Miracle-dz/UniFAR-FTUs huggingface dataset:
The hermeneutics of symbolical imagery in Shakespeare's sonnets

This thesis aims at studying the symbolical imagery of Shakespeare’s Sonnets in the light of modern theories on the imaginary, symbolism, and myth put forward by authors such as C.G. Jung, P. Ricoeur, and G. Durand. It attempts at showing a part of Shakespeare’s creative process by identifying personal myths, recurrent images, as well as archetypes and archetypal patterns inherent in the Sonnets. The work is divided into three chapters. The first chapter presents Shakespeare as a poet and summarizes some critical approaches and consequent problems that have been part of the Sonnets critical heritage. It also anticipates the discussion on the importance of the reader’s imaginary in the hermeneutic process. Chapter two is divided in two segments. The first, where I present the grounds on which myth, literature and symbols are related, as well as Ricoeur’s theory of the metaphor; and the second, that consists of general imaginary symbolic data about the 154 sonnets, approached through a modernized version of the 1609 Quarto. In addition, there comes the analysis of sonnets 28 and 146, as models for the others to come in chapter 3. Finally, chapter three The Hermeneutics of Symbolical Imagery in Shakespeare’s Sonnets, displays the study of recurrent images, archetypes, archetypal patterns and personal myths within Shakespeare’s Sonnets. The Conclusion reflects upon the work’s attempt at showing the importance of symbolic images for the study of the sonnets, as well as considers some of the ways through which the imaginary of the writer and that of the reader bind, generating meaning.
Bagged ensembles with tunable parameters

Ensemble learning is a popular classification method where many individual simple learners contribute to a final prediction. Constructing an ensemble of learners has been shown to often improve prediction accuracy over a single learner. Bagging and boosting are the most common ensemble methods, each with distinct advantages. While boosting methods are typically very tunable with numerous parameters, to date, the type of flexibility this allows has been missing for general bagging ensembles. In this paper, we propose a new tunable weighted bagged ensemble methodology, resulting in a very flexible method for classification. We explore the impact tunable weighting has on the votes of each learner in an ensemble and compare the results with pure bagging and the best known bagged ensemble method, namely, the random forest.
Microsimulation of Child Benefits: A Review of Studies

: This paper reviews studies that use static non-behavioural microsimulation models of taxes and benefits in the analysis of child benefits. The studies are categorised into four groups according to the main topic of enquiry: the estimation of benefit incidence, the analysis of actual reforms, the importation of policies from other countries and freestyle reforms. The methods for measuring social welfare used in these studies are summarised. Additionally, a brief overview of the research using static behavioural, dynamic, and spatial models is provided. The paper discusses the main findings and recommends directions for further research
Two-stage Method for Millimeter Wave Channel Estimation

The millimeter wave is a promising technique for the next generation of mobile communication. The large antenna array is able to provide sufficient precoding gain to overcome the high pathloss at millimeter wave band. However, the accurate channel state information is the key for the precoding design. Unfortunately, the channel use overhead and complexity are two major challenges when estimating the channel with high-dimensional array. In this paper, we propose a two-stage approach which reduces the channel use overhead and the computational complexity. Specifically, in the first stage, we estimate the column subspace of the channel matrix. Based on the estimated column subspace, we design the training sounders to acquire the remaining coefficient matrix of the column subspace. By dividing the estimation task into two stages, the training sounders for the second stages are only targeted for the column subspace, which will save the channel uses and the computational complexity as well.
Support Vector Machines for Object Based Building Extraction in Suburban Area using Very High Resolution Satellite Images, a Case Study: Tetuan, Morocco

Many fields of artificial intelligence have been developed such as computational intelligence and machine learning involving neural networks, fuzzy systems, genetic algorithms, intelligent agents and Support Vector Machines (SVM). SVM is a machine learning methodology with great results in image classification. In this paper, we present the potential of SVMs to automatically extract buildings in suburban area using Very High Resolution Satellite (VHRS) images. To achieve this goal, we use object based approach: Segmentation before classification in order to create meaningful image objects using color features. In the first step, we form objects with the aid of mean shift clustering algorithm. Then, SVM classifier was used to extract buildings. The proposed method has been applied on a suburban area in Tetuan city (Morocco) and 83.76% of existing buildings have been extracted by only using color features. This result can be improved by adding other features (e.g., spectral, texture, morphology and context).
Intergenerational transmission of health care habits in France

