Reviewerly/exHarmony huggingface dataset:
Concealed questions without meta-meta-questions

Sentences like John knows the price that Fred knows are ambiguous between ‘Reading A’ and ‘Reading B’. When such sentences have a further embedding, existing analyses predict ‘Reading C’ that involves meta-meta-questions. This paper presents an analysis in which the escalating ambiguity disappears when the referent of concealed question DP has a proper name. I show that Reading C is reduced to a version of Reading B without meta-meta-questions. The proposal is based on the idea that questions are given different interpretations depending on the perspective taken to identify entities in the domain.
Pelatihan Penyusunan Alat Evaluasi Berbasis Teknologi Informasi Dan Komunikasi ( Program Wondershare Quiz Creator) Untuk Guru SDN Airlangga I Surabaya

The community service program in the 2018 budget year was carried out with the aim of organizing community empowerment programs throughout the UPBJJ-UT region which included efforts to improve education and community welfare. Based on a description of the situation analysis of the partners/ assisted communities, the community service activities carried out were training in the development of information and communication technology-based evaluation tools (Wondershare Quiz Creator Program) for teachers of Airlangga I Elementary School in Surabaya. The implementation of this training activity is to provide understanding and skills on how to design and apply the wondershare quiz creator program in the development of evaluation tools for student learning outcomes. One of the targets to be achieved through community service activities is the change in attitude and improvement of the skills of partner communities so that the teachers of Airlangga I Elementary School Surabaya can develop evaluation tools for student learning outcomes using software wondershare quiz creator. The training was conducted with lecture methods, slide and video screenings, question and answer, interactive dialogue, opinion sharing and work practices.Community service activities as a whole are carried out in a span of 6 months (June - November 2018), starting from the planning, preparation, and implementation stages. In implementing community service, the team collaborated with lecturers from University of Wijaya Kusuma Surabaya namely the Language and Science Faculty as keynote speakers and instructors. The target community are teachers at Airlangga I Elementary School Surabaya and several teachers from Public and Private Elementary Schools from Gubeng District, Surabaya. The results of community service can be seen from the results of evaluating the processes, products, and participants' responses to the implementation of the training collected through the satisfaction questionnaire. In the process of implementing the training, partners generally have a great willingness and interest to take part in the training.
AMPRO-HPCC: A Machine-Learning Tool for Predicting Resources on Slurm HPC Clusters.

Determining resource allocations (memory and time) for submitted jobs in High Performance Computing (HPC) systems is a challenging process even for computer scientists. HPC users are highly encouraged to overestimate resource allocation for their submitted jobs, so their jobs will not be killed due to insufficient resources. Overestimating resource allocations occurs because of the wide variety of HPC applications and environment configuration options, and the lack of knowledge of the complex structure of HPC systems. This causes a waste of HPC resources, a decreased utilization of HPC systems, and increased waiting and turnaround time for submitted jobs. In this paper, we introduce our first ever implemented fully-offline, fully-automated, stand-alone, and open-source Machine Learning (ML) tool to help users predict memory and time requirements for their submitted jobs on the cluster. Our tool involves implementing six ML discriminative models from the scikit-learn and Microsoft LightGBM applied on the historical data (sacct data) from Simple Linux Utility for Resource Management (Slurm). We have tested our tool using historical data (saact data) using HPC resources of Kansas State University (Beocat), which covers the years from January 2019 - March 2021, and contains around 17.6 million jobs. Our results show that our tool achieves high predictive accuracy R2 (0.72 using LightGBM for predicting the memory and 0.74 using Random Forest for predicting the time), helps dramatically reduce computational average waiting-time and turnaround time for the submitted jobs, and increases utilization of the HPC resources. Hence, our tool decreases the power consumption of the HPC resources.
Towards Taming the Adaptivity Problem

Systems following the Polyglot Persistence paradigm are on the rise and with them come new problems and challenges. A major challenge is the ability to automatically self-adapt to changing requirements and workloads. The most difficult and as yet rarely discussed form of adaptivity relates to cahanges to the underlying data composition and topology. The search for a topology suited best for a given set of requirements can be modelled as a complex optimization problem.This paper proposes and formalizes Blueprints, which we define as graphs representing functional units composed of (heterogeneous) data stores. Blueprints can be used as manageable, predefined building blocks to form the highly complex system topologies Poly- and MultiStores use internally. Subsequently, the optimization search space can be limited to a set of Blueprints, which can be matched against the Poly-/MultiStores’ requirements. Furthermore, we discuss System requirements and their impact on adaptivity decisions and identify future research directions building upon our Blueprint concept.
Multimode quantum networking with trapped ions

