Reviewerly/exHarmony huggingface dataset:
Pilot Study: Characterizing Successful Beginning Reading in Indonesian

The investigation reported in this article aims to point out how the lexical and sub- lexical route are employed in normal beginning reading in Bahasa Indonesia (Indonesian) and to identify  reading performance that may suggest the occurrence of impaired reading in Bahasa Indonesia which is possibly displayed by the children with the lowest reading performance. Ten typical developing third-grade  students participated in the study. Error pattems of those ten students are analysed for the error analysis and for the analysis on the relationship between psycholinguistic variables and reading perforrnance. Five of those students were  recorded during the reading part and the data were used in the latency analysis. The prelirninary findings reported here seem to show that beginning reading in Bahasa Indonesia is characterised by the utilization of the sub-lexical route and more skilled reading by lexical route. The development of the lexical route depends on the development of the sublexical route which is influenced by the complexity of the Grapheme Phoneme Correspondence. The lexical route for words with simple graphemes is developed first, the lexical route for words with consonant clusters are developed later. The last to be developed is the lexical route for words with digraphi. Furthermore, Late AoA, imageability, syllable number, and resemblance to words influence the lexical processing of the stimuli in the test. Impaired reading seems to be characterised by less developed sub-lexical route as evidenced by difliculties with words containing consonant clusters and digraphs and longer latencies for reading aloud words and pseudowords. Keywords : psycholinguistics, r eading p erformanc e
A Novel Technique with Lo Gradient Minimization for Rain-Free Images

Detection and removal of rain in the image are a complicated and critical problem due to difficulty of rain and its negative effects on the image. The paper proposes a novel, efficient and simple algorithm for detection and removal of rain from the image using Lo gradient minimization that can commonly eliminate rain pixels from the image. The algorithm is easy to use and successful in spotting and removing rain of sequential images. This method does not depend on local features but as an alternative locates necessary edges globally. This relevant edge information will wait until all other information is extracted in this manner and then rain pixels are removed. Next, to improve contrast in images, intensity enhancing is done using histogram adjustment technique. To compare this result with other techniques, quality index has been measured for the rain removal image. Experimental results showed that the proposed algorithm is extremely efficient as it removes rain successfully for even light and heavy rain in the image.
Formal Verification of Merkle–Damgård Construction in ProVerif

ProVerif is one of the most successful automatic cryptographic protocol verifiers. However, in ProVerif, it is difficult to formalize recursive execution, whose internal state is changed by an execution result, such as a stream cipher. In this paper, we propose a method of formalizing recursive execution with an internal state in ProVerif. In our proposed method, we treat function calls as communication between internal processes using private channel. The Merkle–Damgard construction (MD construction) is a method of constructing a cryptographic hash function such as SHA-1 or MD5. The behavior of MD construction is similar to recursive execution, because its construction includes one-way compression functions and an internal variable changed by the output of these functions. We also formalize the MD construction algorithm utilizing our proposed method for recursive execution. We verify that our formal model of MD construction successfully holds properties of cryptographic hash function, preimage resistance and collision resistance.
Word sense disambiguation using optimisation techniques

In the field of computational linguistics, word sense disambiguation (WSD) is a problem of high significance which helps us to find the correct sense of a word or a sequence of words based on the given context. It is treated as a combinatorial optimisation algorithm wherein the aim is to discover the set of senses which help to improve the semantic relatedness among the target words. Nature inspired algorithms are helpful to find optimal solutions in reduced time. They make use of collection of agents that interact with the surrounding environment in a coordinated manner. In this article, two such algorithms, namely, cuckoo search and firefly algorithms, have been used for solving this problem and their performance have been compared with the D-bees algorithm based on bee colony optimisation algorithm. They have been evaluated using the standard SemEval 2016 task 11 dataset for complex word identification. Experimental results show that firefly algorithm is performing better than the other algorithms.
Understanding Smart Contracts: Hype or Hope?

