Reviewerly/exHarmony huggingface dataset:
Religious hate speech, libertà di religione e libertà di espressione. Intersezioni tra forma e sostanza dei diritti nella società multiculturale

SOMMARIO: 1. Premesse - 2. Un possibile modello alternativo di tutela: la forma della tutela - 3. Un possibile modello alternativo di tutela: la sostanza della tutela - 4. Alcuni casi pratici - 4.1. Il leader politico - 4.2. Il leader religioso - 5. Conclusioni.Religious hate speech, freedom of religion and freedom of expression. Reshaping the rights in the multicultural societiesABSTRACT: In the multicultural societies, lawyers are more and more often engaged in identifing useful tools to solve the rising conflicts between fundamental rights. The exercise of freedom of religion and freedom of expression can led into this kind of phenomena that could be taken into consideration by law, like hate speech and religious hate speech. The paper tries to approach two particular form of hate speech, the political and the religious one, to check if some alternative models of protection could be implemented to assure an effective protection of minorities without any sacrifice of individual fundamental rights.
A sparse Gaussian sigmoid basis function approximation of hyperspectral data for detection of solids

Abstract We define a new characterization of emissivity and reflectance curves for compositional exploitation of hyperspectral data. Our method decomposes each spectrum into a sparse set of Gaussian sigmoid components using penalized regression. Detection is based on the combination of Gaussian sigmoid components unique to a target material. Focusing on the presence of spectral upslopes and downslopes rather than spectral correlations makes detection more robust to both target variation and spectral variability from atmosphere and background encountered during the collection process. We present simulation studies that demonstrate the potential to reduce false positive rates without compromising sensitivity. Characterization of long‐wave infrared (LWIR) experimental data validates our method using minerals of different particle sizes, measurement angles, and collection conditions.
THE EFFECTIVENESS OF USING STORY PYRAMID STRATEGY TOWARD THE STUDENTS’ READING COMPREHENSION

Some problems are faced by students in reading of English text. Students are frustrated and bored when they do not understand what they are reading. The interesting strategy is needed to teach them. Story Pyramid Strategy is one of strategies to teach reading comprehension. This strategy forces students to review and summarize the main points of a story. This research is aimed at knowing the effectiveness of using story pyramid strategy in teaching narrative text toward students’ reading comprehension was conducted in this school. The research design of this reseacrh was quasi experimental research with quantitative approach. The research finding in this research showed the difference between the mean of students’ reading score when they are taught without using the story pyramid strategy (73.90) and when they are taught using story pyramid strategy (79.97).  The result of statistical computation using Independent Sample T-Test showed that the score of  tcount was (3.024) and ttable was (2.001). By comparing the “t” was tcount > ttable  known that (3.024 > 2.001). The significant value is 0.004 < 0.05. It was concluded that Story Pyramid Strategy is effective strategy in teaching narrative text toward students’ reading comprehension to junior high school.
From Macros to DSLs: The Evolution of Racket

The Racket language promotes a language-oriented style of programming. Developers create many domain-specific languages, write programs in them, and compose these programs via Racket code. This style of programming can work only if creating and composing little languages is simple and effective. While Racket's Lisp heritage might suggest that macros suffice, its design team discovered significant shortcomings and had to improve them in many ways. This paper presents the evolution of Racket's macro system, including a false start, and assesses its current state.
Compiling With Classical Connectives

The study of polarity in computation has revealed that an programming language combines both call-by-value and call-by-name evaluation; the two calling conventions are each ideal for half the types in a programming language. But this binary choice leaves out call-by-need which is used in practice to implement lazy-by-default languages like Haskell. We show how the notion of polarity can be extended beyond the value/name dichotomy to include call-by-need by adding a mechanism for sharing which is enough to compile a Haskell-like functional language with user-defined types. The key to capturing sharing in this mixed-evaluation setting is to generalize the usual notion of polarity shifts: rather than just two shifts (between positive and negative) we have a family of four dual shifts. We expand on this idea of logical duality---and is dual to or; proof is dual to refutation---for the purpose of compiling a variety of types. Based on a general notion of data and codata, we show how classical connectives can be used to encode a wide range of built-in and user-defined types. In contrast with an intuitionistic logic corresponding to pure functional programming, these classical connectives bring more of the pleasant symmetries of classical logic to the computationally-relevant, constructive setting. In particular, an involutive pair of negations bridges the gulf between the wide-spread notions of parametric polymorphism and abstract data types in programming languages. To complete the study of duality in compilation, we also consider the dual to call-by-need evaluation, which shares the computation within the control flow of a program instead of computation within the information flow.
Remote Expert Review System Research Based on Cloud Service Platform

