Reviewerly/exHarmony huggingface dataset:
Waypoint Planning Networks

With the recent advances in machine learning, path planning algorithms are also evolving; however, the learned path planning algorithms often have difficulty competing with success rates of classic algorithms. We propose waypoint planning networks (WPN), a hybrid algorithm based on LSTMs with a local kernel - a classic algorithm such as A*, and a global kernel using a learned algorithm. WPN produces a more computationally efficient and robust solution. We compare WPN against A*, as well as related works including motion planning networks (MPNet) and value iteration networks (VIN). In this paper, the design and experiments have been conducted for 2D environments. Experimental results outline the benefits of WPN, both in efficiency and generalization. It is shown that WPN's search space is considerably less than A*, while being able to generate near optimal results. Additionally, WPN works on partial maps, unlike A* which needs the full map in advance. The code is available online.
Pelatihan Teknik Pengajaran Vocabulary Berbasis Media Realia bagi Guru TK Bakti Sesela Kabupaten Lombok Barat

The purpose of this community service activity is to improve the understanding and ability of teachers at TK Bakti, Sesela, in applying vocabulary teaching techniques based on realia media. This is based on the lack of ability of teachers at TK Bakti in teaching vocabulary material to the children. The method used in the implementation of this service is participatory training with a duration of activities for one month as the scheduled basis. There were five students involved in this program. The results of this community service activity were the teachers at TK Bakti, Sesela had the understanding and ability to apply realia media for vocabulary teaching techniques. In addition, it can make the teachers easier to teach English to students by using objects in the surrounding environment without having to buy new media or toys that are expensive, so they can also save school expenses with limited funds. This community service activity also really helps to make the students easier to remember vocabulary in English as a basic for their ability to speak English in the future.
SELF & FEIL: Emotion and Intensity Lexicons for Finnish.

This paper introduces a Sentiment and Emotion Lexicon for Finnish (SELF) and a Finnish Emotion Intensity Lexicon (FEIL). We describe the lexicon creation process and evaluate the lexicon using some commonly available tools. The lexicon uses annotations projected from the NRC Emotion Lexicon with carefully edited translations. To our knowledge, this is the first comprehensive sentiment and emotion lexicon for Finnish.
Performance Analysis Using Data Mining on Wisconsin Diagnostic Breast Cancer Dataset

Machine Learning techniques (ML) are playing a pivotal role in the medical field. Early diagnosis is required to prevent breast cancer. In this research Wisconsin Diagnostic Breast Cancer (WDBC) dataset with 32 predictors are analyzed to classify breast cancer. In this study attribute selection method CfsSubsetEval evaluator with best first search method is used for feature selection. Various machine learning algorithms are applied to compare Accuracy, kappa statistics, mean absolute error and root mean square error on selected features of this dataset to determine how prevalent those predictors in determining breast cancer. How the feature selection plays an important role to improve the performance of various classifier algorithms.
End-to-End Attention-based Image Captioning

In this paper, we address the problem of image captioning specifically for molecular translation where the result would be a predicted chemical notation in InChI format for a given molecular structure. Current approaches mainly follow rule-based or CNN+RNN based methodology. However, they seem to underperform on noisy images and images with small number of distinguishable features. To overcome this, we propose an end-to-end transformer model. When compared to attention-based techniques, our proposed model outperforms on molecular datasets.
Blockchains and Self-Sovereign Identities Applied to Healthcare Solutions: A Systematic Review.

Self-Sovereign Identity (SSI), a Blockchain-based technology for digital identity management, is a promising concept for handling health data. It could represent a step forward in empowering users, granting them control over their data. This work conducts a systematic literature review to investigate state-of-the-art measures based on SSI and Blockchain technologies for dealing with electronic health records (EHRs), identifying gaps, and determining the key questions for future research. As a result, this review shows a growing interest in Blockchain methods to handle EHRs, but few works consider using the self-sovereign identity approaches. The results obtained in this work also suggest that: Blockchain technologies provide a viable alternative to deliver EHR solutions such as patient monitoring, healthcare data trading, and prescription control; consolidated Blockchain technologies are the preferred core components of most effective strategies; keeping raw health data off-chain helps to create scalable solutions; health data standards make searching medical records in Blockchain structures feasible; Smart Contracts are essential components of Blockchain-based EHR solutions; the concepts of data ownership and Self-Sovereign Identity have been neither adequately defined nor employed in the health context.
Building Supply Chain with Blockchain

