine optimal routing path between cluster head and base station. The proposed EFDR technique is capable of detecting and managing the faulty nodes in an efficient manner.
Sparse representation shape model

This paper introduces a novel shape model, Sparse Representation Shape Model (SRSM). Rather than for modeling specific deformable shapes, this model is specially designed for shape segmentation and matching. This model is utilized under the framework of Active Shape Models (ASM). Unlike the Linear Point Distribution Model utilized by original ASM, which relies on obscure statistical boundary to do shape regularization, SRSM distinctly distinguishes valid shape information and errors contained in input candidate shape from structure and by making use of sparse representation, SRSM could acquire the maximum valid shape information, and hence could achieve optimal shape regularization. Further-more, through exploiting the reliability information of each landmark, SRSM can be improved further to form Weighted SRSM, which is much more evident and accurate.
Making the Case for Campus Mediation

Organizers of college and university mediation programs commonly face the task of having to "sell" the concept of mediation services to reluctant administrators. In this article, I briefly present a range of rationales that I have used with some success to make the case for campus mediation. As each campus setting is different, program developers will have to pick and choose among these strategies based on their situation and the style and personality of the particular administrators with whom they are dealing.
An unsupervised approach for comparing styles of illustrations

In creating web pages, books, or presentation slides, consistent use of tasteful visual style(s) is quite important. In this paper, we consider the problem of style-based comparison and retrieval of illustrations. In their pioneering work, Garces et al. [2] proposed an algorithm for comparing illustrative style. The algorithm uses supervised learning that relied on stylistic labels present in a training dataset. In reality, obtaining such labels is quite difficult. In this paper, we propose an unsupervised approach to achieve accurate and efficient stylistic comparison among illustrations. The proposed algorithm combines heterogeneous local visual features extracted densely. These features are aggregated into a feature vector per illustration prior to be treated with distance metric learning based on unsupervised dimension reduction for saliency and compactness. Experimental evaluation of the proposed method by using multiple benchmark datasets indicates that the proposed method outperforms existing approaches.
A three-phase adaptive phase-locked loop scheme for utility grid-connected systems

This paper deals with a phase-locked loop (PLL) algorithm for both phase-angle and frequency detections in three-phase utility grid connected systems. The proposed algorithm uses non-autonomous adaptive filters (AFs) for extracting the fundamental components of the utility voltages, while a positive sequence detector (PSD) is employed for obtaining the positive sequence components at fundamental utility frequency. Both the AFs and the PSD operate in conjunction with a three-phase power-based PLL (3pPLL) yielding the scheme called AF-PSD-3pPLL. Therefore, power quality problems that interfere on the PLL performance are mitigated, such as voltage harmonics and unbalances. The performance of the proposed AF-PSD-3pPLL algorithm is evaluated by means of experimental tests considering utility disturbances, such as voltage harmonics, voltage unbalances, and voltage sags.
Regularized resolution enhancement of point-based features of synthetic aperture radar image using variable quasi-norm

Nonquadratic regularization with lp quasi-norm has been widely used as an efficient and powerful tool for resolution enhancement of point-based features of synthetic aperture radar (SAR) images. However, adjustment of the lp quasi-norm usually requires a lot of time and labor. In this paper, we propose a modified model and method for choosing regularization term. Considering the sparseness of scatterers in the scene of a SAR image, we use the generalized Gaussian distributions (GGD) as prior distributions for sampled scattering field. Our regularization model is constructed based on variable lp quasi-norms, and the selection of lp quasi-norm is achieved through estimation of the shape parameter p of the GGD by adopting a moment method. The regularization model leads to an alternating iterative algorithm. Experimental results with simulated and real data show that the method can automatically select regularization term and produce SAR images with improved spatial resolution.
Autism risk factors: genes, environment, and gene-environment interactions

The aim of this review is to summarize the key findings from genetic and epidemiological research, which show that autism is a complex disorder resulting from the combination of genetic and environmental factors. Remarkable advances in the knowledge of genetic causes of autism have resulted from the great efforts made in the field of genetics. The identification of specific alleles contributing to the autism spectrum has supplied important pieces for the autism puzzle. However, many questions remain unanswered, and new questions are raised by recent results. Moreover, given the amount of evidence supporting a significant contribution of environmental factors to autism risk, it is now clear that the search for environmental factors should be reinforced. One aspect of this search that has been neglected so far is the study of interactions between genes and environmental factors.
Boosted human head pose estimation using kinect camera

Head pose estimation is essential for several computer vision applications. For example, it has been employed in facial expression recognition, head gesture detection, and driver monitoring systems. In this work, we present a boosted method to estimate the head pose using Kinect camera. This estimation is cooperatively performed with the help of RGB and depth images. The human face is located in the RGB image using frontal and profile Viola-Jones (VJ) face detector, where the depth information is used to confine the size and location of the search window. Appearance features, extracted from the detected face patch in the RGB image and its corresponding in the depth image, are passed to Support Vector Machine (SVM) regressors to infer the head pose. Evaluation on two public benchmark databases demonstrates that our proposed approach compares favorably to state-of-the-art approaches.
Managing Interactions between Technological and Stylistic Innovation in the Media Industries

