Reviewerly/exHarmony huggingface dataset:
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data

Event forecasting is a challenging, yet important task, as humans seek to constantly plan for the future. Existing automated forecasting studies rely mostly on structured data, such as time-series or event-based knowledge graphs, to help predict future events. In this work, we aim to formulate a task, construct a dataset, and provide benchmarks for developing methods for event forecasting with large volumes of unstructured text data. To simulate the forecasting scenario on temporal news documents, we formulate the problem as a restricted-domain, multiple-choice, question-answering (QA) task. Unlike existing QA tasks, our task limits accessible information, and thus a model has to make a forecasting judgement. To showcase the usefulness of this task formulation, we introduce ForecastQA, a question-answering dataset consisting of 10,392 event forecasting questions, which have been collected and verified via crowdsourcing efforts. We present our experiments on ForecastQA using BERT-based models and find that our best model achieves 60.1% accuracy on the dataset, which still lags behind human performance by about 19%. We hope ForecastQA will support future research efforts in bridging this gap.
Сontent, structure and functions of university pedagogical education

The pedagogical process at university is considered as an integral scientific and educational system, which is characterized by interconnection, unity of functioning, internal ordering of components and specific relationships between them. This system has its own specific content, structure and features. Hereby the core of professional and pedagogical training of specialists is considered, which, due to the openness of the pedagogical process at university, includes constant and variable block-modular components. The permanent ones include general education, special, psychological and pedagogical, cultural, research and practical blocks of training a highly qualified professional teacher. Variables include blockmodular cycles of disciplines that take place in the professional and pedagogical training of a teacher, depending on his specialty, specialization and profile, as well as professional interests, needs, opportunities, in general, the concept of future life. The meaning of the main structural components unity and their corresponding functions are revealed, which successively and cyclically replace each other and thereby form a certain pedagogical technology. It consists of the processes of goal-setting, defining tasks, planning and organizing execution, communicating, monitoring, correcting and evaluating the results of the activities of learning subjects, as well as designing a new stage in the pedagogical process. The article substantiates the position that the study of the content, structure and functions of pedagogical education makes it possible to identify promising trends that allow to outline the ways of improving the pedagogical process at the university.
Perancangan Alat Pakan Ikan Otomatis Berbasis Microcontroler Dengan Menggunakan Metode Quality Function Deployment (QFD) (Studi Kasus: Petani Ikan, Sragen)

Fisheries have an important role in efforts to improve the quality and quantity of production that aims to increase income and living standards of people in Indonesia. This research is aimed at making an automatic fish feeder that reduces workload, costs and working time. The tools must be made according to the needs of fish farmers. Therefore the QFD method is appropriate for this study. The Voice of Customer analyzed is then processed using the House of Quality to produce a design of tools and components using an automatic dynamo drive system based on the Arduino Microcontroller. Based on the test results of the automatic fish feeder, the results show that the tool can reduce the workload by accommodating as much as 25 kg of feed,saving costs up to Rp 734, - per day, and spending 25 seconds for feeding 1 fish pond which makes this automatic fish feed tool minimize work time.Keywords: Fish Consumption, HOQ, QFD, Arduino Microcontroller
감정분석 시각화를 통한 소설과 영화의 비교 : 모비딕 중심으로

The purpose of this study is to compare the maritime novel ‘Moby Dick‘ with the novel based-film through the visualization of sentiment analysis using the VADER sentiment word-list. We use line charts as time visualization in the normalized positive and negative sentiment valence sum. The line charts show how the novel or its film has emotional ups and downs within each Act and across Acts in the accumulated sentiment valence. This study also re-examines the influence on Moby Dick that the Four Great Tragedies of Shakespeare such as Hamlet, Othello, King Lear, and Macbeth have had, which has long been discussed in the previous research, focusing on the comparison of the novel and its film to these tragedies. The results of this paper illustrate that the film can be distinctively compared with its original novel through time visualization of sentiment analysis within Acts and between Acts. It is also illustrated that the line chart of the novel ‘Moby Dick’ is similar to those of Othello and Hamlet, whereas the line chart of the film ‘Moby Dick’ released in 1998 is similar to those of King Lear and Macbeth. These results are expected to contribute to research and education of digital humanities and artificial intelligence for English literature as a solid case study, in the era of the 4th industrial revolution.
STUDENTS’ VIEWS ON ENGLISH LITERATURE TEACHING (A STUDY AT THE ENGLISH UNDERGRADUATE PROGRAM OF SYIAH KUALA UNIVERSITY)

