bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Ashes Series
Authors: Bilal Wafaa 
Published: January 2019

Abstract
The Ashes Series depicts the suffering of war not through human displays of emotion, but rather through the absence of human life in once occupied homes. It investigates the impact of the destruction of these private, domestic spaces in war and media images of such destruction. These intimate spaces are literally ripped open and become public through external violence and the act of destruction. The images exist in the aftermath of atrocity, with the presence of the human spirit represented only by the monochromatic whiteness of the ashes. The Ashes Series represents the artist’s attempt to make sense of destruction and to preserve the moment of serenity after the dust has settled: to give the ephemeral moment extended life in a mix of beauty and violence.
A Stuck Place
Authors: Aiello Rosa 
Published: January 2019

Abstract
An excerpt about living together from a near-future dystopian novel, Calypso’s Way. In the cosmology of the novel feudalism, expanded family collectivities, and organized crime co-exist. Smoke appears, like a minor character in the story, to indicate events that once occurred in a corner of the fictional world where domesticity is urgent, grave, and incessant, and characters survive by performing the tasks of the everyday. If the work stops, then what?
BEBERAPA MODIFIKASI PADA ALGORITMA KRIPTOGRAFI AFFINE CIPHER
Authors: Wijayanti Dian Eka 
Published: January 2019

Affine Cipher Cryptography Technique is one of the techniques in classical cryptography which is quite simple so it is very vulnerable to cryptanalysis. Affine cipher's advantage is having an algorithm that can be modified with various techniques. The modifications that can be made to Affine Cipher is to combine Affine cipher's algorithm with other ciphers, replace Affine cipher's key with various functions and matrices and expand the space for plaintext and ciphertexts on Affine cipher. Affine cipher can also be applied to the stream cipher as a keystream generator. This research discusses several modifications of Affine cipher algorithm and performs several other modifications. These modifications are combining Affine Chiper and Vigenere Cipher on , combining Affine, Vigenere and Hill Cipher with invertible matrix applications on . Furthermore, a comparison of the three modifications will be carried out to obtain a new cryptographic method that is more resilient to the cryptanalysis process.
MODEL REGRESI LINIER BAYESIAN DENGAN APLIKASI PADA DATA PENUNDAAN PENERBANGAN
Authors: Lestari Vemmie Nastiti , Subanar Subanar 
Published: January 2019

Bayesian linear regression is an approach to linear regression where statistical analysis depend of Bayesian inference. The Bayesian model on big data uses a summary of data statistics as input; Statistical summary can be calculated from each subset, then a statistical summary of the full dataset is obtained from the sum of the summary statistics for each subset. Recent developments in data science and research, produce large datasets that are too large to be analyzed as a whole due to the limitations of computer memory or storage capacity. To overcome this, a program package was introduced from R namely BayesSummaryStatLM for the Bayesian linear regression model with the Markov Chain Monte Carlo implementation that overcomes this limitation. Then the program package from R, ff is used to read data in large datasets while calculating statistics summary. In this study Bayesian linear regression model used with several choices of prior distribution for unknown model parameters, and illustrates in simulation data and real datasets for flight delay data in US 2008. The application of simulation data and flight delay data produces a plot of density functions for the β parameters has a shape resembling a plot of Normal distribution density function, whereas for plot parameters the density function has a shape resembling the plot of Inverse Gamma distribution density function. In the simulation data, the estimator for each parameter produced has a value that approach to the value of the specified parameter (True Value). This is also indicated by the narrow credible interval for each parameters.
Translanguaging instead of standardisation: Writing Romani at school
Authors: Heltai János Imre 
Published: January 2019