Blockchain, the digital record-keeping technology behind Bitcoin and other crypto currency networks, is a potential game changer in the financial world, but another area where it holds great promise is supply chain management. This paper explores various benefits and use cases for blockchain in supply chain management and discusses challenges while moving Supply Chain processes to block chain.
Intellectual Property Laws in the Digital Era: An International Distributive Justice Perspective

What do the “upload filter” (officially known as Article 17 of the Directive on Copyright in the Digital Single Market), YouTube Content ID Copyright detectors, and the race for a COVID-19 vaccine have in common? They all symbolize the need that has emerged in the digital era to redefine the concept of intellectual property (IP) beyond IP laws, expand the traditional viewpoint to include new digital global mechanisms and develop and adopt necessary supportive tools as well as new theoretical justifications and a global perspective. In the face of the current digital 3A era of automated, autonomous, advanced technologies, all of these technologies require redefining IP norms to better fit the digital age, in order to ensure that all players and stakeholders––from creators and inventors to end-users––are able to make the most of existing IP in related industries that are heavily influenced by developing technology, by making the fruits of the this field accessible worldwide. As “rapid technological developments continue to transform the way works and other subject matter are created, produced, distributed and exploited,” the examples above represent a new and broader understanding of the scope of IP that includes affiliated and supportive tools that enable and enhance equal access within an international perspective. In other words, an international distributive of justice approach.
Classical emulation of quantum states with coherent mixtures

We propose a classical emulation methodology to emulate quantum phenomena arising from any non-classical quantum state using only a finite set of coherent states or their statistical mixtures. This allows us to successfully reproduce well-known quantum effects using resources that can be much more feasibly generated in the laboratory. We present a simple procedure to experimentally carry out quantum-state emulation with coherent states that also applies to any general set of classical states that are easier to generate, and demonstrate its capabilities in observing the Hong-Ou-Mandel effect, violating Bell inequalities and witnessing quantum non-classicality.
‘쉬운 언어’ 문학의 가능성 모색 - 에 관한 소고-

In this study I analysed and discussed ‘Easy-to-read Koreans Short Stories’, Korean short stories rewritten in ‘Einfache Sprache(simplified language). I demonstrate how I consider that these written stories are not the examples of Leichte Sprache, but instead Einfache Sprache. I h ave tried t o rewrite them i n the form of Leichte Sprache. Also, I suggest some guidelines to follow when writing or rewriting literary works in Leichte Sprache.
The Development and Application of Bilingual Engineering in an Education Institution (A Case Study in RMB)

&lt;p align="center"&gt;Teaching Speaking effectively is one of problems in the field of language teaching. Many teachers and schools are frustated in activating students’ speaking ability. We need a research to find an appropriate teaching method and teaching strategy to handle the problem. This qualitative research was applied by using &lt;em&gt;system perspective. &lt;/em&gt;Theoretically, system perspective is a study of system by questioning: how and why a system entirely works as it should be. The researcher will come into the system, observing how the bilingual engineering is applied. The object of the research will be focused on observing the forms of bilingual engineering and all parties’ opinion related to applying bilingual program. The researcher also did literature study as a comparative study especially related to bilingual theory. The result of the research shows that the program is success. It is shown by the good satisfaction level. Satisfaction will be able to improve school’s academic achievement. Finally, the researcher believes that the application of the bilingual program has a significant implication to the school’s overall achievement. &lt;/p&gt;
Review on Reversible Logic Circuits and its Application

One of the emerging studies on reversible gates has been region to ensure a continuous process of trends in innovation that explore and make use of resources. It sparks the reversible gate Via its applications in many technologies, such as low-power technologies, CMOS, DNA computing, visual, quantum computing, Nanotechnology, and so on. This article presents the development of Reversible gate which is used to function reversibly. Even, presents the comparative study of different combinational and combinational studies Sequential circuits that use various reversible gates. Reversible in Logic circuits for each different combination of specific inputs it’s possible to generate production and vice versa. Many of the outcomes of Existing work is identified and compared to various works. About parameters. The primary objective of developing reversible logic is to minimize Quantum cost, garbage output number & circuit depth.
What Does My QA Model Know? Devising Controlled Probes using Expert

Open-domain question answering (QA) involves many knowledge and reasoning challenges, but are successful QA models actually learning such knowledge when trained on benchmark QA tasks? We investigate this via several new diagnostic tasks probing whether multiple-choice QA models know definitions and taxonomic reasoning—two skills widespread in existing benchmarks and fundamental to more complex reasoning. We introduce a methodology for automatically building probe datasets from expert knowledge sources, allowing for systematic control and a comprehensive evaluation. We include ways to carefully control for artifacts that may arise during this process. Our evaluation confirms that transformer-based multiple-choice QA models are already predisposed to recognize certain types of structural linguistic knowledge. However, it also reveals a more nuanced picture: their performance notably degrades even with a slight increase in the number of “hops” in the underlying taxonomic hierarchy, and with more challenging distractor candidates. Further, existing models are far from perfect when assessed at the level of clusters of semantically connected probes, such as all hypernym questions about a single concept.
Disruptive Technology Relocate a well-established Product and Engender Benchmark in Industry