This article explores the intergenerational transmission of health care habits and the related differences in terms of health care and prevention use. Our study is based on a sample of 4 613 individuals who answered the 2010 French Health, Health Care and Insurance Survey and completed the specific questions about health care and prevention use and living conditions during childhood. Results provide evidence of an intergenerational transmission of health care preferences. More precisely, we show a transmission of health care habits and an influence of parental habits during childhood on the conditional number of general practitioner and specialist visits and on the use of preventive health service namely colon cancer screening. We also find a long term influence of maternal education on the use of smear test. This study shows the long term influence of social background and parental habits on adulthood health care use, which contributes to the intergenerational transmission of health inequalities.
Improved Clustering of Documents using K-means Algorithm

With the huge upsurge in information, it has become difficult to gather relevant information within the limited time. Hence clustering methods are introduced to ease the task of gathering the relevant information in a cluster. Efficiency of clustering therefore becomes one of the crucial requirements to be met by the clustering methods. There are several methods and algorithms have been introduced. Hierarchical clustering is often portrayed as the better quality clustering approach, but it is limited because of its time complexity. In contrast, K-means and its variants have a time complexity which is linear in the number of documents. A clustering method based on the hidden semantics within the documents is proposed here for better results. The proposed method extracts features from the web documents using conditional random fields and builds a linguistic topological space based on the associations of features. The features that are used this method are TF (Term Frequency) and IDF (Inverse Document Frequency). Both TF and IDF values are best in reflecting the importance of the document in the given context. Then the documents are clustered based on the K-means clustering after finding the topics in the documents using these features. The advantage of K-means method is that it produces tighter clusters than hierarchical clustering, especially if the clusters are globular. Keywords— Document clustering, TF, IDF, K-means, cosine similarity, heirarchichal clustering.
A comparison between virtual code management techniques

During the past decade (2000 to 2010) , the multi / many core architectures have seen a renaissance, due to the insatiable appetite for performance. Limits on applications and hardware technologies have put a stop to the frequency race in 2005. Current designs can be divided into homogeneous and heterogeneous ones. Homogeneous designs are the easiest to use since most toolchain components and system software do not need too much of a rewrite. On the other end of the spectrum, there are the heterogeneous designs. These designs offer tremendous computational raw power, but at the cost of losing hardware features that might be necessary or even essential for certain types of system software and programming languages. An example of this architectural design is the Cell B.E. processor which exhibits both a heavy core and a group of simple cores designed to be its computational engine. Recently, this architecture has been placed in the public eye thanks to being a central component into one of the fastest super computers in the world. Moreover, it is the main processing unit of the Sony’s Playstation 3 videogame console; the most powerful video console currently in the market. Even though this architecture is very well known for its accomplishments, it is also well known for its very low programmability. Due to this lack of programmability, most of its system software efforts are dedicated to increase this feature. Among the most famous ones are ALF, DaCS, CellSs, the single source XL compiler, the IBM’s octopiler, among others. Most of these frameworks have been designed to support (directly or indirectly) high level parallel programming languages. Among them, there is an effort called Open OPELL from the University of Delaware. This toolchain / framework tries to bring the OpenMP parallel programming model (De facto shared memory parallel programming paradigm) to the Cell B.E. architecture. The OPELL framework is composed of four components: a single source toolchain, a very light SPU kernel, a software cache and a partition / code overlay manager. This extra layer increases the system’s programmability,
STEREO CORRESPONDENCE BASED ON MULTIRESOLUTION ANALYSIS

Disparity estimation from stereo imagery has gained substantial interest of research community from its commencement with the recent trend being the use of multiresolution methods. Existing multiresolution based methods generally rely on approximate band based matching neglecting other subbands that carry high-frequency information. Present research is an effort to find a multiresolution based stereo correspondence method that effectively uses the high and low-frequency subbands in multiple resolutions, bridges the gap between feature-based and area-based matching by incorporating the vast feature space of multiresolution and develops an optimum approach between global and local area-based methods in terms of accuracy, implementation and computational complexity. As a response to the lack of exploration of different multiresolution based stereo, a novel comprehensive comparison framework is proposed to evaluate different multiresolution based disparity estimation methods. Extensive qualitative and quantitative results with detailed analysis have been provided to support the claims of the work.
The Oxford Junior Dictionary

A completely revised and updated edition of the very popular starter dictionary for ages 7+. This edition contains more headword entries, additional meanings, and more example sentences; new words from maths, science, other cultures, etc.; new appendices of weights and measures, countries, shapes, numbers, days of the week, and months of the year; and a new layout to make the dictionary easier to use. This book is intended for interest age: 7+
Fast image mosaic algorithm based on the improved Harris-SIFT algorithm