Smart Contracts are commonly considered to be an important component or even a key to many business solutions in an immense variety of sectors and promises to securely increase their individual efficiency in an ever more digitized environment. Introduced in the early 1990s, the technology has gained a lot of attention with its application to blockchain technology to an extent, that can be considered a veritable hype. Reflecting the growing institutional interest, this intertwined exploratory study between statistics, information technology, and law contrasts these idealistic stories with the data reality and provides a mandatory step of understanding the matter, before any further relevant applications are discussed as being factually able to replace traditional constructions. Besides fundamental flaws and applica-tion difficulties of currently employed Smart Contracts, the technological drive and enthusiasm backing it may however serve as a jump-off board for future developments thrusting well in the presently unshakeable traditional structures.
Penerapan Naive Bayesian Classifier Dalam Penyeleksian Beasiswa PPA

In this study, the author uses the Naive Bayes Classifier method to classify scholarship recipients at Budi Darma University. The use of the Naive Bayes Classifier method was chosen to make decisions in order to determine whether students enrolled in the scholarship program were accepted or rejected. The classifier method is to classify text based on the highest probability that it is defined as a new document category. From the results of this research, the results show that the value of Receiving is higher than No, which is 0.0351 compared to 0, so it can be concluded that the student on behalf of Riska Ramadhani received the PPA 2019 scholarship.
Penerapan Metode SAW (Simple Additive Weighting) Dalam Pemilihan Siswa-Siswi Berprestasi Pada Sekolah SMK Swasta Mustafa

In the face of the times and the era of technology that is rapidly developing at any time, the development of human resources is a top priority in the national development of the state, the position and position of students, has a very important role in teaching and learning activities for students to improve. Student achievement in academics and non-academic fields, one of the things that motivates students to always develop themselves is to give an award as an outstanding student with the criteria determined by the school. Temporary observations at Mustafa Private Vocational High School in determining outstanding students were done manually. This method is still considered ineffective and inefficient. Based on this, a model for determining outstanding students at Mustafa Private Vocational School is needed with a more efficient and effective system. This system is designed using a decision support system through the Simple Additive Weighting (SAW) method. This system can display the results of the ranking of outstanding students based on the calculation results of the SAW method
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations

When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods in Monte Carlo studies. The credibility of such Monte Carlo studies is often limited because of the freedom the researcher has in choosing the design. In recent years a new class of generative models emerged in the machine learning literature, termed Generative Adversarial Networks (GANs) that can be used to systematically generate artificial data that closely mimics real economic datasets, while limiting the degrees of freedom for the researcher and optionally satisfying privacy guarantees with respect to their training data. In addition if an applied researcher is concerned with the performance of a particular statistical method on a specific data set (beyond its theoretical properties in large samples), she may wish to assess the performance, e.g., the coverage rate of confidence intervals or the bias of the estimator, using simulated data which resembles her setting. Tol illustrate these methods we apply Wasserstein GANs (WGANs) to compare a number of different estimators for average treatment effects under unconfoundedness in three distinct settings (corresponding to three real data sets) and present a methodology for assessing the robustness of the results. In this example, we find that (i) there is not one estimator that outperforms the others in all three settings, so researchers should tailor their analytic approach to a given setting, and (ii) systematic simulation studies can be helpful for selecting among competing methods in this situation.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Aesthetic Experiences of Making with Paper

AbstractArtists bring heightened awareness of sensation and material qualities in the experience of making. In this chapter, I portray the sensate experience of making with paper spurred by artists as embedded living installations in The Corner—a play/making space for under eight year olds in the State Library of Queensland, Australia. I look closely at the experience of making as inherently connected to aesthetics (); in particular making with paper. Three artists make with paper on different days. Each brings different insights of the sensuous qualities and making capacities of paper.Children and their families make with the artists. Intense focus is experienced. The unlimited possibilities of paper come to be known in a library—a place of books—preserved entities made of paper; yet, in The Corner of the library, paper can be reconfigured—is reconfigured—opening up the wonder of the aesthetic experience of mattering, imagining, and making with paper. Attention to sensation, matter and making were gathered through sensory ethnography (Pink, 2015), aesthetic sensibilities and understanding of the vibrancy of matter (). Performative accounts of artist making experiences with paper are shared to glean what happens in the experiences of making; what we come to sense, to know, to be and connect across generations and communities. Material literacies unfold.
Post treatment of effluents from anaerobic digestion of organic fraction of municipal solid waste