Envisioned large-scale quantum networks demand the ability to rapidly distribute and store entanglement between remote matter-based nodes using photons [1] . The minimum time required to distribute entanglement between two nodes is the time it takes light to travel between them, which over 100 km distance already 0.33 ms. The speed of light thus sets a fundamental limit on the achievable entanglement distribution rate: with a single quantum emitter in a node, one has to wait for the photon travel time before trying again with a new photon for any application that would require also classical communication (e.g. to realize a quantum repeater) [2] . Over 100 km of fiber, this limits the entanglement distribution attempt rate to 2 kHz and, given 1.5% transmission in the best telecom fibres, a success rate of 30 Hz. This is a general problem for entanglement distribution over long distances as far higher rates are critical for the practical realisation of quantum networks and their applications. To overcome this limit, several entanglement distribution attempts have to be done in parallel. This requires multiple modes of the node (memory qubits) to couple selectively to the multiple modes of the link.
Pedagogical paradigms of professional training of future engineers in the conditions of educational and information environment of technical university

The article identifies and analyzes the paradigm of educational information environment formation in the technical higher educational institutions. The authors presented the paradigm based on the humanitarization of higher education, which aims to provide valuable guidance and motivation to establish criteria for creating conditions for self-development and personal fulfillment of future engineers. The article argues that revealing of the integrity of education and regulating scientific, research and practical innovation of training activities and educational paradigm should be considered in conjunction. The pedagogical paradigms of professional training of future engineers in the educational and information environment of a technical university enable determining the content of academic disciplines. In general, the analysis of the dynamics of formation and development of the paradigm helps to preserve the principles of learning and a genetic nucleus of the national pedagogical science and practice.
Making your repository more trustworthy and FAIR-enabling a support programme

FAIRsFAIR is supporting 10 European repositories on their journey towards becoming more FAIR-enabling and trustworthy. This includes helping them make and keep their data FAIR and preparing them for the CoreTrustSeal certification as trustworthy repositories. In return, the repositories share their invaluable knowledge on how trustworthy repository practices best enable FAIR data. Their observations and common issues in the certification process help create better guidance and support material for the wider repository community, developing recommendations for integrating FAIR into the CoreTrustSeal requirements.
Solar Irradiation Prediction Using Weather Forecast Data

Solar radiation is an important parameter for the planning and operation of solar energy systems. Black-out occurs when the proportion of electricity that has been provided is greater or lesser than the proportion of electricity devoured. This has become an extra compound due to the hike in renewable energy, largely due to weather. Conventional power plants need to reach up to speed with these consistent variations as it is difficult to store power in enormous amounts throughout a prolonged time frame. The major objective of this work is to discover a machine learning model which accurately forecasts solar radiation. In this work, Linear Regression, ElasticNet, Gradient Boosting Regressor, Support Vector Regression, Random Forest Regressor, Extra Trees Regressor, Sequential and MultiLayer Perceptron models are used. The evaluation measures which are used in this work to identify the best model are MAE and RMSE.
A CONCEPTUAL FRAMEWORK ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN HUMAN RESOURCE MANAGEMENT

Though, Artificial Intelligence (AI) concept has been around for a while but it gained popularity recently.AI technologies are growing relentlessly and constantly and experts believe that now is the right time to permeate AI into almost all fields and functional areas and forge AI as a real sophisticated tool in the hands of humans. Having in mind the above points, the study proposes a conceptual framework of state of-the art AI technologies currently being used in IT industry and its application in human resource practices. An attempt has been made to synchronize human resource management functions such as planning, recruitment, training, performance management, decision making, employee engagement and work-life balance with its potential corresponding AI technology applications. Information from relevant books, websites, reports, working papers, magazines, conceptual papers, various peer reviewed journal articles are used to explore the concept.
Research status and hotspot analysis of literature metrology in artificial intelligence field

Abstract It is of great significance to describe the innovation track of emergency management digital research through metrology for better grasping the theoretical system and subject frontier, and promoting the practice of emergency management digital. In this paper, artificial intelligence (AI) papers published in the world from 2010 to 2019 in the SCI database of Web of Science are taken as the research object to explore the influence of countries in the field of AI research and the current hot areas, so as to provide data support and decision-making reference for AI policy making. It is found that in the process of the development of the digitalization of emergency management from scratch, a novel and complete research system has been formed, which takes the digitalization of emergency management technology as the core and takes the digitalization of emergency management organization, the digitalization of emergency management environment and the digitalization of emergency management objects as the foundation. Further studies have found that digital frontier including emergency management in large data, mobile Internet, Internet of things, technology innovation, and AI as the representative of volunteers to digital citizens in emergency management, digital and digital community, represented by the main body of innovation, and to no one digital dynamic emergency management and the digitization of emergency management as a representative of management innovation. Finally, the study concludes that the digital integration of emergency management consists of two parts: risk information and emergency response.
Hybrid Teleportation Protocols for Heterogeneous Quantum Networks