This paper proposes a fast image mosaic algorithm based on the improved Harris-SIFT algorithm, according to such problems as more memory consumption, greater redundancy quantity of feature points, slower operation speed, and so on, resulting from using the SIFT algorithm in the image matching stage of the image mosaic process. Firstly in the matching stage of the algorithm, the corner point is extracted by using the multi-scale Harris, feature descriptor is constructed by the 88-dimensional vector based on the SIFT feature, the coarse matching is carried out by the nearest neighbor matching method, and then the precise matching point pair and image transformation matrix are obtained by the RANSAC method. The seamless mosaic can be achieved by using the weighted average image fusion. The experimental results show that this algorithm can not only achieve precise seamless mosaic but also improve operation efficiency, compared with the traditional algorithm.
An Approach for Predicting Clinical EEG Signal Based on SVM

Accurate modeling of Electroencephalography (EEG) signals is an important problem in clinical diagnosis of brain diseases. The method using support vectors machine (SVM) based on the structure risk minimization provides us an effective way of learning machine. But solving the quadratic programming problem for training SVM becomes a bottle-neck of using SVM because of the long time of SVM training. In this paper, a local-SVM method is proposed for modeling EEG signals. The local method is presented for improving the speed of the prediction of EEG signals. Furthermore, this proposed model is used to detect epilepsy from EEG signals in which dynamical characteristics are difference between normal and epilepsy EEG signals. The experimental results show that the training of the local-SVM obtains a good behavior. In addition, the local SVM method significantly improves the prediction and detection precision.
Multisystemic Treatment of Substance Abusing and Dependent Juvenile Delinquents: Effects on School Attendance at Posttreatment and 6-Month Follow-Up

The effectiveness of multisystemic therapy (MST) in promoting school participation among substance abusing and dependent juvenile offenders with high rates of psychiatric comorbidity was examined. Youth were randomly assigned to receive MST versus usual community-based services. Results indicated that MST (but not usual services) significantly increased school attendance at posttreatment, and that these treatment gains were maintained at the 6-month follow-up assessment. Explanations for the findings and directions for future research are discussed.
Vector-based semantic analysis: representing word meanings based on random labels

Vector-based semantic analysis is the practice of representing word meanings as semantic vectors, calculated from the co-occurrence statistics of words in large text data. This paper discusses the theoretical presumptions behind this practice, and a representational scheme based on the Distributional Hypothesis is identified as the rationale for vector-based semantic analysis. A new method for calculating semantic word vectors is then described. The method uses random labelling of words in narrow context windows to calculate semantic context vectors for each word type in the text data. The method is evaluated with a standardised synonym test, and it is shown that incorporating linguistic information in the context vectors can enhance the results.
Development and Practice of Design Guidelines for e-Learning Materials in Blended Learning for Chinese as a Second Foreign Language

* 東北大学大学院教育情報学研究部・教育部(Graduate‌School‌of‌Educational‌Informatics,Tohoku‌University) ** 東北学院大学教養学部(Tohoku‌Gakuin‌University‌Faculty‌of‌Liberal‌Arts) *** 東北大学高等教育開発推進センター(Center‌for‌the‌Advancement‌of‌Higher‌Education,‌Tohoku‌University) **** 東北大学教育情報基盤センター(Center‌for‌Information‌Technology‌in‌Education,Tohoku‌University) 受付日:2013 年 5月 6日;再受付日:2013 年 7月 31日;採録日:2013 年 9月 10日 第二外国語としての中国語学習のためのブレンディッド ラーニングにおける e ラーニング教材設計指針の 作成と実践 趙 秀敏,冨田 昇,今野 文子,朱 嘉琪,稲垣 忠, 大河 雄一,三石 大
The Relationship Between Personality Traits and Social Media Use

Existing literature has previously highlighted the effects of the dimensions of the Big Five Model of personality on social media use. The present study aims to investigate the influence of these personality factors on social media use, thus expanding on the previous research. A questionnaire based, quantitative design was adopted. Participants, recruited from the general population (N = 81), were requested to complete a report, providing the relevant demographic information, the Big Five Personality Questionnaire and The Social Media Use Questionnaire, taking approximately 5-10 minutes. Spearman’s rho correlation revealed a positive relationship between extraversion and social media use, negative relationships between the predictor variables of conscientiousness, neuroticism and age with social media use. Results further revealed non-significant differences in levels of openness to new experience and agreeableness regarding the use of social media. How the implications of this study may be of benefit to educators, marketers and advertisers, and politicians are discussed.
The first evaluation of glucose-6-phosphate dehydrogenase deficiency (G6PD) gene mutation in malaria-endemic region at South Central Timor (SCT) district, Eastern Indonesia 2015-2016