The processes of technological innovation have been widely researched, but their interactions with another type of innovation that is particularly important in sectors like the fashion and the media content industries have been neglected: stylistic innovation. This paper puts forward the idea that a better understanding of such interactions between content and technology in the media industries might help explaining differences in the receptiveness of firms towards new technological opportunities. The nature of the interactions, so it is argued in this paper, depends on three groups of key factors at the level of the product, the organization and the industry: among them, first, the locations of the different types of innovation in the media product's components; second, organizational factors like the identity and the reputation of a firm with respect to the above types of innovation; and third, the industry-specific characteristics of the certification environment in which the firms operate. Awards are discussed as specific instantiations of micro certification environments indicating quality with respect to stylistic and/or technological product features. To round off the theoretical part, a definition of stylistic innovation is developed with reference to the key concepts discussed in this paper. Within the media sector the literary publishing industry has been chosen to provide the subject of the empirical part. Two cases related to the introduction of eBook technology are presented: one is a study of the first digital literary publisher in Europe and the other is a case study of the first international eBook award, which mixes technological and stylistic criteria. Theory and cases lead to a number of hypotheses offered as potential departure points for future research into the interactions between innovation in style and technology.
Lower Bounds on the Complexity of Solving Two Classes of Non-cooperative Games

This paper studies the complexity of solving two classes of non-cooperative games in a distributed manner in which the players communicate with a set of system nodes over noisy communication channels. The complexity of solving each game class is defined as the minimum number of iterations required to find a Nash equilibrium (NE) of any game in that class with $\epsilon$ accuracy. First, we consider the class $\mathcal{G}$ of all $N$-player non-cooperative games with a continuous action space that admit at least one NE. Using information-theoretic inequalities, we derive a lower bound on the complexity of solving $\mathcal{G}$ that depends on the Kolmogorov $2\epsilon$-capacity of the constraint set and the total capacity of the communication channels. We also derive a lower bound on the complexity of solving games in $\mathcal{G}$ which depends on the volume and surface area of the constraint set. We next consider the class of all $N$-player non-cooperative games with at least one NE such that the players' utility functions satisfy a certain (differential) constraint. We derive lower bounds on the complexity of solving this game class under both Gaussian and non-Gaussian noise models. Our result in the non-Gaussian case is derived by establishing a connection between the Kullback-Leibler distance and Fisher information.
The Public Policy Process

The Public Policy Process is essential reading for anyone trying to understand the process by which public policy is made. Explaining clearly the importance of the relationship between theoretical and practical aspects of policy making, the book gives a thorough overview of the people and organisations involved in the process. Fully revised and updated for a seventh edition, The Public Policy Process provides: • Clear exploration, using many illustrations, of how policy is made and implemented. • A new chapter on comparative theory and methods. • New material on studying advocacy coalitions, policy changes, governance and evaluation. • More European and international examples
Essays on Value Creation and Appropriation in Human-Capital-Intensive Firms.

s from team-based creation of products. In reality, however, both individuals and teams create products in firms. In part, data constraints guided the choice to focus solely on individuals. From the available data, it is difficult to tease out an individual’s contribution to a team’s performance. Focusing on individuals ensures a clear mapping between their performance and subsequent actions. With more fine-grained data about the
Multilane Racetrack caches: Improving efficiency through compression and independent shifting

Racetrack memory (RM), a spintronic domain-wall non-volatile memory has recently received attention as a high-capacity replacement for various structures in the memory system from secondary storage through caches. The main advantage of RM is an improved density and like other non-volatile memory structures, the static power of RM is dramatically lower than conventional CMOS memories. However, a major challenge of employing RM in universal memory components is the added access latency and dynamic energy consumption caused by shifts to align the data of interest with an access port. We propose multilane Racetrack caches (MRC), a RM last level cache design utilizing lightweight compression combined with independent shifting. MRC allows cache lines mapped to the same Racetrack structure to be accessed in parallel when compressed, mitigating potential shifting stalls in the RM cache. Our results demonstrate that unlike previously proposed RM caches, an isocapacity MRC cache replacement can outperform SRAM caches while providing energy improvement over STT-MRAM caches. In particular, MRC improves performance by 5% and reduces energy by 19% compared to an isocapacity baseline RM cache resulting in an energy delay product improvement of 25%.
Brave New Workplace: How Individual Contracts are Changing Our Jobs

Purpose – The purpose of this paper is to bridge the knowledge management (KM) and strategic business network literatures from the viewpoint of SMEs.Design/methodology/approach – This paper presents a typology of KM and strategic business networks; thus the paper is based on a literature review and analysis.Findings – The paper provides a typology of the strategic SME network types and their key KM challenges based on a synthesis of existing literature.Research limitations/implications – It is suggested that longitudinal case studies of KM practices in strategic SME networks should be conducted. An empirical multi‐case study has already been started.Originality/value – The presented SME network typology can benefit SME managers facing networking and KM challenges. Besides, it is suggested that a common strategy should be developed for all types of networks to enable the creation of knowledge‐based competencies and capabilities.
An In-depth Study of Map Reduce in Cloud Environment

Cloud computing has introduced an utility computing model which offers an alternative to traditional servers and computing clusters. Due to fault tolerance and scalability feature, Map Reduce distributed data processing architecture has now become the choice for data-intensive analysis in the clouds. Recently Mapruduce is used as a service or for setting up one's own Map reduce cluster. In this paper we evaluate the architecture and performance of different Map Reduce framework, such as AzureMapreduce built using the Microsoft Azure cloud infrastructure, Cloud Map Reduce(CMR) built on top of Amazon cloud OS. We belief that the techniques we discussed in this paper are general enough that would encouraged others to use them in other applications. Our survey would definitely open an promising approach to improve Map Reduce performance for Cloud Computing.