AbstractIn most public education in the western world the existence of a standardized language variety is still regarded as a precondition of teaching writing. This stance generates a problem in situations where no standardized variety matches the children’s home language practices and no traditions of an extended and standardised literacy exist. Roma students in Hungary have to acquire writing skills in the majority language (Hungarian), since the teaching of writing cannot rely on a standardized Romani language. In this way, school writing activities seem unrelated to the local discoursal practices of their own community. This puts Romani-speaking children at a disadvantage in learning to write, and reduces their chances of academic success. This paper reports on an ongoing project in Tiszavasvári, Hungary, designed to offer an alternative to approaches that wish to eliminate the disadvantages of Roma students by creating a standardized language. It explores the possibility of applying a translanguaging approach to the teaching of writing, arguing that if teachers allow students to draw on their local Romani-bounded non-standardised language practices, including the grassroots literacy activities occurring in the community, their general writing skills can be improved. For this to happen, teachers must be trained in translanguaging pedagogy, so that they can transcend the boundaries staked out by monolingual ideologies. The hitherto prevailing view that posits an indissoluble connection between standard, school and writing should be set aside. It should also be realized that general linguistic competences can, and should, be separated from language-specific competences. A key endeavour of the Tiszavasvári project has been to convert teachers to the translanguaging stance, and some promising signs can be reported. The introduction of local translanguaging practices into the teaching of writing fostered new learning practices among the students and began to change the pedagogical stance of teachers participating in the project.
Stability analysis of a rotationally restrained microbar embedded in an elastic matrix using strain gradient elasticity
Authors: Yayli Mustafa Özgür 
Published: January 2019

Abstract
The buckling of rotationally restrained microbars embedded in an elastic matrix is studied within the framework of strain gradient elasticity theory. The elastic matrix is modeled in this study as Winkler’s one-parameter elastic matrix. Fourier sine series with a Fourier coefficient is used for describing the deflection of the microbar. An eigenvalue problem is obtained for buckling modes with the aid of implementing Stokes’ transformation to force boundary conditions. This mathematical model bridges the gap between rigid and the restrained boundary conditions. The influences of rotational restraints, small scale parameter and surrounding elastic matrix on the critical buckling load are discussed and compared with those available in the literature. It is concluded from analytical results that the critical buckling load of microbar is dependent upon rotational restraints, surrounding elastic matrix and the material scale parameter. Similarly, the dependencies of the critical buckling load on material scale parameter, surrounding elastic medium and rotational restraints are significant.
Parallel real-world LU decomposition: Gauss vs. Crout algorithm
Authors: Stabrowski Marek 
Published: January 2019

Abstract
This paper presents numerical experiments with assorted versions of parallel LU matrix decomposition algorithms (Gauss and Crout algorithm). The tests have been carried out on the hardware platform with fourcore Skylake processor featuring hyperthreading technology doubling virtually core number. Parallelization algorithms have been implemented with the aid of classic POSIX threads library. Experiments have shown that basic 4-thread acceleration of all parallel implementations is almost equal to the number of threads/processors. Both algorithms are worth considering in real-world applications (Florida University collection). Gauss algorithm is a better performer, with respect to timing, in the case of matrices with lower density of nonzeros, as opposed to higher density matrices. The latter are processed more efficiently with the aid of Crout algorithm implementation.
Transparency as Ideology, Ideology as Transparency: Towards a Critique of the Meta-aesthetics of Neoliberal Hegemony
Authors: Valdovinos Jorge I. 
Published: January 2019

Abstract
Along with the increasing commodification of all aspects of culture and the persistent aestheticisation of everyday life under late capitalism, there is an equally increasing longing for objectivity, immediacy, and trust. As the mediation of our everyday experiences augments, a generalised feeling of mistrust in institutions reigns; the sense of a need to bypass them increases, and the call for more “transparency” intensifies. As transparency manages to bypass critical examination, the term becomes a source of tacit social consensus. This paper argues that the proliferation of contemporary discourses favouring transparency has become one of the fundamental vehicles for the legitimation of neoliberal hegemony, due to transparency's own conceptual structure-a formula with a particularly sharp capacity for translating structures of power into structures of feeling. While the ideology of transparency promises a movement towards the abolition of unequal flows of information at the basis of relations of power and exploitation, it simultaneously sustains a regime of hyper-visibility based on asymmetrical mechanisms of accountability for the sake of profit. The solution is not “more” transparency or “better” information, but to critically examine the emancipatory potential of transparency at the conceptual level, inspecting the architecture that supports its parasitic logic.
Beyond Emotion: Empathy, Social Contagion and Cultural Literacy
Authors: Crawshaw Robert 
Published: January 2019

