Reviewerly/exHarmony huggingface dataset:
Learning User-Interpretable Descriptions of Black-Box AI System Capabilities.

Several approaches have been developed to answer specific questions that a user may have about an AI system that can plan and act. However, the problems of identifying which questions to ask and that of computing a user-interpretable symbolic description of the overall capabilities of the system have remained largely unaddressed. This paper presents an approach for addressing these problems by learning user-interpretable symbolic descriptions of the limits and capabilities of a black-box AI system using low-level simulators. It uses a hierarchical active querying paradigm to generate questions and to learn a user-interpretable model of the AI system based on its responses. In contrast to prior work, we consider settings where imprecision of the user's conceptual vocabulary precludes a direct expression of the agent's capabilities. Furthermore, our approach does not require assumptions about the internal design of the target AI system or about the methods that it may use to compute or learn task solutions. Empirical evaluation on several game-based simulator domains shows that this approach can efficiently learn symbolic models of AI systems that use a deterministic black-box policy in fully observable scenarios.
KEMAMPUAN SISWA MENULIS TEKS BERITA DENGAN MENGGUNAKAN MEDIA AUDIO VISUAL KELAS VIII SEMESTER GENAP SMP SURYA DHARMA BANDAR LAMPUNG TAHUN PELAJARAN 2018/2019

The purpose of this study was to find out and describe the students' ability to write news texts using audio visual class VIII students of Surya Dharma Bandar Lampung Middle School 2018/2019. The method used in this study is descriptive quantitative method, while the technique of collecting data is by performance tests, namely by assigning students to write news texts using audio visual. The population in this study amounted to 30 students and the number of samples of this study was determined by the entire population, that is 30 people, the determination of julah sample of this study using total sampling technique. Analyzing the data in this study is to use a percentage. The results of this study are as follows: (1) Ability to write news texts based on completeness indicators with an average value of 87 included in very good criteria. (2) Ability to write news texts based on indicators of language rigidity with an average value of 57.3 including in sufficient criteria. (3) Ability to write news text based on word selection indicators with an average value of 61.3 including in sufficient criteria. (4) The ability to write news text based on the indicator of attractiveness of the title with an average value of 53.3 included in the criteria of less. (5) Ability to write news text based on spelling usage indicators with an average value of 66.6 included in the criteria of good.
Task strategies mediate the interaction between working memory and other cognitive systems

Author(s): Newlin, Philip; Moss, Jarrod | Abstract: Individuals can learn differently, even in very simple tasks. In an association learning task, participants learned associations between correct keypresses and sets of categorically related images. Following a delay, participants were then tested on the associations in a surprise test. This task has been used to examine the relationship between reinforcement learning and working memory. However, the strategies that individuals use to explore the associations between keypresses and images as well as the opportunity to take advantage of a simple rule based on the structure of the task without having to retrieve the correct response may both impact test performance. Two experiments were conducted to test these hypotheses. Results showed that the performance difference from the end of the learning phase to the testing phase differed significantly between set size conditions in a way that is more consistent with strategic differences than an interaction between working memory and reinforcement learning.
The Current State of AI Governance – An EU Perspective

The rapid pace of technological advancement and innovation has put governance and regulatory mechanisms to the test. There is a clear need for new and innovative regulatory mechanisms that enable governments to successfully manage the integration of such technologies into our societies and ensure that such integration occurs in a sustainable, beneficial, and just manner. Artificial Intelligence stands out as one of the most debated such innovations. What exactly is it, how should it be built, how can it be used, and how and should it be regulated? Yet, in this debate, AI is becoming widely utilized within both existing, evolving, and bespoke regulatory contexts. The present chapter explores in particular what is arguably the most successful AI regulatory approach to date, that of the European Union. We explore core definitional concepts, shared understandings, values, and approaches currently in play. We argue that due to the so-called ‘Brussels effect’, regulatory initiatives within the European Union have a much broader global impact and, therefore, warrant close inspection.
초등과학영재학생들의 컴퓨터 활용 과학 실험 교수 학습 전략 탐색

