Reviewerly/exHarmony huggingface dataset:
Analysis and Development of KEBI 1.0 Checker Framework as an Application of Indonesian Spelling Error Detection

At educational institutions, especially at University, writing scientific papers is a skill that must be possessed by academics such as educators and students. However, writing scientific papers is not easy, there are many provisions and rules that need to be fulfilled. Several studies show that there are still many academics who make mistakes in writing their scientific papers. Some of the mistakes made include punctuation errors, typographic writing errors and the use of non-standard words in Indonesian. Researchers in Indonesia have developed various spelling error detection applications in Indonesian-language scientific papers. This study tries to analyze the development of an application framework for detecting Indonesian spelling errors from various assessment indicators. This study tries to compare the application framework for detecting spelling errors between other studies with proposed application that named KEBI 1.0 Checker. KEBI 1.0 Checker as a spelling error detection application has 3 main features, namely detecting errors in the use of punctuation marks, writing typography, and using non-standard words in accordance with the standards of the Big Indonesian Dictionary and the General Guidelines for Indonesian Spelling. In addition, this study tries to objectively examine the complexity of the features, advantages and disadvantages, methods and the level of accuracy of each application. The results of the analysis show that KEBI 1.0 Checker has the completeness of features, fast computation time, easy application access, and an attractive user interface. However, it is still necessary to improve the precision in correcting spelling errors in typographic words.
Translating to Share: An Enigmatical Compromise between Tradition and Treason

Translating means transposing a text from a source language to a target language. This practice considers that languages are defined as discrete in a reality dominated by continuity: they apply arbitrary cuts that do not correspond among idioms. Quine defined the principles of translation’s indeterminacy: the perfect translation does not exist; each one starts from hypotheses to draw conclusions. A language is more than a vocabulary or a grammar as well as a translation is more than an interlinguistic exchange: they represent the combination between vocabulary and encyclopaedia. The term translation presents a lexical proximity with tradition but also with treason. We cheat in order to get into the text, adapting the piece and the source language to the reader and the target language. A mechanism, in literature, which not only considers ideas but also creativity. The aim is to create a parallelism between two cultural systems and transpose semantic differences and nuances of meaning. The translator is called upon to give evidence of his/her abilities to promote a fruitful dialogue between two systems. These theories guided me during my first translation into Italian of the novel Chamsa, fille du soleil: a linguistic challenge in the understanding of the original text and then a cultural one rewriting it, bringing the Arab world closer to Italian readers. Translation is therefore an act of betrayal, of textual separation, but also a rally point among communities, safeguarding diversity. Finding the compromise among these variations is the real headache of a good translator.
Brawn with Brains

Abstract There are now many organizations that are utilizing some form of artificial intelligence or machine learning-powered robotics to help with automation capabilities. These companies are learning just how many duties that were once considered too hard for robots these AI-powered machines can handle.
nose and nose2

The last chapter introduced xUnit and unittest. In this chapter, you will explore yet another unit-testing API for Python, called nose. Its tagline is nose extends unittest to make testing easier.
THE DEVELOPMENT OF "MAHIR BERBAHASA" LEARNING APPLICATION FOR BIPA STUDENTS OF IKIP BUDI UTOMO MALANG

This research is intended to develop a web-based learning application “Mahir Berbahasa” to support the learning process of BIPA students at IKIP Budi Utomo. The software used in the development of this application is the Codeigniter and Bootstrap Framework. It is hoped that this application will become a student learning medium that can make it easier for foreign students to continue studying wherever they are. This type of research is R&amp;D development research. The development model used is the development of Borg and Gall. The results of this research development product in the form of "Mahir Berbahasa" learning applications have been tested and have received good ratings from users and validators. The assessment includes aspects of visual appearance, aspects of media relevance, aspects of material organization, aspects of software engineering, aspects of effects for learning strategies, and aspects of language. From a value range of 1-5, the user gives a mean value of 4.72, while the validator gives a value of 4.52. Based on this assessment, this learning application is in the category of feasible to use.
Blockchain