Abstract
This paper reviews the implications for research in cultural literacy of the current hypothesis that revolutionary advances in communication technology are inseparable from an over-reliance on emotion, both in the representation of global disaster and human suffering and as a means of manipulating public behaviour in the political and commercial spheres. It explores the view that feeling has become a simulacrum or form of “hyperreality” whose “contagion” through targeted exploitation is an obstacle to deeper understanding of social processes. It summarises the challenges which this presents for research into the nature of cultural literacy by critically considering three current paradigms: affect theory, clinical psychology including neuroscience, and memetics with due regard for recent attempts to model social behaviour through computer-based simulation. Its conclusions are that historical comparisons between past and present of the processes whereby cultural artefacts mediate emotion, combined with highly contextualised empirical fieldwork into their contemporary impact, should be key foci of critical research into cultural literacy, using the full range of technological instruments available.
Major food groups contributing to sodium intake in school-attending adolescents
Authors: Pinto Rafael Lavourinha , de Souza Bárbara da Silva Nalin , Pereira Rosangela Alves , Sichieri Rosely , Yokoo Edna Massae 
Published: January 2019

Abstract

Background
Excessive sodium intake is a risk factor for developing systemic arterial hypertension. Increased blood pressure during childhood increases the risk of hypertension in adulthood. Assessing sodium intake across different eating places is important, as the meals offered in different places can influence dietary quality.

Objective
This study aimed to assess the contribution of different food groups to the mean of sodium intake of school-attending adolescents in the city of Niterói, a metropolitan area of Rio de Janeiro, Brazil.

Subjects
A total of 347 public school students aged between 10 and 18 years participated in the study.

Methods
Food consumption was based on two 24-h dietary recalls. The reported items were grouped into 31 food groups and the percentage of contribution of each food group to total mean sodium intake was estimated. Sodium intake according to eating place was also estimated.

Results
The food groups mostly contributing to total sodium intake were rice, beans, savory biscuits, breads, beef, poultry, processed meat, filled cookies, pasta and potatoes. The highest sodium intake within the food groups occurred at home, except for savory biscuits and pizza, which showed a higher sodium intake percentage at school. Savory biscuits were the third-most consumed item contributing to the total sodium intake and were the main source of sodium when consumed at school (48.9%).

Conclusion
Most sodium intake stemmed from ultra-processed food consumed at school. Therefore, actions to promote healthy eating habits within the school environment are necessary.
Engineering Flat Gain Tunable Raman-Parametric Hybrid L-Band Amplifier for Narrow Band Multi-Channel Terabits System
Authors: Kaur Gaganpreet 
Published: January 2019

Abstract
We present a model of a Raman-parametric hybrid amplifier for flat gain amplification of narrowband Dense Wavelength Division Multiplexed (DWDM) terabits capacity system. In the proposed configuration Raman pump has been cascaded with one – pump parametric amplifier. While Raman amplifier typically uses a long length single mode fiber as a gain medium, the Fiber Optical Parametric Amplifiers (FOPA) uses a small length of Highly Non-Linear Fibers (HNLF). This allows for maximum optimization of the gain achieved using Raman as well as parametric processes. We focus on the signal degradation due to non-linear crosstalk arising because of multi-pump configuration, in particular, due to the generated idlers within the operational bandwidth. As the channel spacing is reduced, fiber non-linearities increase significantly. The dilemma to use the fewer number of high powered pumps Vs, the use of increased number of relatively low powered pumps has been investigated for DWDM system. The optimization of the pump powers has been evaluated in terms of signal degradation, gain, gain variation and OSNR. It has been demonstrated that a maximum gain of 45.38 dB for 96×40 Gbps, 25 GHz system is attainable up to 200 km of transmission distance while maintaining OSNR>18 dB using the proposed hybrid. No gain compensation or gain optimization technique has been used. The findings of this work establish flat gain in narrowband DWDM systems is achievable through proper optimization of pump wavelengths and their powers.
Ideals and congruences in pseudo-BCH algebras
Authors: Walendziak Andrzej 
Published: January 2019