The purpose of this research is to analyze the learning characteristics of elementary science gifted students in computer based science experiment(CBE) class and explore teaching and learning strategies that can effectively represent the advantages of computer based science experiment(CBE). In the research, CBE lesson with 4 classes were given to the eight elementary school students attending the Science Gifted Institute affiliated with the university. At the end of the class, the learning characteristics of students that appeared in relation to the advantages of CBE mentioned in the preceding study were analyzed qualitatively. As a result, it was confirmed that students performed less monitoring of experiment conditions, more frequent result prediction and graph-making activities in accordance with the teacher's assignment. And it was confirmed that the frequency of students' discourse decreases in classes where teachers' explanation time is long or relying heavily on textbooks. The effective teaching and learning strategies explored in research are as follows. First, the time to observation of laboratory instruments and share the results of other groups should be secured as much as possible and autonomy should be given to organizing experiments. Second, presenting appropriate tasks and intervening in student activities. for graph processing, feedback and discussion. Third, the teacher's explanation and guidance should be replaced with discussion and experiment result sharing time so that students have various observational opportunities and opportunities to interpret experimental results.
Solar tracker platform development for energy efficiency improvement of photovoltaic panels

Solar energy systems have emerged over the last decades as the cleanest and most abundant renewable energy resources available worldwide. Solar trackers are devices specially developed to enhance the energy efficiency of solar energy systems. This paper presents the design and implementation stages of a reconfigurable hardware technology-based two-axis solar tracker platform, specially conceived to improve the energy efficiency of photovoltaic (PV) panels. The main module of this platform is the NI MyRIO ready-to-use development system built upon a high-performance Field Programmable Gate Array (FPGA) processor that controls the entire solar tracker unit. Optimal tracking of the sun movement and obtaining the maximal energy efficiency rate is achieved by simultaneous real-time controlling both the captured sunlight intensity and PV cell temperature magnitudes. In this way, a robust and versatile positioning system has been developed that performs a high precision and accurate tracking pathway. All the control algorithms are implemented there under the LabView graphical programming software toolkit. The final solution boosts in a useful and modularized tracking system that looks useful in a wide range of applications both in industrial and domestic project sites with different power scales.
Do Researchers Affect Economic Growth?

The great scientific development and the great technology, which turned the globe as a whole into a small village, were not the product of a moment or a coincidence, and this great development did not come out of an empty, but was thanks to a considerable and difficult effort, and the enormous contributions of many scientists, inventors and researchers from various regions They have spent their lives studying, researching, contemplating, serving science and various sciences, with sincerity and dedication to advancing themselves and for all of humanity. Without these scientific revolutions and the great effort, they have made, we would not have achieved this great scientific and technological progress which our current era is witnessing at all levels. In this article, using a database that includes 104 countries during the period 1996 -2018, we seek an answer to the following question: Do researchers stimulate economic growth?
LibGuides: Online Resources for Remote Library & Learning : Linking to Library Resources from Canvas

Utilize the information & tools listed in this guide to assist with library usage and online learning in the event that library/campus services are disrupted by Covid-19.
Analysis of Medical Record Sharing Using Blockchain Technology: A Study

Blockchain endeavor on the impression of a digitally disbursed record and consensus algorithm is getting rid of all the threats of intermediaries. Its early applications have been related to the investment/finance zone; however now this conception has been prolonged to nearly all the vital areas of research along with education, Internet of things, bank segment, defense, medical zone etc. Blockchain technology, built over the internet has the potential to use the contemporary healthcare evidence into associates and interoperable manner through using a patient-centric method. In this study the blockchain is used for managing and sharing digital medical records to allow patient role, clinics, and different scientific stakeholders to share histories amongst themselves, due to which the interoperability is maintained. The blockchain construction is based on the entities contributing/connecting to build a series/chain network.
A Review on Blockchain- A Way Forward for Business

Blockchain is a digital phenomenon that is expected to transform the complete meaning to the existence in the market in today’s competitive era.  The papers focuses on the journey of blockchain from inception to implementation with the review in different domains.  The type of blockchain pertaining to the different sector application is emphasized here. Blockchain being the buzz word in the market is considered to be applicable in all the spheres of operation the papers emphasis the conditions that define the applicability of it.  The study aims to bridge the gap by making an individual understand the concept with its application in different sectors in India as. The paper evokes the reader to understand the blockchain system and broader the thinking process in the potential areas. The findings will contribute too many more areas of research in Indian market with reference to Blockchain.
STUDENTS’ PERCEPTION TOWARD ENGLISH SPEAKING ABILITY (A DESCRIPTIVE STUDY OF NINTH GRADE STUDENTS AT SMP NEGERI 18 BANDA ACEH)

The purpose of this study is to identify students’ perception towards English speaking ability.  The researcher used descriptive qualitative research as the method in this study. The Observation and interview were used as the instrument.  To increase the validity of the data, field note was used to support the methodology of the research. After analyzing the data, the researcher found that the students’ perception toward English speaking ability is various. They realized that speaking is an important skill in English to be mastered well. They argued that speaking is important skill to communicate each other especially as the International and global language used in the world. Unfortunately, most of them could not speak English well and fluently, and many students also considered that speaking is difficult to be mastered because of some aspects such as limited vocabulary, less understanding of grammar and also the pronunciation which cannot be practiced well. The result also showed that there are some themes drawn from the interview, namely students’ difficulties, students’ expectation and need of teacher’s assistance.
웹 크롤링의 경쟁법적 고찰