The review of urban planning projects is an important task of the urban planning management. In order to solve problems of human and technology resources shortage, time consumption of review and just the inefficiency of review in the traditional projects review, this study uses the modern cloud service technique to build the remote expert review system. This paper mainly include the content of the research, the technical route, the cloud platform structure designing and the functional modules designing of the system, especially the studies of technical methods used in the cloud service platform.
LibGuides: Children Literature Genres: Poetry

This guide will help readers, educators, and parents identify common children literature genres so that the reading experience can be diversified by genre or to help readers figure out what genre they enjoy reading.
Efficient Outsourcing of Modular Exponentiations in Cloud Computing

Cloud computing is a user-centered computing service. A majority of cloud computing services are deployed through outsourcing. Modular exponentiation is one of the most complex computations in public key based cryptographic schemes. It is useful to reduce the computation cost of the clients by using outsourcing computation. In this paper, we propose an outsourcing algorithm for modular exponentiation by using the new mathematical division with two non-colluding cloud servers. The privacy is kept and the efficiency is improved.
Diseño del juego Yo Fantástico, para potenciar la autoestima en niños de 3 a 4 años

Self-esteem is one of the main factors for the child's development, being one of the basic qualities for success in the different relationships that it will generate in the course of his life, from a good deal in the social and personal environment, such as success in his academic and professional life.A union is made with play and fantasy as tools that connect the learning processes to elements of self-esteem, being an intrinsic aspect of children's growth and a catalyst for creation, liberation, and teaching of new daily knowledge by children. that are happening, that will facilitate the introspection of the factors that make up the self-esteem.This paper shows the proposal of products that will facilitate the process of enhancing self-esteem in children within their homes through a collaborative execution, this in order to re-empower parents in the process of teaching and living with their children.It is constructed through the methodology of Design focused on the human being and exploratory research.
Graph of Significant Terms for Source Code

When developers are tasked to modify source code of unknown systems, they have to employ considerable time and effort in activities for understanding the system implementation and locate units of source code. This work proposes a graph that supports the localization of directories which hold significant terms based on their frequency, using criteria of organization of source code directories. Popular open source projects were analyzed, the results show relevant features of visualization and information.
Determinants of Economic Growth in Ethiopia: An Application of Autoregressive Distributed Lag Model (ARDL)

Ethiopia has grown on average 10 % annually for more than a decade and the country is the fifth fastest growing economy among the 188 IMF member countries. As such, growth in one sector of the economy does not automatically transform into equal benefits for the population. This study specified an empirical investigation of the relationship between the economic growth of Ethiopia and its determinant as studies in this area are inadequate. Alongside this backdrop, the data span for the study was the annual data from 1974 to 2013, and employed the Autoregressive Distributed Lag (ARDL) Approach to Co-integration. Error Correction Model (ECM) was used in order to examine the long-run and short run relationship between the dependent variable (real GDP) and its determinant independent variables.The findings of the bounds test confirmed that there was the steady long run association between the real GDP, Physical capital, human capital, export, foreign aid, external debt and inflation. Moreover, the empirical results reveal that physical capital, human capital, export, foreign aid and inflation were found the positive impact on economic growth both in the long run and short run, whereas external debt affects economic growth negatively but, statically significant both in the long run and short run. Conversely, the study reveals that total export of goods and service, foreign aid and inflation were statistically insignificant at 5% level on the GDP growth of Ethiopia in the long run.
Zero-shot transfer for implicit discourse relation classification

Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation. It becomes even more challenging by the fact that annotated training data exists only for a small number of languages, such as English and Chinese. We present a new system using zero-shot transfer learning for implicit discourse relation classification, where the only resource used for the target language is unannotated parallel text. This system is evaluated on the discourse-annotated TED-MDB parallel corpus, where it obtains good results for all seven languages using only English training data.
Track Reconstruction Using the Hough Transform at BESIII

In order to overcome the difficulties caused by the curling charged tracks in the BESIII drift chamber, we introduce a Hough-transform-based tracking algorithm, which is used as a supplementary method to find low transverse momentum tracks.The Hough transform is a mathematical method that can map hits in a detector to parameter space to find tracks globally.This tracking algorithm is implemented in the BESIII offline software system, and its performance is checked using both Monte Carlo and data.The results show that this tracking method improves reconstruction efficiency at the low transverse momentum region.
PENGUJIAN MOVING GRID PADA MEJA PEMERIKSAAN PESAWAT SINAR-X TOSHIBA DI INSTALASI RADIOLOGI RUMAH SAKIT ISLAM KLATEN