Abstract
We introduce the concept of a translation ideal in pseudo-BCH algebras and investigate its properties. We prove that for any pseudo-BCH algebra 𝔛 there is a one-to-one order-preserving correspondence between the closed translation ideals of 𝔛 and the relative congruences on 𝔛.
Uniqueness and periodicity for meromorphic functions with partial sharing values
Authors: Lin Weichuan , Chen Shengjiang , Gao Xiaoman 
Published: January 2019

AbstractWe prove a periodic theorem of meromorphic functions of hyper-orderρ2(f) < 1. As an application, we obtain the corresponding uniqueness theorem on periodic meromorphic functions. In addition, we show the accuracy of the results by giving some examples.
Mild solution of stochastic partial differential equation with nonlocal conditions and noncompact semigroups
Authors: Zhang Xuping , Chen Pengyu , Abdelmonem Ahmed , Li Yongxiang 
Published: January 2019

Abstract
The aim of this paper is to discuss the existence of mild solutions for a class of semilinear stochastic partial differential equation with nonlocal initial conditions and noncompact semigroups in a real separable Hilbert space. Combined with the theory of stochastic analysis and operator semigroups, a generalized Darbo’s fixed point theorem and a new estimation technique of the measure of noncompactness, we obtained the existence of mild solutions under the situation that the nonlinear term and nonlocal function satisfy some appropriate local growth conditions and a noncompactness measure condition. In addition, the condition of uniformly continuity of the nonlinearity is not required and also the strong restriction on the constants in the condition of noncompactness measure is completely deleted in this paper. An example to illustrate the feasibility of the main results is also given.
The convergence-theoretic approach to weakly first countable spaces and symmetrizable spaces
Authors: Chigr Fadoua , Mynard Frédéric 
Published: January 2019

Abstract
This article fits in the context of the approach to topological problems in terms of the underlying convergence space structures, and serves as yet another illustration of the power of the method. More specifically, we spell out convergence-theoretic characterizations of the notions of weak base, weakly first-countable space, semi-metrizable space, and symmetrizable spaces. With the help of the already established similar characterizations of the notions of Frchet-Ursyohn, sequential, and accessibility spaces, we give a simple algebraic proof of a classical result regarding when a symmetrizable (respectively, weakly first-countable, respectively sequential) space is semi-metrizable (respectively first-countable, respectively Fréchet) that clarifies the situation for non-Hausdorff spaces. Using additionally known results on the commutation of the topologizer with product, we obtain simple algebraic proofs of various results of Y. Tanaka on the stability under product of symmetrizability and weak first-countability, and we obtain the same way a new characterization of spaces whose product with every metrizable topology is weakly first-countable, respectively symmetrizable.
Effect of ZnSO4 fertilizer on soil chemical properties, performance and proximate quality of sweet potato in a derived savanna ecology of Nigeria
Authors: Adekiya A.O. , Aboyeji C.M. , Agbede T.M. , Dunsin O. , Adebiyi O.T.V. 
Published: January 2019