The purpose of the Competition Law is to enhance consumer welfare through free and fair competition in the market. In particular, the nature of search-based services in a data-driven economy requires data to be constantly shared, communicated, and analyzed in the marketplace. The Web crawling, which uses information collection robots to collect necessary information from other websites, is becoming common in the trading world as a new way of collecting the necessary information directly among the numerous information posted on the Internet. Web crawling is an essential act of gathering information in such search-based services, not in itself to limit the operations of others. It is a consumer-friendly mechanism that promotes price and quality competition for products or services and increases consumers’ choice because it can quickly and accurately provide the desired search results, product information, photos, and reviews.Thus, unfair restricting web crawling could impede consumer interests and also create obstruction of business activities for counterparts and competitors. It would be necessary to prevent large online operators from monopolizing information or distorting competition so that various information can be provided to consumers. As to whether it is illegal to crawl copyrighted content or databases, it will be necessary to determine whether crawling is consistent with the fair use of copyright. And if collecting information through crawling helps consumers expand their options and promote their welfare, it is necessary to avoid hastily judging them as violations of the law. The most important thing in the data-driven economy is that operators can compete fairly and that consumers should benefit from competition and innovation, which should not be overlooked in the legal judgment of crawling.
Hubungan antara Sikap dan Penerimaan Pelajar terhadap Amalan Pembelajaran atas Talian

Online learning is the latest method used in national learning system to ensure that the national education system is moving along with other developed countries. The purpose of this study is to examine the relationship between attitudes and acceptance of students towards online learning practices. The dimensions of student attitudes that been used were attitude of students on the ease of use, attitudes towards relative advantages and attitudes towards compatibility of use. Quantitative research methods were used in this study by distributing questionnaires to students from 8 faculties in UTHM, however only 164 students responded to the survey with a response rate of 44%. The data were analyzed using the Statistical Packages for Social Science (SPSS) software. Descriptive and correlation analysis were used to answer the research questions. This study found that both attitude and acceptance of the students towards online learning is at a moderate level. In addition, there is a significant relationship between attitude and acceptance of students towards online learning practices.
Uso de herramientas web en la enseñanza de matemáticas

Este articulo aborda la experimentacion del uso de herramientas web en la ensenanza de las matematicas con estudiantes de los primeros semestres del Instituto Tecnologico Superior de Progreso (ITSP), Yucatan, Mexico. Se describe la experiencia y los retos de implementar clases en linea, que incentiven a los estudiantes a participar y, que ademas, permitan a los estudiantes resolver problemas tanto de manera grupal como individual, estando siempre bajo la supervision del docente. Varias de las herramientas que aqui seran expuestas son parte de la plataforma de Google.Abstract. This article addresses the experiment of using web tools in the teaching of mathematics to students from the first semesters of the Instituto Tecnologico Superior de Progreso, Yucatan. This work describes the experience and challenges of implementing online classes, which encourages students to participate and allows them to solve problems both in groups and individually, always supervised by the teacher. Several of the tools that will be exposed here are part of the Google platform.
Precision-Weighted Federated Learning.

Federated Learning using the Federated Averaging algorithm has shown great advantages for large-scale applications that rely on collaborative learning, especially when the training data is either unbalanced or inaccessible due to privacy constraints. We hypothesize that Federated Averaging underestimates the full extent of heterogeneity of data when the aggregation is performed. We propose Precision-weighted Federated Learning a novel algorithm that takes into account the variance of the stochastic gradients when computing the weighted average of the parameters of models trained in a Federated Learning setting. With Precision-weighted Federated Learning, we provide an alternate averaging scheme that leverages the heterogeneity of the data when it has a large diversity of features in its composition. Our method was evaluated using standard image classification datasets with two different data partitioning strategies (IID/non-IID) to measure the performance and speed of our method in resource-constrained environments, such as mobile and IoT devices. We obtained a good balance between computational efficiency and convergence rates with Precision-weighted Federated Learning. Our performance evaluations show 9% better predictions with MNIST, 18% with Fashion-MNIST, and 5% with CIFAR-10 in the non-IID setting. Further reliability evaluations ratify the stability in our method by reaching a 99% reliability index with IID partitions and 96% with non-IID partitions. In addition, we obtained a 20x speedup on Fashion-MNIST with only 10 clients and up to 37x with 100 clients participating in the aggregation concurrently per communication round. The results indicate that Precision-weighted Federated Learning is an effective and faster alternative approach for aggregating private data, especially in domains where data is highly heterogeneous.
PENGGUNAAN APLIKASI PEMBELAJARAN SELAMA PANDEMI PADA ANAK USIA DINI DI KECAMATAN BUBUTAN SURABAYA