Abstract Name: Pharisaa Darni Student Number: 1509200080007 Study Program: Master Degree in English Education Department: English Education Title: Students’ Views on English Literature Teaching (A Study at the English Undergraduate Program of Syiah Kuala University) Keywords: Student’s View, Literature, Literature Teaching This study aimed at investigating the students’ views on English literature teaching at the English Education Undergraduate Program of Syiah Kuala University. It also tried to find out the importance of learning English Literature for students from the lecturers’ views. A mixed method of both descriptive quantitative and qualitative approach was used as the research design in this study. The data were collected by giving fifteen items of questionnaire for 30 students and interviewing three lecturers of the English Literature course in order to attain the needed data for this study. The results of data from questionnaire were analyzed by using percentage formula from Sudijono (2005), while the interview results were analyzed by using procedure of data analysis from Miles and Huberman (1992). The research findings show that students view literature is an important discipline because it improves language skill (i.e. reading, writing) and communication skill, teaches social and political values, and enriches culture learning. In conclusion, literature is the study of standard language and socio-cultural values theoretically and practically.
Bayesian graphical modelling for heterogeneous causal effects.

Our motivation stems from current medical research aiming at personalized treatment using a molecular-based approach. The goal is to develop a more precise and targeted decision making process, relative to traditional treatments based primarily on clinical diagnoses. A challenge we address is evaluating treatment effects for individuals affected by Glioblastoma (GBM), a brain cancer where targeted therapy is essential to improve patients' prospects. Specifically, we consider the pathway associated to cytokine TGF-beta, whose abnormal signalling activity has been found to be linked to the progression of GBM and other tumors. We analyze treatment effects within a causal framework represented by a Directed Acyclic Graph (DAG) model, whose vertices are the variables belonging to the TGF-beta pathway. A major obstacle in implementing the above program is represented by individual heterogeneity, implying that patients will respond differently to the same therapy. We address this issue through an infinite mixture of Gaussian DAG-models where both the graphical structure as well as the allied model parameters are regarded as uncertain. Our procedure determines a clustering structure of the units reflecting the underlying heterogeneity, and produces subject-specific causal effects through Bayesian model averaging across a variety of model features. When applied to the GBM dataset, it reveals that regulation of TGF-beta proteins produces heterogeneous effects, represented by clusters of patients potentially benefiting from selective interventions.
Digital graphic organizers as a tool to foster reading comprehension

Foreign language learners have difficulties understanding texts because they try to code and decode in their mother tongue; then, the necessity of looking for a strategy to help them is crucial. The objective of this research is to show how digital graphic organizers (DGOs) help students develop reading comprehension, especially in understanding the evolution of the English language. The review of different theories about DGOs guided to identify a proto-typed model of analysis and design digital activities to represent students' understanding of a text. Methodologically, an experimental design consisting of pre and post-treatment tests were applied in the control and experimental group, during fall 2019 in the English Language Teaching Bachelor at BUAP, on a sample of 60 subjects. A treatment phase (didactic intervention) to prove the suitability of the proposal took place by using DGOs as a tool to promote reading comprehension of texts and knowledge representation. The most outstanding results were a deeper understanding of facts, historical events, the ability to synthesize information with DGOs, and the motivation to read about historical events. In conclusion, this way of developing understanding and representation of the knowledge was perceived positively by the subjects.
Steganography Using Kmeans Clustering Algorithm

The growth of high speed computer networks and particularly that of the internet has increased the ease of communication and transfer of data. The down sight of this discovery is the fear of getting ones data snooped or intruded during the time of transfer from one person or group of people to another. Many people forget that, just as the growth in internet, so has the growth is many attack techniques which are aimed at stealing and destroying these data. Data is an important aspect of every organisation so it needs to be protected at all cost. To combat these attacks and attackers, many security methods have been introduced. In all the many security measures employed, steganography stands out and is one of the most common methods of securing data to be transferred through the internet. Steganography is the method of stowing away classified information inside any media. Steganography involves hiding of text, image or any sensitive information inside another image, video or audio in such a way that an attacker will not be able to detect its presence. In this paper, we propose a technique where a sample data is first clustered using a clustering algorithm known as kmeans clustering algorithm and then the output of the clustering is then hidden using image steganography to provide a security layer to that data.
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning

In this paper, we consider a transfer Reinforcement Learning (RL) problem in continuous state and action spaces, under unobserved contextual information. For example, the context can represent the mental view of the world that an expert agent has formed through past interactions with this world. We assume that this context is not accessible to a learner agent who can only observe the expert data. Then, our goal is to use the context-aware expert data to learn an optimal context-unaware policy for the learner using only a few new data samples. Such problems are typically solved using imitation learning that assumes that both the expert and learner agents have access to the same information. However, if the learner does not know the expert context, using the expert data alone will result in a biased learner policy and will require many new data samples to improve. To address this challenge, in this paper, we formulate the learning problem as a causal bound-constrained Multi-Armed-Bandit (MAB) problem. The arms of this MAB correspond to a set of basis policy functions that can be initialized in an unsupervised way using the expert data and represent the different expert behaviors affected by the unobserved context. On the other hand, the MAB constraints correspond to causal bounds on the accumulated rewards of these basis policy functions that we also compute from the expert data. The solution to this MAB allows the learner agent to select the best basis policy and improve it online. And the use of causal bounds reduces the exploration variance and, therefore, improves the learning rate. We provide numerical experiments on an autonomous driving example that show that our proposed transfer RL method improves the learner's policy faster compared to existing imitation learning methods and enjoys much lower variance during training.
KEPAHAMAN DAN KESIAPAN MAHASISWA ATAS PENGGUNAAN TEKNOLOGI INFORMASI DALAM SISTEM INFORMASI AKUNTANSI TERHADAP KUALITAS INFORMASI AKUNTANSI DENGAN ETIKA SEBAGAI MODERATING VARIABLE

This study aims to obtain empirical evidence regarding students' perceptions of their understanding and readiness as users of information technology in accounting information systems on information quality. Also, the following research was conducted to obtain empirical evidence of the influence of ethical aspects in the use of information technology on information quality. Purposive sampling was chosen as a method of collecting data from the respondents of undergraduate accounting students. Of the total population, 75 respondents were sampled. Data were analyzed using SPSS statistical analysis with descriptive test technique, multicollinearity test, heteroscedasticity test, classical assumption test, and absolute difference value test. The result is that the understanding and readiness of information technology users in the accounting information system affects the quality of accounting information and user ethics becomes a moderating variable that strengthens this influence.
Intensive Batch Scheduling Application for Parallel Programming In the Cloud Computing Infrastructure

Enterprises are gathering and analyzing an increasing number of large amounts of facts to be able to derive enterprise insights.Two challenges to fulfill.First, in parallel programming is together time-consuming and error-susceptible.Second, the developing Cloud Computing paradigm executes the primary infrastructure, which armies Enterprises to reconsideration their request structure.Now we advocate massive scale data-intensive batch troubles below the Cloud infrastructure restraints.A programming version and fleeces the difficulty of parallel programming, it offers the customers broad manipulate on facts separated and distribute calculation the applications.We reap high overall performance in computing Cloud and parallel programming is much less time and performance.
An Empirical Comparison of Instance Attribution Methods for NLP

Widespread adoption of deep models has motivated a pressing need for approaches to interpret network outputs and to facilitate model debugging. Instance attribution methods constitute one means of accomplishing these goals by retrieving training instances that (may have) led to a particular prediction. Influence functions (IF; Koh and Liang 2017) provide machinery for doing this by quantifying the effect that perturbing individual train instances would have on a specific test prediction. However, even approximating the IF is computationally expensive, to the degree that may be prohibitive in many cases. Might simpler approaches (e.g., retrieving train examples most similar to a given test point) perform comparably? In this work, we evaluate the degree to which different potential instance attribution agree with respect to the importance of training samples. We find that simple retrieval methods yield training instances that differ from those identified via gradient-based methods (such as IFs), but that nonetheless exhibit desirable characteristics similar to more complex attribution methods. Code for all methods and experiments in this paper is available at: this https URL
전시기획사 직무분석 및 컨벤션기획사와의 비교에 관한 연구

The purpose of this study is to analyze the job of PEO (Professional Exhibition Organizers) by using a DACUM(Developing A Curriculum) method. And to analyze similarities and differences of the jobs’ definitions, certificates, duties, tasks, knowledge, skills, behavioral attitudes, tools of PEO for expanding their academic background and finding practical implications for PEO. The DACUM job analysis of PEO is conducted, and two experts of human resources development and a MICE content specialist conduct the task of comparing the duties of the PEO and the PCO. And then, they confirm the content validity of the analysis. First, the job description of PEO reveals 8 duties and 92 tasks. The duties are planning exhibitions, marketing to exhibitors, marketing to buyers and participants, advertising and promotion, official event, exhibition joint event, exhibition operation and post management. Second, the DACUM analysis find the duties, tasks, knowledge, skills, behavioral attitudes and tools of PEO. Finally, we find that the differences and similarities between PEO and PCO and reveal the theoretical and practical implications.
Low-cost stereo-based obstacle avoidance for small UAVs using uncertainty maps