Abstract
Micro-nutrients especially zinc can not only increase the yield of sweet potato but can also improve the quality of tubers. Hence, experiments were carried out in 2015 and 2016 cropping seasons to determine the impact of various levels of ZnSO4 fertilizer on soil chemical properties, foliage and storage root yields and proximate qualities of sweet potato (Ipomoea batatas L.). The experiments consisted of 5 levels (0, 5, 10, 15 and 20 kg ha-1) of ZnSO4 fertilizer. These were arranged in a randomized complete block design and replicated three times. ZnSO4 increased (with the exception of P) soil chemical properties compared with the control. N, K, Ca, Mg and Zn were increased up to the 20 kg ha-1 ZnSO4 level in both years. ZnSO4 reduced P concentrations in soil as the level increased. For sweet potato performance, 5 kg ha-1 ZnSO4 fertilizer had the highest values of foliage yield (vine length and vine weight) and storage root yield. Using the mean of the two years and compared with the control, ZnSO4 fertilizer at 5 kg ha-1 increased storage root yield of sweet potato by 17.4%. On fitting the mean storage root yield data of the two years with a cubic equation, the optimum rate of Zn for sweet potato was found to be 3.9 kg ha-1 to achieve the maximum sweet potato yield. In this study, relative to the control, ZnSO4 fertilizer increased moisture and decreased the fibre contents of sweet potato. There were no consistent patterns of variation between the 5, 10, 15 and 20 kg ha-1 ZnSO4 treatments for proximate qualities except that the highest values of fat, protein, carbohydrate and ash was at 5 kg ha-1 ZnSO4.
Fast recognition method of moving video images based on BP neural networks
Authors: Shao Yu , Witarsyah Deden 
Published: January 2019

Abstract
At present, the accuracy of real-time moving video image recognition methods are poor. Also energy consumption is high and fault tolerance is not ideal. Consequently this paper proposes a method of moving video image recognition based on BP neural networks. The moving video image is divided into two parts: the key content and the background by binary gray image. By collecting training cubes. The D-SFA algorithm is used to extract moving video image features and to construct feature representation. The image features are extracted by collecting training cubes. The BP neural network is constructed to get the error function. The error signal is returned continuously along the original path. By modifying the weights of neurons in each layer, the weights propagate to the input layer step by step, and then propagates forward. The two processes are repeated to minimize the error signal. The result of image feature extraction is regarded as the input of BP neural network, and the result of moving video image recognition is output. And fault tolerance in real-time is better than the current method. Also the recognition energy consumption is low, and our method is more practical.
Compressed sensing image restoration algorithm based on improved SURF operator
Authors: Zhou Guodong , Zhang Huailiang , Lucas Raquel Martínez 
Published: January 2019

Abstract
Aiming at the excellent descriptive ability of SURF operator for local features of images, except for the shortcoming of global feature description ability, a compressed sensing image restoration algorithm based on improved SURF operator is proposed. The SURF feature vector set of the image is extracted, and the vector set data is reduced into a single high-dimensional feature vector by using a histogram algorithm, and then the image HSV color histogram is extracted.MSA image decomposition algorithm is used to obtain sparse representation of image feature vectors. Total variation curvature diffusion method and Bayesian weighting method perform image restoration for data smoothing feature and local similarity feature of texture part respectively. A compressed sensing image restoration model is obtained by using Schatten-p norm, and image color supplement is performed on the model. The compressed sensing image is iteratively solved by alternating optimization method, and the compressed sensing image is restored. The experimental results show that the proposed algorithm has good restoration performance, and the restored image has finer edge and texture structure and better visual effect.
Localization and recognition algorithm for fuzzy anomaly data in big data networks
Authors: Zhang Huajie , Zhang Sen , Hanafiah Marlia Mohd 
Published: January 2019

Abstract
In order to accurately detect the fuzzy anomaly data existing in big data networks, it is necessary to study the localization and recognition algorithm. The current algorithms have problems related to poor noise reduction, low recognition efficiency, high energy consumption and low accuracy. A novel localization and recognition algorithm for fuzzy anomaly data in big data networks is proposed. The multi-wavelet denoising method is used to remove the noise signals existing in the network. The k-means algorithm is utilized for network clustering, and the association mode between nodes and the unitary linearity regression model is adopted to eliminate spatially and temporally redundant data that exist in big data networks. The similarity anomaly detection method based on multi-feature aggregation identifies fuzzy anomaly data existing in big data networks, establishes an anomaly data localization model, and completes the localization and recognition of fuzzy anomaly data. Experimental results show that the proposed method has good noise reduction, high recognition efficiency, low energy consumption and high accuracy of localization and recognition.