Blockchain is a shared, permanent record for recording exchanges, following resources and building trust. The principal key components of a Blockchain incorporate disseminated record innovation, permanent records and keen agreements. The significant advantages of Blockchain are all that organization members are approaching rights to the conveyed record and it is permanent, so nobody can change the exchange whenever it’s recorded and it additionally speeds up the exchanges due to the usefulness of keen agreements One of the most encouraging approaching advances in the field of Information Technology is Blockchain innovation. According to the review conducted by Grand View Research, Inc., the worldwide Blockchain market size was 1,590.0 million USD in year 2018 and it is predicted to increase at a compound annual growth rate (CAGR) of 69.4% during 2019 to 2025. In this chapter, we have examined digital currency and its various types, Blockchain Technology and Structure, Types of Blockchain, need and working of Blockchain, strategies for Blockchain and its Platform, the Applications of Blockchain, future patterns of Blockchain, future patterns in Blockchain, Integration of Machine Learning In Blockchain-Based Application.
Ghana

Ghana’s 1992 constitution provides guarantees for press freedom with little, if any, interference from the state. However, the Ghanaian media operate in a double bind, meaning the media do not generally respect the legitimate regulatory regime of the industry, neither are they willing to adhere to rules of self-regulation. This chapter examines existing and potential media accountability instruments (MAIs) in Ghana as well as the challenges and prospects of such instruments. The analysis reveals that the media landscape in Ghana has nurtured and established just a few MAIs, which include the National Media Commission and the ethical codes of journalists’ and media associations. Efforts to improve media self-regulation continues to occur outside the mass media, in online media criticism (social media) and political critique. There is still a fundamental challenge regarding the capacity of the existing and emerging MAIs to exact accountability from journalists in Ghana.
CLUDS: COMBINING LABELED AND UNLABELED DATA WITH LOGISTIC REGRESSION FOR SOCIAL MEDIA ANALYSIS

Automatic text classification and sentiment polarity detection are two important research problems of social media analysis. The meanings of the words are so important that they need to be captured by a document classification algorithm to reach an accurate classification performance. Another important issue with the text classification is the scarcity of labeled data. In this study, Combining Labeled and Unlabeled Data with Semantic Values of Terms (CLUDS) is presented. CLUDS has the following steps: preprocessing, instance labeling, combining labeled and unlabeled data, and prediction. In preprocessing step Latent Dirichlet Allocation (LDA) algorithm is used. In instance labeling step Logistic Regression is applied. In CLUDS, relevance values computation has been applied as a supervised term weighting methodology in the text classification field. Still, according to the literature, CLUDS is the first attempt that uses both relevance and weighting calculation in a semi-supervised semantic kernel for Support Vector Machines (SVM). In this study, Sprinkled-CLUDS and Adaptive-Sprinkled-CLUDS have also been implemented. Evaluated experimental results show that CLUDS, Sprinkled-CLUDS and Adaptive-Sprinkled-CLUDS generate a valuable performance gain over the baseline algorithms on test sets.
Quantum Algorithms

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Creating Multimodal Interactive Agents with Imitation and  Self-Supervised Learning

A common vision from science fiction is that robots will one day inhabit our physical spaces, sense the world as we do, assist our physical labours, and communicate with us through natural language. Here we study how to design artificial agents that can interact naturally with humans using the simplification of a virtual environment. We show that imitation learning of human-human interactions in a simulated world, in conjunction with self-supervised learning, is sufficient to produce a multimodal interactive agent, which we call MIA, that successfully interacts with non-adversarial humans 75% of the time. We further identify architectural and algorithmic techniques that improve performance, such as hierarchical action selection. Altogether, our results demonstrate that imitation of multi-modal, real-time human behaviour may provide a straightforward and surprisingly effective means of imbuing agents with a rich behavioural prior from which agents might then be fine-tuned for specific purposes, thus laying a foundation for training capable agents for interactive robots or digital assistants. A video of MIA's behaviour may be found at https://youtu.be/ZFgRhviF7mY
Reuse in component-based prototyping: an industrial experience report from 15 years of reuse

At Thales Defense Mission Systems, software products first go through an industrial prototyping phase. We elaborate evolutionary prototypes which implement complete business behavior and fulfill functional requirements. We elaborate and evolve our solutions directly with end-users who act as stake-holders in the products’ design. Prototypes also serve as models for the final products development. Because software products in the defense industry are developed over many years, this prototyping phase is crucial. Therefore, reusing software is a high-stakes issue in our activities. Component-oriented development helps us to foster reuse throughout the life cycle of our products. The work presented in this paper stems from 15 years of experience in developing prototypes for the defense industry. We directly reuse component implementations to build new prototypes from existing ones. We reuse component interfaces transparently in multiple prototypes, whatever the underlying implementation solutions. This kind of reuse spans prototypes and final products which are deployed on different execution platforms. We reuse non-component legacy software that we integrate in our component architectures. In this case, we seamlessly augment standard classes with component behavior, while preserving legacy code. In this paper, we present our component programming framework with a focus on component reuse in the context of evolutionary prototyping. We study our prototypes composition through data we extracted from our code repository. On these last 15 years we observe that, in average, our prototypes are composed of 80% reused components. Today, some of our prototypes can be constituted of more than 96% reused components. In this context, we report three reuse scenarios we regularly encounter in our prototyping activity, and that motivates our engineering efforts toward reusable components.
A note on the normality assumption for modeling constraint in cognitive  individual differences