“Disruption” portrays a method whereby a tiny corporation with smalleramount capital is capable to effectively confront well-known presentcompany. Harvard Business School professor Clayton M. Christensen coinedthe expression “disruptive technology”. In 1997 in one of his best-sellingbooks, “The Innovator’s Dilemma,” Christensen split new technology intotwo categories: “sustaining” and “disruptive”. Sustaining technology relieson incremental upgrading to a previously established technology. Disruptivetechnology lacks enhancement, regularly has recital troubles for the reason that it is new,appeals to a limited audience and may not yet have a demonstrated practical relevance.In this write-up we will emphasize on certain heads which make readers a familiar withCurtain Raiser to Disruptive technologies, sectors affected by disruptions technology,examples of disruptive technology, true disruptive brands, Investing in Disruptive Technology,Controversy with a theory and finally how India is going to be benefitted.
Library Guides: How to Start Your Research: Search Library Databases

Tips and tools for starting your research and searching for information in library databases and catalogs.
Structural and functional model of developing pedagogical skills of teachers of economics in Master’s degree programmes

The article represents a structural and functional development model of pedagogical skills of teachers of economic disciplines in Master’s degree programmes with carrying out and proving its theoretical substantiation and the expediency of its use. The interconnected, namely theoretical, semantic and effective blocks of the suggested model are analyzed. The components, criteria and levels of pedagogical skills are described as well. The article identifies such approaches to the development of pedagogical skills of teachers of economic disciplines in Master’s degree programmes, as psycho-didactic, competence, activity and innovative; the principles that must be followed in the development process of pedagogical skills of teachers of economic disciplines in Master’s degree programmes, namely, professional orientation, subjectivity, priority of active teaching methods, interactive technologies and self-improvement are also characterized. The effectiveness of the structural and functional model introduction of pedagogical skills development of teachers of economic disciplines in the Master’s degree programmes was tested experimentally.
계획된 행위이론에 근거한 대학생의 인플루엔자 예방접종 행위의도 관련 요인

The purpose of this study was to identify the factors that affect the influenza vaccination intention in university students based on theory of planned behavior. Methods: The data were collected total 149 university students in the G region who agreed to participate in the study from September 21 to September 29, 2020 by using self reported questionnaires. Date were analyzed using descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficients and multiple regression with the SPSS 23.0 program. Results: The mean score of attitude toward influenza vaccine was 6.06±1.03, subjective norm was 5.90±1.19, perceived behavioral control was 5.85±0.96, intention was 5.71±1.35. Intention to influenza vaccine showed a significantly positive correlation with attitude (r=0.62, p<0.001), subjective norms (r=0.50, p<0.001), perceived behavioral control (r=0.48, p<0.001). The influence the intent to influenza vaccination in university students were attitude (β=0.47, p<0.001), subjective norm (β=0.18, p=0.032). The explanatory power of these variables was 43.0%. Conclusions: In order to improve the influenza vaccination rate of university students, positive attitude toward influenza vaccination should be made first, and efforts should be made to improve the purpose of vaccination by meaningful people around them through interest in vaccination and positive awareness.
Extracting total Amb programs from proofs

Abstract We present a logical system CFP (Concurrent Fixed Point Logic) that supports the extraction of nondeterministic and concurrent programs that are provably total and correct. CFP is an intuitionistic first-order logic with inductive and coinductive definitions extended by two propositional operators, $$B|_{A}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>B</mml:mi><mml:mo>|</mml:mo></mml:mrow><mml:mi>A</mml:mi></mml:msub></mml:math> (restriction, a strengthening of implication) and $${\mathbf {\downdownarrows }}(B)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>⇊</mml:mo><mml:mo>(</mml:mo><mml:mi>B</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math> (total concurrency). The source of the extraction are formal CFP proofs, the target is a lambda calculus with constructors and recursion extended by a constructor Amb (for McCarthy’s amb) which is interpreted operationally as globally angelic choice and is used to implement nondeterminism and concurrency. The correctness of extracted programs is proven via an intermediate domain-theoretic denotational semantics. We demonstrate the usefulness of our system by extracting a nondeterministic program that translates infinite Gray code into the signed digit representation. A noteworthy feature of our system is that the proof rules for restriction and concurrency involve variants of the classical law of excluded middle that would not be interpretable computationally without Amb.
Improved and Efficient Text Adversarial Attacks using Target Information