The wave-particle duality of light has led to two different encodings of optical quantum information. One approach, referred to as the discrete-variable (DV) one, relies on finite dimensional quantum systems, while the other one, referred to as the continuous-variable (CV) one, is based on wave-like states belonging to an infinite dimensional Hilbert space. These two encodings have historically been separated, but recently, new hybrid protocols which aim at combining the advantages of the two encodings have emerged [1] . In that prospect our recent demonstration of the measurement-induced generation of hybrid entanglement between discrete- and continuous-variable quantum states [2] , [3] , located at distant places and connected by a lossy channel, has opened the way to the implementation of hybrid protocols and heterogeneous quantum networks. Following the first protocols based on this resource, such as the remote preparation of continuous-variable qubits [4] , or a violation of an Einstein-Podolsky-Rosen steering inequality [5] , we will here report our latest experimental results on entanglement swapping and quantum teleportation protocols using hybrid entangled states based on different encodings [6] .
Legal and moral infrastructure of the innovation and creativity system

Context: The most important pillar of the development of any country is research. Therefore, developed countries spend a considerable amount of their gross income on research, and as a result, the job of some people has been research. The distinctive feature of the research from other activities, such as study is creativity, and systematic innovation in the scale of knowledge that has made enterprises and even countries competitive. The more innovation and creativity in a country is, the better it is in terms of credibility over other countries. Innovation and creativity require specific infrastructure, one of which is legal and moral infrastructure. Purpose: The purpose of this study is to investigate the legal and moral infrastructure of creativity in society. Method: The research method is quasi-experimental. First, by examining the texts and interviewing the experts, the ethical and legal factors affecting creativity were extracted, and then, using the Demethan theme, relationships between them were examined. The statistical population of all experts in the field of ethics, law, creativity and innovation is the statistical sample of 30 people who have been selected as snowstorms. Results: The analysis of the results shows that shortcomings, over-opportunities, easy access to judicial courts, the recognition of the individual and social effects of virtues, proper laws and the existence of transparency are the most important causes of human morality. The social environment, education, adherence to patterns of morality, the recognition of virtues and vices, the implementation of the lawlessness of the law, the recognition of virtues rewards, and the recognition of punishments are causing disadvantages. Conclution: In order to observe the ethics of research, it must first be trained and the models, especially the sovereignty, should adhere to intellectual property rights. It is also easy to have access to judicial tribunals to investigate research offenses.
WORKSHOP PEMANFAATAN INTERNET UNTUK SUMBER BELAJAR BAHASA INGGRIS DALAM MENINGKATKAN KINERJA GURU SD DI KECAMATAN DANAU TELUK KOTA JAMBI

The need to apply science and technology is becoming an increasingly important need. For educators, the need for mastery of technology is something that must be mastered to support the learning process. The aim of this program is to equip elementary school teachers with mastery of using the Internet to facilitate the search for English learning resources and to introduce and deepen their knowledge of English learning aid sites to improve teacher performance. There are five stages in implementing a community service program to find English learning resources in Internet Usage Seminars: Introduction Stage, Social and Audience Stage, Development Stage, Internet usage training and final assessment stage. The conference lasted for two days. The first day of activity is in the form of material procurement. The second day focused on Internet usage practices. Keywords: internet workshop, teacher, english, learning resources
THE EFFECTIVENESS OF THE PICTURE STORY METHOD IN INCREASING STUDENT'S READING INTEREST CLASS 2 AT SOURCE STATE ELEMENTARY SCHOOL, BANDUNG: indonesia