ABSTRACTMOVING GRID TESTING ON THE EXAMINATION TABLE TOSHIBAX-RAY UNIT IN RADIOLOGY INSTALLATION KLATEN ISLAMIC HOSPITALNurul Defri Zhairina 1), Siti Daryati 2)The research about the moving grid performance testing in Radiology Installation Klaten Islamic Hospital have been done using Toshiba X-ray unit. The moving grid has never been tested, both acceptance testing and routine performance evaluation since 2015 purchases. The frequency of using the moving grid is quite high. The purpose of this study was to know the result of moving grid testing. This research conducted in the examination room 2 in the Radiology Installation Klaten Islamic Hospital by putting the grid alignment test tool in the middle of examination table and bucky table with vertical X-ray tube. Three small holes are place toward the researcher. Then, do exposure with exposure factor of 55 kVp and 20 mAs to the third hole, the other hole is closed with lead Pb and do exposure to each hole. Do the processing and measure the optical density using densitometer three time each holes. From these result, data processing and analysis are carried out. The highest density should be on the third hole and getting decreases to the lateral. The measurement results of the average density value on the first hole has 2,59, on the second hole has 2,67, on the third hole has 2,63, on the fourth hole has 2,62, and the fifth hole has 2,66. The second hole has the highest density and the first hole has the lowest density. This means the moving grid is misalignment with the central rays. Keyword : moving grid, grid alignment test tool, density1)Student of Radiodiagnostic and Radiotherapy Technique, Health Polytechnique Departement, Health Ministry Semarang.2)Lecture Scientific of Radiodiagnostic and Radiotherapy Technique, Health Polytechnique Departement, Health Ministry Semarang.
Google fails in search for cold fusion

Scientists at Google and several research institutes in North America have reopened what they call the “cold case” of cold fusion.
Cruce de Fronteras en el Territorio Tecnológico: del Docente Analógico al Digital

Nowadays, digital literacy is very present in the educational pedagogical discourse, therefore, several initiatives have been implemented aimed at the integral development of digital competence. Action measures aimed at 4 levels of application, micro, professional, meso, and macro, in the training of students in teacher training, infrastructure centres and the implementation of educational policies governing this transformation. In response to the need to develop the new professional digital teaching, it’s presented this research study, which aims to publicize the opinions and perceptions of teachers on the degree of the technological domain in each of the areas that make up the digital competence. Data that, in turn, allow to speculate on the degree of consciousness-competence of the teacher, in order to be able to delimit and determine the different phases that integrate the process of digital literacy in the professional practice.
A Talent Assessment Model Based on Learning Behaviors and Patterns

Talent assessment is an important topic in various areas like enterprise management, education, and psychology. However, it is also a challenging topic as the conventional assessment methods and models are unsuitable for talent assessment due to the following two aspects: (i) domain-dependent. The assessment of talent is highly depended on a specific domain which requires a large volume of domain knowledge in the assessment model; and (ii) behavior-based (or pattern-based). The characteristics of talents are reflected by a wide range of factors like their behaviors (patterns), emotions, self-identities, and metacognition. In this paper, we propose a talent assessment model based on online learning behaviors and patterns by using fuzzy models. Specifically, we attempt to develop a talent assessment model by identifying their learning data as we believe that the learning behaviors in the online learning platforms like massive open online courses (MOOCs) can reflect some characteristics of talents. Furthermore, we discuss what are the data sources, the learning behaviors and the potential computational methods in this assessment model in details. In addition, the potential limitations and possible improvement plans are introduced.
Retrieval-Based Open-Domain Question Answering: Exploring The Impact on The Retrieval Component across Datasets