To answer the question of "Does everybody...?" in the context of performance on cognitive tasks, Haaf and Rouder (2017) developed a class of hierarchical Bayesian mixed models with varying levels of constraint on the individual effects. The models are then compared via Bayes factors, telling us which model best predicts the observed data. One common criticism of their method is that the observed data are assumed to be drawn from a normal distribution. However, for most cognitive tasks, the primary measure of performance is a response time, the distribution of which is well known to not be normal. In this technical note, I investigate the assumption of normality for two datasets in numerical cognition. Specifically, I show that using a shifted lognormal model for the response times does not change the overall pattern of inference. Further, since the model-estimated effects are now on a logarithmic scale, the interpretation of the modeling becomes more difficult, particularly because the estimated effect is now multiplicative rather than additive. As a result, I recommend that even though response times are not normally distributed in general, the simplification afforded by the Haaf and Rouder (2017) approach provides a pragmatic approach to modeling individual differences in cognitive tasks.
Quantum Signal Processing (QSP) for simulating cold plasma waves

Numerical modeling of radio-frequency waves in plasma with sufficiently high spatial and temporal resolution remains challenging even with modern computers. However, such simulations can be sped up using quantum computers in the future. Here, we propose how to do such modeling for cold plasma waves, in particular, for an X wave propagating in an inhomogeneous one-dimensional plasma. The wave system is represented in the form of a vector Schr\"odinger equation with a Hermitian Hamiltonian. Block-encoding is used to represent the Hamiltonian through unitary operations that can be implemented on a quantum computer. To perform the modeling, we apply the so-called Quantum Signal Processing algorithm and construct the corresponding circuit. Quantum simulations with this circuit are emulated on a classical computer, and the results show agreement with traditional classical calculations. We also discuss how our quantum circuit scales with the resolution.
Current crowding in nanoscale superconductors within the Ginzburg-Landau  model

The current density in a superconductor with turnarounds or constrictions is non-uniform due to a geometrical current crowding effect. This effect reduces the critical current in the superconducting structure compared to a straight segment and is of importance when designing superconducting devices. We investigate the current crowding effect in numerical simulations within the generalized time-dependent Ginzburg-Landau (GTDGL) model. The results are validated experimentally by measuring the magnetic field dependence of the critical current in superconducting nanowire structures, similar to those employed in single-photon detector devices. Comparing the results with London theory, we conclude that the reduction in critical current is significantly smaller in the GTDGL model. This difference is attributed to the current redistribution effect, which reduces the current density in weak points of the superconductor and counteracts the current crowding effect. We numerically investigate the effect of fill factor on the critical current in a meander and conclude that the reduction of critical current is low enough to justify fill factors higher than $33\,\%$ for applications where detection efficiency is critical. Finally, we propose a novel meander design which can combine high fill factor and low current crowding.
The Optimization of Flux Trajectories for the Adiabatic Controlled-Z  Gate on Split-Tunable Transmons

In a system of two tunable-frequency qubits, it is well-known that adiabatic tuning into strong coupling-interaction regions between the qubit subspace and the rest of the Hilbert space can be used to generate an effective controlled Z rotation. We address the problem of determining a preferable adiabatic trajectory for which to tune the qubit frequency along, and apply this to the flux-tunable transmon model. The especially minimally anharmonic nature of these quantum processors makes them good candidates for qubit control using non-computational states, as long as higher-level leakage is properly addressed. While the statement of this method has occurred multiple times in literature, there has been little discussion of which trajectories may be used. We present a generalized method for optimizing parameterized families of possible flux trajectories and provide examples of use on five test families of one and two parameters.
INVESTIGATION OF FELT THAT CAN BE USED AS INSULATION MATERIAL IN MUSIC EDUCATION ENVIRONMENTS