The anaerobic process is considered to be a sustainable technology for organic waste treatment mainly due to its lower energy consumption and production of residual solids coupled with the prospect of energy recovery from the biogas generated. However, the anaerobic process cannot be seen as providing the ‘complete’ solution as its treated effluents would typically not meet the desired discharge limits in terms of residual carbon, nutrients and pathogens. This has given impetus to subsequent post treatment in order to meet the environmental legislations and protect the receiving water bodies and environment.This book discusses anaerobic treatment from the perspective of organic wastes and wastewaters (municipal and industrial) followed by various post-treatment options for anaerobic effluent polishing and resource recovery. Coverage will also be from the perspective of future trends and thoughts on anaerobic technologies being able to support meeting the increasingly stringent disposal standards. The resource recovery angle is particularly interesting as this can arguably help achieve the circular economy. It is intended the information can be used to identify appropriate solutions for anaerobic effluent treatment and possible alternative approaches to the commonly applied post-treatment techniques. The succeeding discussion is intended to lead on to identification of opportunities for further research and development.This book can be used as a standard reference book and textbook in universities for Master and Doctoral students. The academic community relevant to the subject, namely faculty, researchers, scientists, and practicing engineers, will find the book both informative and as a useful source of successful case studies.ISBN: 9781780409733 (paperback)ISBN: 9781780409740 (eBook)ISBN: 9781780409757 (ePub)
Allegory and Excess

Chapter 1 deals with the excess that opera always seems to produce in performance, which has mostly been associated with the physical, material aspects of the singing voice. Drawing on performative theory, this chapter approaches this excess as the result of a dialogic situation of meaning-making, where the audio-viewers strive to make sense of what they see and hear on stage or screen. The concept of allegory is evoked to approach the processes of meaning-making in hypermedial opera, drawing attention to how opera incites reading while at the same time withholds a coherent, univocal meaning. Allegory also helps recognize that the reading of opera involves not only text and image but also music and the voice. By contrast, the perception that the singing voice escapes signification is understood here as an effect of immediacy. Louis Andriessen’s and Peter Greenaway’s <italic>Rosa</italic> serves as the main case study.
Seasonal and Diurnal Variations of Carbon Dioxide and Energy Fluxes over Three Land Cover Types of Nepal

&amp;lt;p&amp;gt;This study examines the seasonal and diurnal variations of carbon dioxide and energy fluxes over three land cover types of Nepal by using the eddy covariance method from March to November 2016. The surface energy balance closures were moderate with the values of about 56%, 61%, and 64% closure at Kirtipur, Simara, and Tarahara sites respectively. The monthly average values of net radiation flux and latent heat flux peaked in August at Kirtipur and Tarahara sites whereas in June at Simara site respectively. The maximum monthly average measured sensible heat flux was 37 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt;, 43.6 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt;, and 36.3 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; in April for all the sites whereas soil heat flux was 5.1 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; and 2.9 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; in April for Kirtipur and Simara sites and 6.2 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; in June for Tarahara site. The magnitude of diurnal peak of net ecosystem CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; exchange (NEE) reached up to 11.04 &amp;amp;#181;mol m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; s&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; at Kirtipur, 15.04 &amp;amp;#181;mol m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; s&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; at Simara, and 10.44 &amp;amp;#181;mol m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; s&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; at Tarahara sites respectively. Among the three study sites, the ecosystem at the Kirtipur site was a good carbon source; the ecosystems at Simara and Tarahara sites were low and good carbon sink in the growing season. In addition, all three different land cover ecosystems were carbon sources when accounted for the measurement period.&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;
A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric Power Communication Network

As the scale of the electric power communication network is getting larger and larger, network security issues are becoming more and more complex. as an effective protection method, network traffic anomaly detection can provide important technical support for network situation awareness. In some cases, plenty of labeled data are unavailable, which may lead to low detection accuracy. To deal with this problem, a nonnegativity-constraint sparse stacked denoising autoencoder(NSSDAE) is proposed. Meanwhile, we propose a method called dynamic parameter freezing(DPF) for parameter transfer, which allows to find the best performance that may exist between the freezing and fine-tuning within a layer by adjusting the variable alpha. And discriminative joint probability maximum mean discrepancy is introduced for distribution adaptation. The results for NSL-KDD show that the proposed NSSDAE-TL algorithm is effective.
Correction: SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets

[This corrects the article DOI: 10.2196/11487.].
Las prácticas pedagógicas mediadas por tecnologías digitales en espacios curriculares de alto contenido práctico

This article summarizes a research about teaching practices under digital technologies ( TD ) in curricular areas with high practical content ( ECACP ) in blended-modality courses of Plan 2017 , from the Instituto Normal de Enseñanza Técnica (INET).This type of classes, with practical content like workshops and lab work, are taught through a virtual platform from the Consejo de Formación en Educación (CFE) and are complemented with a thirty percent of in-person classes.There is also the possibility of using videoconferencing.Teachers are responsible for designing strategies to address the practical aspects of their courses using virtual digital technologies.Questions arise regarding the problems faced by the teachers, how they handle them, which are the critical aspects to solve and which are the most successful strategies that can be used as an input by other teachers.This is a descriptive study in which semi-structured interviews with three teachers, the observation of their virtual classrooms and the analysis of documentation have been used as data-collection instruments.
Sentiment analysis measure of topic mapping in LDA-LSTM combination model

Abstract New energy market competition incentive, how to improve the product accurately, so as to attract consumers, will become the key point for enterprises to occupy the market. From the perspective of improving products, this paper constructs a review information dimension mapping theme emotion analysis model. Firstly, LDA model is used to extract the topic of comment information. Secondly, topic mapping is carried out on the comment information to get the correlation degree between each comment information and each dimension topic. Finally, the LSTM model is constructed for sentiment analysis, and the emotional intensity of consumers in each dimension theme is measured.
A path planning method for UAVs based on multi-objective pigeon-inspired optimisation and differential evolution

Inspired by the behaviour of pigeon flocks, an improved method of path planning and autonomous formation for unmanned aerial vehicles based on the pigeon-inspired optimisation and differential evolution is proposed in this paper. Firstly, the mathematical model for UAV path planning is devised as a multi-objective optimisation with three indices, i.e., the length of a path, the sinuosity of a path, and the risk of a path. Then, the method integrated by pigeon-inspired optimisation and mutation strategies of differential evolution is developed to optimise feasible paths. Besides, Pareto dominance is applied to select the global best position of a pigeon. Finally, a series of simulation results compared with standard particle swarm optimisation algorithm and standard differential evolution algorithm show the effectiveness of our method.
Evaluating chemical weathering of sediments using “R” programming environment – A possible alternate of spreadsheet applications

Evaluation of chemical weathering of sediments is the key factor for provenance study and characterization of various sedimentological processes involved in weathering. The various Weathering Indices (WIs) models are available to estimate major elemental geochemistry of the sedimentary package including CIW, CPA, CIA, PIA, CIX, ICV, WIP, R, V, STI and MWPI. The present investigation is to improve and correlation of the earlier models with our development of a computer program using R programming environment to establish various statistical measures, correlation of chemical indices of weathering and to plot different compositional variation diagrams and their analyses. The present results reveal that the correlation of Different correlation plots suggest a significant level of relationship and positive correlation coefficients in CIW – PIA, CIA – PIA, CPA – CIX, ICV – MWPI pairs while significant level of relationship and negative correlation coefficients in CIW – ICV, CIA – WIP pairs. Besides, boxplot of WIs indicates a skewed left or negatively-skewed distribution of CIW and CIA while a skewed right or positively-skewed distribution of CPA, CIX and WIP. Different compositional space diagrams (A – C – N, A – CN – K, A-K – C – N, M – F – W, A – CNK – FM, A – N – K) constrain sediments and rock/mineral composites major elemental geochemistry and demonstrate weathering profiles and source rock chemical makeup. R environment provides flexibility to alter the code as per the data and user requirement by altering different arguments in the code and to include further relevant charts &amp; plots. The applicability of the programming tool is demonstrated by its performance in evaluating the chemical weathering of Surma and Barail sandstones, Mizoram Foreland Basin, NE India and sediments of Manasbal Lake, Kashmir, India, having contrasting provenance histories.