Open-domain question answering (QA) is an important step in Artificial Intelligence and its ultimate goal is to build a QA system that can answer any question posed by humans. The majority of the open-domain QA system is the retrieval-based open-domain QA system, which enables the retrieval component to retrieve relevant documents from a large-scale knowledge source to a question and the answer extraction component to extract the answer to this question based on retrieved documents. As the techniques of Deep Learning progressing significantly, many researchers tried to apply the neural reading comprehension (RC) model to serve the answer extraction component of the open-domain QA system. However, the performance of the neural RC model in open-domain QA is considerably worse than the performance of it in RC-style QA. Therefore, many works have focused on the neural RC model for addressing the performance gap, whereas the retrieval component of the open-domain QA system lacks equivalent attention. Some researchers have built the neural network based information retrieval (IR) models, but currently, it is still difficult for these neural IR models to directly retrieve documents from a large-scale knowledge source in open-domain QA. Hence, many works attempted to use neural IR models for re-ranking documents retrieved by the traditional but efficient IR models (e.g., TF-IDF, BM25) in open-domain QA. However, these works did not analyze the impact of different questions of QA datasets on traditional IR models. Thus, this research gap is the focus in this thesis. We conduct error analyses of questions of different QA datasets to figure out the error types of questions that have a negative impact on the traditional IR models. From the error analysis, we learn that different QA datasets have different impacts on the traditional IR models and are differently hard to be dealt with by the traditional IR models. Therefore, we propose hypotheses that might mitigate the negative impact of the error types of questions that are relatively harder to be handled by the traditional IR models. Furthermore, we perform experiments based on the methodologies that implement our hypotheses for figuring out the validity of these hypotheses. In conclusion, we believe that our work is a step forward to obtaining more insights into the retrieval component of the open-domain QA system and will contribute to the development of the retrieval component for a better open-domain QA system. Moreover, our work can give our users guidance on how to issue a more suitable question that can be processed by the open-domain QA system for giving a more accurate and better answer.
Classification of Distinct Plasmodium Species in Thin Blood Smear Images using Kapur Segmentation Strategy

Malaria is a mosquito-borne irresistible chronic sickness of humans and other creatures brought about by parasitic protozoans which belong to Plasmodium type. Malaria causes side effects that incorporate fever, fatigue, vomiting and cerebral pains. If not properly treated, it can bring about yellow skin, unconsciousness and even death. Malaria is induced by five species of plasmodium- P. Falciparum, P. Vivax, P. Malariae, P. Ovale and P. Knowlesi. In this paper, a venture has been formulated to develop an automated diagnosis strategy for classifying the malarial parasites. The blood smear images obtained from CDC database were segmented by utilizing Fuzzy C Means (FCM) and kapur segmentation strategies. The segmented image has been further utilized to extract features and the extracted measurements have been utilized for classifying the plasmodium species using SVM (Support Vector Machine) classification technique.
Do I Want My Money Backed? Trust Ambivalence &amp; Business Consequences Ensuing India’s Demonetization

This multi-method study brings the topic of money back into business scholarship by investigating how the relationship between institutional trust and trust in money affects organizational growth. Using demonetization in India as our empirical setting, we first use qualitative data and find that the policy shock implemented in 2016 by the government created institutional trust ambivalence (i.e. some dimensions of trust were affected positively and others negatively). Then, using theory on attributional search and social evaluation spillovers, we hypothesize and demonstrate empirically, with a regression discontinuity design, that trust ambivalence provides growth opportunities for business organizations acting as alternative trustees to government. Specifically, we show that organizations without ties to the government benefit the most from institutional trust ambivalence, especially private banks (to process payments) and cryptocurrency organizations (to store value). Our study contributes to the interdisciplinary literature on institutional trust and money and reconnects the notion of institutional trust to organizational growth and industry evolution.
Extracting stroke errors from digital ink characters by beginning learners of Chinese as a foreign language based on accurate stroke matching

The extraction of errors is an important aspect of Chinese character writing research. Stroke errors are the origins of most handwriting mistakes. Previous works have made some efforts on the types of errors extracted, while most of them are either preset by rules or deficient to include all types of stroke errors. For foreign students learning Chinese as a foreign language, especially beginners whose writing habits and characteristics are affected by ones of their native languages, methods by presetting are difficult to adopt. Therefore, this paper initiated from the data itself, proposes an adaptive approach to extract handwriting errors based on the result of the stroke matching which is accurate to sampling points in strokes. After the tagging list given as a matching index, the writing errors are adaptively extracted in different stroke errors of Chinese characters, including missing strokes, extra strokes, concatenated strokes, broken strokes, redundant strokes, incomplete strokes, the error of orientation and order. After serial experiments, the result indicates that the proposed approach is effective in extracting handwriting stroke errors.
Low Frequency Sampled Data Modal Control and Stabilization of Linear Periodic Processes with Control Signal Delay

The paper deals with a single-loop MIMO SD-system, in which a linear continuous T-periodic process is controlled by a digital controller that operates with a period of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> = dT, where d > 1 is an integer. Necessary and sufficient conditions for modal controllability and stabilizability of the system are given. The analysis is carried out on the basis of the discrete model of the system using the apparatus of determinant polynomial equations.