Abstract Student’s reading interest Elementary school, especially grade 2 SD Sumber Bandung, is still low because they prefer to play online games, watch television, etc. This factor causes their reading ability is still lacking. In addition, there are reading books in school institutions that are still monotonous without pictures so that children get bored easily and are not interested in reading them. This study purposed to see how effectiveness of pictural story book in increasing reading inters of grade 2 students at SD Sumber Bandung. The method has been use in this research is an experimental research method with one group pre test – post test design. The use of learning media to foster children's interest in reading is by using picture story books. This picture book is more developed if the teacher dares to be creative. This picture story book is effectively used in the second grade students of SD Sumber Bandung because it includes games and education. In the picture story book there are several learning activities including observing, telling, reading and sorting the pictures so that they become a complete story. Furthermore, the teacher can add / collaborate on strategies or methods that can support the use of other picture story books to be more innovative in each lesson. The result of this research is that picture story books are very effective in increasing reading interest of student Grade 2 SD sumber bandungKeywords :; Story book; interest in reading,  SD Sumber Bandung
ANALISIS MAKNA DIKSI LIRIK LAGU â€œSATUâ€ MILIK DEWA 19 DENGAN MENGGUNAKAN PENDEKATAN SEMIOTIK

A song that has lyrics with a deep meaning or meaning is always popular even though it has been lyrical for a long time, in the creation of song lyrics, there are language games such as games in language style and word meanings. Dhani's songs with Dewa 19 are often judged to have controversial lyrics in the lyrics, the word "I" and the "You" do not always describe someone who is expressing feelings with their soulmate. The owner of this song also often describes the relationship between man and the creator. The song 'Satu' is an example. This research is to analyze a meaning in the one song lyrics. The method used is descriptive qualitative method by dividing the lyrics into several verses, with a semiotic approach the song lyrics are divided into markers and signs and then analyzed to determine their meaning. The research was carried out in several steps, (1) determining the song, (2) dividing it into several verses, (3) determining the markers and signs, (4) analyzing the meaning, (5) describing the results. The results of the authorâ€™s analysis on the lyrics of the song Satu Dewa 19 by Ahmad Dhani concluded that the lyrics contain meaning that implies oneâ€™s obedience to God.
On solving non-homogeneous partial differential equations with right-hand side defined on the grid

An algorithm is proposed for obtaining solutions of partial differential equations with right-hand side defined on the grid $\{ x_{1}^{\mu}, x_{2}^{\mu}, \ldots, x_{n}^{\mu}\},\ (\mu=1,2,\ldots,N)\colon f_{\mu}=f(x_{1}^{\mu}, x_{2}^{\mu}, \ldots, x_{n}^{\mu}).$ Here $n$ is the number of independent variables in the original partial differential equation, $N$ is the number of rows in the grid for the right-hand side, $f=f( x_{1}, x_{2}, \ldots, x_{n})$ is the right-hand of the original equation. The algorithm implements a reduction of the original equation to a system of ordinary differential equations (ODE system) with initial conditions at each grid point and includes the following sequence of actions. We seek a solution to the original equation, depending on one independent variable. The original equation is associated with a certain system of relations containing arbitrary functions and including the partial differential equation of the first order. For an equation of the first order, an extended system of equations of characteristics is written. Adding to it the remaining relations containing arbitrary functions, and demanding that these relations be the first integrals of the extended system of equations of characteristics, we arrive at the desired ODE system, completing the reduction. The proposed algorithm allows at each grid point to find a solution of the original partial differential equation that satisfies the given initial and boundary conditions. The algorithm is used to obtain solutions of the Poisson equation and the equation of unsteady axisymmetric filtering at the points of the grid on which the right-hand sides of the corresponding equations are given.
Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings

Adversarial robustness of deep models is pivotal in ensuring safe deployment in real world settings, but most modern defenses have narrow scope and expensive costs. In this paper, we propose a self-supervised method to detect adversarial attacks and classify them to their respective threat models, based on a linear model operating on the embeddings from a pre-trained self-supervised encoder. We use a SimCLR encoder in our experiments, since we show the SimCLR embedding distance is a good proxy for human perceptibility, enabling it to encapsulate many threat models at once. We call our method SimCat since it uses SimCLR encoder to catch and categorize various types of adversarial attacks, including L_p and non-L_p evasion attacks, as well as data poisonings. The simple nature of a linear classifier makes our method efficient in both time and sample complexity. For example, on SVHN, using only five pairs of clean and adversarial examples computed with a PGD-L_inf attack, SimCat's detection accuracy is over 85%. Moreover, on ImageNet, using only 25 examples from each threat model, SimCat can classify eight different attack types such as PGD-L_2, PGD-L_inf, CW-L_2, PPGD, LPA, StAdv, ReColor, and JPEG-L_inf, with over 40% accuracy. On STL10 data, we apply SimCat as a defense against poisoning attacks, such as BP, CP, FC, CLBD, HTBD, halving the success rate while using only twenty total poisons for training. We find that the detectors generalize well to unseen threat models. Lastly, we investigate the performance of our detection method under adaptive attacks and further boost its robustness against such attacks via adversarial training.