There has been recently a growing interest in studying adversarial examples on natural language models in the black-box setting. These methods attack natural language classifiers by perturbing certain important words until the classifier label is changed. In order to find these important words, these methods rank all words by importance by querying the target model word by word for each input sentence, resulting in high query inefficiency. A new interesting approach was introduced that addresses this problem through interpretable learning to learn the word ranking instead of previous expensive search. The main advantage of using this approach is that it achieves comparable attack rates to the state-of-the-art methods, yet faster and with fewer queries, where fewer queries are desirable to avoid suspicion towards the attacking agent. Nonetheless, this approach sacrificed the useful information that could be leveraged from the target classifier for that sake of query efficiency. In this paper we study the effect of leveraging the target model outputs and data on both attack rates and average number of queries, and we show that both can be improved, with a limited overhead of additional queries.
Parallels Between the Future for MedTech and Agri-Tech, Perspectives Drawing on the British Experience

In this chapter we explore the future for innovation in two related, but distinct, sectors. We consider the linkages between medical technology (MedTech) and agricultural technology (Agri-Tech) innovation in the UK. We ask and discuss questions: Who are the key actors in the innovation systems of MedTech and Agri-Tech in the UK? What are the core technologies driving the current waves of innovation in these two sectors? Can one industry learn from the other? Where is the scope for cooperation and synergies? We notice that both sectors are technologically linked through foundational technologies underpinning the majority of the observed innovation, e.g. big data, AI, IoT and robotics. The outputs of these technologies rely crucially on digital data for insight and decision support. However, Agri-Tech benefits from less complex stakeholder issues regarding data security and privacy. Both sectors are important to the UK going forwards, and both will be exposed to Brexit and consequences of the COVID pandemic. Our discussion on the future for innovation should be of particular interest to start-up leaders, entrepreneurs, investors, managers and policy-makers in MedTech, Agri-Tech and cognate sectors.
THE EFFECTIVENESS OF TEACHER’S CORRECTIVE FEEDBACK IN TEACHING WRITIN

The effect of Teacher’s Corrective Feedback in Teaching Writing is a strategy that effectively facilities in learning English. The students can be more aware with the errors that they made in their writing product and will not write the errors repeatedly. The method used in this study was pre-experimental design and it was conducted in one of Islamic High School in Garut class X IPA 1. Written test was given to every students of the class to find out students’ writing achievement before and after have been given treatments. Beside that the interview was conducted to gather more information about students’ responses toward the strategy. Based on the findings that the value of tobserve (17.372) &gt; tcritical (2.0452) it can be define that tobserved was out of Ho area and it meant that Ha was accepted. Therefore, it was concluded that using teacher’s corrective feedback significantly affected students’ achievement in writing text.
Determinants of Innovations in the Region of MENA

This paper investigates determinants of innovation in MENA (Middle East and North Africa) countries. This investigation focused on GDP per capita (PPP), higher education enrollment, economy openness, business disclosure and unemployment rates, among other factors. The analysis uses the Global Innovation Index (GII), patent applications and high technology export as dependent variables in separate models. Panel regression is applied in the study. The result indicates that in the MENA region, all the above four factors except unemployment rate are determinants of innovation, and it is also shown that high technology export is the best proxy for innovation among the three dependent variables. This study is organized in the following format: introduction, followed by literature review, then data and methodology, then the results and discussion; finally, the paper closes with its conclusion and potentialities for future research.
Riemannian Trust-Region based Adaptive Kalman filter with unknown noise Covariance matrices

The problem of adaptive Kalman filtering for a discrete observable linear time-varying system with unknown noise covariance matrices is addressed in this paper. The measurement difference autocovariance method is used to formulate a linear least squares cost function containing the measurements and the process and measurement noise covariance matrices. Subsequently, a Riemannian trust-region optimization approach is designed to minimize the least squares cost function and ensure symmetry and positive definiteness for the estimates of the noise covariance matrices. The noise covariance matrix estimates, under sufficient excitation of the system, are shown to converge to their unknown true values. Saliently, the exponential stability and convergence guarantees for the proposed adaptive Kalman filter to the optimal Kalman filter with known noise covariance matrices is shown to be achieved under the relatively mild assumptions of uniform observability and uniform controllability. Numerical simulations on a linear time-varying system demonstrate the effectiveness of the proposed adaptive filtering algorithm.