This research is based on the government’s policy that learning must be carried out online due to the Covid-19 pandemic. The purpose of this research is to find out what applications have been used by teachers in Bubutan, Surabaya City during the Covid-19 pandemic to support online learning in early childhood education. The research method used is descriptive qualitative. D ata collection was obtained from the results of a survey conducted by google form and interviews by WhatsApp. The results showed that there were many kinds of online learning support applications during the Covid-19 pandemic such as WhatsApp, zoom, google meet, google classroom, and pear deck. Whatsapp is the most widely used application and Peardeck is an application that is still unfamiliar to be used in the Bubutan, Surabaya City.
Dynamic output feedback fault-tolerant controller design for a class of generalized Takagi-Sugeno fuzzy nonlinear systems

A novel design approach to construct a fault-tolerant control (FTC) system for a class of nonlinear systems based on a generalized Takagi-Sugeno (GT-S) fuzzy model is proposed. The local rules of the GT-S fuzzy model consist of some multiplicative nonlinear terms. The nonlinear system is affected by actuator faults and unknown disturbances. A state/fault observer is designed and then, a dynamic output feedback scheme is proposed based on the estimated fault and state information. The sufficient conditions for observer and controller design are separately given in terms of linear matrix inequalities (LMIs). It can be shown that the number of LMIs and the computational burden is less than that of similar methods and the effectiveness of the proposed dynamic output feedback FTC approach is verified by proposing simulation results applied to an inverted pendulum system.
Explainable AI for non-experts: Is this a chimera?

Artificial intelligence (AI) offers transformative benefits in many areas of economic activity, through the innovative use of profuse, multifaceted streams of data. This power comes at a cost: the systems evolve so organically that the rationale behind its decisions can be a mystery even to its developers. The AI-based system thus becomes a “black box” that is, one that is not transparent, making it difficult to trust the system’s decisions, assess model fairness, detect bias, and meet regulatory demands. These concerns have led to the consideration of explainable AI (XAI) as a cognitive bridge between the two worlds. However, the majority of deployments are for machine learning engineers. Thus there is a need for human-understandable AI systems that can tailor explanations relative to the needs, knowledge, and goals of non-experts. This essay explores some of the literature over the past half century pertaining to the explainability needs of different stakeholders, including efforts made to address such needs as well as lessons learned.
The Queen's Gambit. Un perfect match tra immaginario ludico e calcoli algebrici = The Queen's Gambit. A perfect matching between game imagery and algebraic strategies

The streaming video platforms, like Netflix and Amazon Prime Video, continue to grow up the original content titles, proposing changes and variation without being choked by the production costs. Something that would have been impossible in the past decade. Today, the platforms can provoke such broad interest exploiting in one shot a double effect of revenue maximizing and effort minimizing: a combination of executives' intuition and analytics suggestion about the best-watching movie or series. The Queen's Gambit, produced by Netflix last year, ranked everywhere at first position in the first month, is not unfamiliar to this classification. In this work we try to deconstruct the main features that have achieved worldwide prominence: the script's ability to maintain an equilibrium between originality and curiosity, weirdness and popular attitudes (at worst addictions) with which the general audience could recognize themselves or the neighbor. We focus the attention on the more interesting contribution of the subject, a mixture between logic of chess strategies and imagination of the player. Not only this pattern opens the path of the success but becomes the central point of main topics' attraction around the story (the changing of the fashion, the brand female evolution, the prodigy addiction, the friction between instinct and education).
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering

Standard first-order stochastic optimization algorithms base their updates solely on the average mini-batch gradient, and it has been shown that tracking additional quantities such as the curvature can help de-sensitize common hyperparameters. Based on this intuition, we explore the use of exact per-sample Hessian-vector products and gradients to construct optimizers that are self-tuning and hyperparameter-free. Based on a dynamics model of the gradient, we derive a process which leads to a curvature-corrected, noise-adaptive online gradient estimate. The smoothness of our updates makes it more amenable to simple step size selection schemes, which we also base off of our estimates quantities. We prove that our model-based procedure converges in the noisy quadratic setting. Though we do not see similar gains in deep learning tasks, we can match the performance of well-tuned optimizers and ultimately, this is an interesting step for constructing self-tuning optimizers.