Primaquine (PQ) is the only licensed drug effective against P. vivax for specific hypnozoites and as a key drug in the malaria elimination stage. However, PQ can cause severe hemolysis in G6PD deficient individuals. Unfortunately, few epidemiological data of these disorders was in Indonesia. This study aimed to assesses the prevalence and genotyping variant of G6PDd among the people on malaria-endemic. Blood samples from 555 unrelated subjects in eastern Indonesia were for G6PDd by quantitative test and PCR-RFLP-DNA sequencing. All protocols followed by Promega, Madison, USA. The prevalence of malaria and anemia was 32.6% (181/555) and 16% (89/555) with P. vivaxdominant species 52.5% (95/181), respectively. Overall, 16.6% (92/555) subjects were G6PD deficient, including 58.7% (54/92) females and 41.3% (38/92). Among the 92 cases G6PD deficient molecularly studied, the genotype variant Vanua Lava (T10883C) were detected dominant and unknown G6PD deficient (T-13.154-C) in 3 cases. It was high G6PD deficient in eastern Indonesia indicate that diagnosis and management of G6PD deficient are necessary. Obligatory anti-malaria doses for G6PD deficient individuals, population screening, are needed on endemic malaria in eastern Indonesia.
Volatility Spillover Among Industries in the Capital Market in Iran

Measuring the dynamic relationship between banking and industries with systemic importance has attracted much attention after the recent financial crisis. This paper examines the dynamic conditional correlations and volatility spillover using three popular multivariate GARCH models in the twelve-year period (from the beginning of 2005 to the beginning of 2016) among the fourteen systemically important industries in Iran’s capital market. The purpose of this study is to understand and identify the volatility spillover between industries to predict financial fluctuations, as well as policy decisions and risk management. The results of this study confirm the spillover between “Banking” and the five industries of "Basic Metals", "Industrial Multidisciplinary", "Investments", "Computers", and "Transportation & Warehousing". There is also an asymmetric spillover between “Banking” index and the "Chemical Industry", the "Extraction of Metal Ores", "Pharmaceuticals" and "Communications Devices". The results are used for mapping fundamental analysis and risk programming.
Computer Modeling and Simulation of Ultrasonic Signal Processing and Measurements

The system for simulation, measurement, and processing in Graphical User Interface implementation is presented. The received signal from the simulation is compared to that of an actual measurement in the time domain. The comparison of simulated, experimental data clearly shows that acoustic wave propagation can be modeled. The feasibility has been demonstrated in an ultrasound transducer setup for material property investigations. The results of simulation are compared to experimental measurements. The simulation result has good agreement with the experimental data which confirms the validity of the model. The simulation tool therefore provides a way to predict the received signal before anything is built. Furthermore, the use of an ultrasonic simulation package allows for the development of the associated electronics to amplify and process the received ultrasonic signals. Such a virtual design and testing procedure not only can save us time and money, but also can provide better understanding on design failures and allow us to modify designs more efficiently and economically.
Stereopolis II: A multi-purpose and multi-sensor 3D mobile mapping system for street visualisation and 3D metrology

Nous presentons dans cet article un systeme de numerisation mobile 3D hybride laser-image qui permet d’acquerir des infrastructures de donnees spatiales repondant aux besoins d’applications diverses allant de navigations multimedia immersives jusqu’a de la metrologie 3D a travers le web. Nous detaillons la conception du systeme, ses capteurs, son architecture et sa calibration, ainsi qu’un service web offrant la possibilite de saisir en 3D via un outil de type SaaS (Software as a Service), permettant a tout un chacun d’enrichir ses propres bases de donnees a hauteur de ses besoins. Nous abordons egalement l’anonymisation des donnees, a savoir la detection et le floutage de plaques d’immatriculation, qui est est une etape inevitable pour la diffusion de ces donnees sur Internet via des applications grand public.
Why most domain models are aspect free

DISCLAIMER This is not a paper against aspects. In fact, I take my hat off to the people who have given us ASPECTJ and all the other excellent tools that have made AOP become reality and let us all find out for ourselves what aspects can do for us. This is not even a paper against aspect-oriented modelling. Quite the contrary: the way we model today (and presumably also the way we will model tomorrow) is inherently aspectoriented, and the development of reliable weaving techniques is—in my view—at the core of MDA. It is however a paper against the belief that the aspects of AOP are modelling concepts that—on the same level as classes, attributes, and methods—are readily identified in every problem domain if only one looks at it with the right glasses on.