The last years there is a wide interest in UAVs which can be attributed to their low cost and wide range of use in recreational, commercial and scientific applications. Despite the large increase in drones, UAV flights are permitted only in secluded areas. In order to be granted access to public areas, it must prove its capacity to sense and safely avoid collisions with other obstacles. Therefore, the need for a secure and reliable CAS is imperative. In this thesis a low-cost, low computationally demanding, stereo-based, robust CAS solution for small UAVs is designed, assuming flights primarily in an outdoor environment. In order to address this problem, firstly the existing dense stereo open-source algorithms are reviewed based on their suitability for obstacle avoidance and their computational complexity. Based on a semantic evaluation and profiling, the review concludes that BM should be preferred for low-cost obstacle avoidance and SGBM should be used only in highly textureless environments. Subsequently, since the imperfect accuracy of any existing stereo solution is a fact, a machine learning method is introduced in order to predict the uncertainty of the stereo measurements. This so called “uncertainty map” method assigns an uncertainty value to every image pixel. It was shown that it can successfully predict the uncertainties of BM and SGBM stereo algorithms. Furthermore, a low-cost collision avoidance method was proposed which makes use of uncertainty map in sensing filtering, collision detection and path planning. The evaluation showed that the use of uncertainty map improves both collision detection and path planning, especially when BM is used. Last but not least, the whole CAS was implemented in an embedded system Raspberry Pi 3 model B+. Results show that real-time execution of the propsoed CAS with a runtime frequency of 4-54 Hz is possible when BM is used and 1-16 Hz when SGBM is used.
PEMANFAATAN TUTUP BOTOL SEBAGAI MEDIA PEMBELAJARAN BAHASA INGGRIS DAN MATEMATIKA

This community service activity was carried out at the Qurrataa'yun Kindergarten, Air Joman Excellence Village. The number of participants in this service amounted to 30 students. The background of this dedication is the lack of children's interest in counting and learning English. This situation reduces the value of children's enthusiasm when learning. The solution given to the problem above is the use of bottle caps as a medium for learning English and mathematics. Community service activities utilize used goods as a medium for learning English and Mathematics. Used goods are used in the form of drink bottle caps which are then wrapped in colorful origami paper. Then the bottle cap will be attached by the students to the cardboard paper. Then the students must paste the bottle cap in sequence according to the numbers written on the cardboard. After putting the bottle cap on, the students must be able to pronounce the names of the colors of the bottle caps in English. Students are very enthusiastic in participating in this series of activities so as to increase students' understanding and motivation in learning to count and recognize colors in English. Teachers in Qurrataa'yun Kindergarten are increasingly using used materials as a medium for student learning so that student interest in learning increases. Keywords : English, Mathematics, Learning Media, Bottle Caps
FORMATION OF THE COMMUNICATIVE AND OPERATIONAL GRAPHIC COMPETENCIES OF THE ARCHITECTURE STUDENTS

The publication is devoted to the problem of the formation of the communicative and operational graphic competencies of the architecture students. The parallels are drawn between the design and artistic activities of the students. The forms of search and implementation of a creative idea by the graphic means are studied. The paper reveals modern approaches to the professional communication by graphic methods, means of forming environmental mise-en-scenes, featuring the functional and activity, emotional and figurative, etc. components of the architectural concept. The parallels are drawn between the theatrical and scenographic approach, cinema storyboard and the method of featuring sequential environmental impressions in the architectural sketches. The potential of formal art in enhancing the emotional-compositional component of students’ works are researched.
Coalgebra and Abstraction

Frege’s Basic Law V and its successor, Boolos’s New V, are axioms postulating abstraction operators: mappings from the power set of the domain into the domain. Basic Law V proved inconsistent. New V, however, naturally interprets large parts of second-order ZFC via a construction discovered by Boolos in 1989. This paper situates these classic findings about abstraction operators within the general theory of F-algebras and coalgebras. In particular, we show how Boolos’s construction amounts to identifying an initial F-algebra in a certain category, we identify a natural coalgebraic dual to Boolos’s axiom which naturally interprets large parts of Aczel’s non-well-founded set theory via the construction of a certain terminal F-coalgebra, and we suggest a coalgebraic way forward for an abstraction-theoretic axiomatization of the real numbers.