Music education is the process of acquiring certain musical behaviors through the individual's life purposefully. When the environments where music education is given are examined, the music departments of fine arts high schools, education faculties fine arts education department music teaching programs, art design faculties music departments, fine arts faculties music departments, conservatories, public education centers, art centers, sections of municipal conservatories reserved for music lessons, etc. appears to be. In order to provide music education in a healthy way, the noise level of the buildings where music education is given should be controlled and the buildings should have certain qualifications. Buildings, classrooms and concert halls should be designed with attention to be in a form that can have acoustic properties. With the advancement of technology and the discovery of new materials, important developments have begun to emerge in building materials. While all these developments (strength, flexibility, bendability, etc.) generally reflect positively on the properties of the material, they may cause some disadvantages, especially in terms of insulation and acoustics. However, the slow progress of the legislation related to insulation causes the development speed of the studies on building materials to decrease. Insulation is of great importance, especially in terms of achieving the purpose of educational buildings with musical functions. In this study, information was provided about wool, which is a textile material, and felt obtained from wool. Evaluations were made about the usability of wool and felt in music education environments. Keywords: Wool, felt, music education, ınsulation, textile
Communicable disease outbreaks: Contact tracing

The role of the general practitioner (GP) as the medical expert at the centre of Australia's multidisciplinary primary healthcare system is never more acute than when populations are threatened by a communicable disease epidemic.This series is a refresher covering key concepts.This third article focuses on contact tracing, fondly known as 'shoe-leather epidemiology'.
Pre-Order Post-Order Coded Aggregate Tree based Algorithm for Mining Sequential Patterns

Sequential pattern mining is a data mining approach; aims to discover common interesting patterns in sequence datasets, which attracted a significant research interest due to its real world applications in various fields such as web click stream mining, retail business, stock market and bio-informatics. Each sequence in sequence dataset is composed of time ordered events and each event is an item set. It discovers all frequent subsequences having frequency greater than the given minimum support threshold. Discovering sequential patterns is expensive with respect to mining time as well as the amount of memory used, because of aggressive search space growth due to generation of explosive number of frequent subsequences with the sequence length as well as count of distinct items and large volume of sequence dataset. So, research in this domain aims at developing effective data structures which address frequency counting and large search space as well as scalable algorithms to reduce the execution time and the amount of memory utilized. We propose two efficient data structures called Pre-order Post-order Coded Aggregate Tree (PPCA-Tree) for compact representation of the sequence dataset and Root-node List of First-Occurrence Sub Trees Map (RLFOST-Map) for efficient representation of projected databases. We also developed an efficient Partially ordered Sequential PAttern Mining algorithm called PSPAM and Parallel implementation of Partially ordered Sequential PAttern Mining algorithm called PAPSPAM based on PPCA-Tree using RLFOST-Map which eliminates reconstruction of the projected databases. Experimental analysis done on various synthetic datasets proves that our algorithms PSPAM and PAPSPAM outperform prefixspan and other conventional &amp; state-of-the-art algorithms over dense datasets with better scalability.
Effects of Random Errors on Graph Convolutional Networks

The use of Graph Convolutional Networks (GCN) has been an emerging trend in the network science research community.While GCN achieves excellent performance in several tasks, there exists an open issue in applying GCN to real-world applications.The issue is the effects of network errors on GCN.Since real-world network data contain several types of noises and errors, GCN is desirable to be less affected by such errors.However, the effects have not been sufficiently evaluated before.In this paper, we analyze the effects of random errors on GCN through extensive experiments.The results show that the node classification accuracy of GCN is decreased only 5% even when 50% of the edges are randomly increased or decreased.Moreover, in terms of false labels, the accuracy of node classification is decreased only 10% even when 20% of the labels are changed.
Get Ready for Measures

Overall, a proper cybersecurity management program contains output values in key areas used for decision support. A proper program runs like a decision support system, providing an appropriate measurement of the problem being managed. In this case, cybersecurity risk.
Dynamic Voice Clones Elicit Consumer Trust

Platforms today are experimenting with many novel personalization technologies.We explore one such technology here, voice-based conversational agents, with a focus on consumer trust.We consider the joint role of two key design / implementation choices, namely i) disclosing an agent's autonomous nature to the user, and ii) aesthetic personalization, in the form of user voice cloning.We report on a set of controlled experiments based on the investment game, evaluating how these design choices affect subjects' willingness to participate in the game against an autonomous, AI-enabled partner.We find no evidence that disclosure affects trust.However, we find that the greatest level of trust is elicited when a voice-based agent employs a clone of the subject's voice.Mechanism explorations based on audio analytics indicate that voice-cloning induces trust by eliciting a perception of homophily.