Reviewerly/exHarmony huggingface dataset:
Auto-Select Reading Passages in English Assessment Tests?

We show a method to auto-select reading passages in English assessment tests and share some key insights that can be helpful in related fields. In specifics, we prove that finding a similar passage (to a passage that already appeared in the test) can give a suitable passage for test development. In the process, we create a simple database-tagger-filter algorithm and perform a human evaluation. However, 1. the textual features, that we analyzed, lack coverage, and 2. we fail to find meaningful correlations between each feature and suitability score. Lastly, we describe the future developments to improve automated reading passage selection.
The financial and cash stability and its role in financial sustainability in Iraq

In Iraq and during the last three years, it has appeared and develop of general budget deficitand increasing of general debt, accordingly most of the specialists in the financial and cash policies to studythe effect of the general debt in financial sustainability and evaluate the country ability to pursue the generalexpense trend and fulfill its financial obligations for their importance and effectiveness to design andimplement and validity of the total economic policy and considered them the key standard to assess theeconomic strength and the extent of its ability to assimilate the internal and external economic shocks,related with deficit of general budget and the state assessment to achieve the financial sustainabilityconsidered of structural nature, and its seriousness appeared in Iraq, when its oil exports, the main source tofinance the budget ,subjected to sharp decline in prices under non-existence of diversity of incomes, thematter led to fluctuation of its general incomes and practicing surprised pressure on its general expenses,due to this, analyzing the sound of the financial procedures and judgment on the quality of financial decisionand policies has become of great necessary, The research focuses on knowing the rate of financial resourcescontribution( non-oil) to finance the budget and it has become clear the contribution of non- oil resourcesweakness amount (4%) and the tax rate (1%) for the period from 2005-2015 considered very low ratebecause of the backwardness of the agricultural and industrial sectors and tax decrease resulted fromadministrative and financial corruption and tax evasion and weakness of tax content besides weakness oftax system, thus the research has recommended the necessity to reform tax system and economic reform..
Android Voting System

Android Voting System is an Android app that is used to securely conduct votes and elections. As it is a digital platform, it abolished the need to vote using ballot paper or physically in person and user can easily vote using the Aadhar Card credentials. They also protect the probity of the votes by avoiding voters from voting repeatedly. Our System Make use of Firebase as a background, login, registration and maintenance purposes which makes our system more secure and reliable. Java-based programming language can be used for application development. Issues or disputes are entered into the system by the administrator. People can no longer vote and say yes or no. One voter can cast only one vote in a dispute. Each vote cast is stored on a valid dispute website. After submission of the votes the system calculates the total vote count. Thus, the app helps the authorities get the right number of votes for the voters
Gold Price Prediction Using Support Vector Regression

In this modern era, one of the businesses that continues to grow is investment. Gold has a more stable value. In Indonesia, there are futures exchange companies that offer gold investment with an online transaction system (E-Trade). The amount of demand and supply, the rate of inflation, economic conditions, and many more can affect the high and low prices of gold. Due to changes in the conditions above, the price of gold may increase, decrease, or remain constant every day. The price of gold that can go up and down causes the need for gold price predictions so that future gold trading investment prospects can be seen. In this final project, the accuracy of Support Vector Regression will be investigated to find out how accurate it is in predicting gold prices with High, Low, Open, Close, and Volume variables. Based on the calculation of the best RMSE in the study, it was found that the best RMSE was to use a Linear kernel with a C of 35 and using a Y variable dataset of 7.4615. The Support Vector Regression Algorithm can predict quite well, as evidenced by the acquisition of fairly good RMSE results. It is necessary to do a simulation of buying and selling gold based on the prediction results and comparing the advantages of the testing data and the actual data.
ANALISIS PELAKSANAAN KEBIJAKAN PEMBELAJARAN DARING PADA MASA PANDEMI COVID-19 DI SMA BAKTI SETIA NANGA PINOH KABUPATEN MELAWI

This study aims (1) Analyzing the implementation of online learning policies, (2) describes the problem of the implementation of online learning faced by teachers, aligna and parents (3) describing the teacher strategy in overcoming the problem of online learning (4) describing the use of digital facilities and media Teachers in Online Learning (5) Describe Persipan Teachers in Penencanan, Implementation Process, and Assessment / Evaluation in Online Learners. This research is located at Bhakti Loyal Nanga Pinoh High School using a qualitative research method of qualitative description approach, the data source from the principal, deputy curriculum, and subject teacher. Research instruments use, observation sheets, interview sheets and documentation. Data collection techniques through observation, interviews, documentation. Data processing steps include: data reduction, data classification, data display, data interpretation and conclusion withdrawal. The research findings show (1) the implementation of the learning policy of the Covid-19 pandemic period was carried out flexibly in two ways, namely in the network and outside the network. The implementation of learning in the network (online) uses the Google Classroom, Google Form and WhatsApp application. While luring learning is carried out with limited face-to-face and hourly. In limited face-to-face learning, the teacher explains the subject matter broadly and gives assignments to students to be done in their homes. (2) The problems faced by teachers, students and parents of students in online learning are constrained by technology, namely not all students have seriousness / gadgets and the internet. (3) The strategy carried out by the teacher is to carry out learning in two ways, namely online and luring in overcoming the problem of online learning (4) digital media used by teachers in online learning using computer programs and software such as digital videos, video games , web pages and websites, including social media; Data and databases, digital audio, such as MP3, MP4 and e-books, in addition, supporting factors in learning at the Covid-19 pandemic period are good school management, high quality teachers and disciplined students and school facilities and infrastructure adequate. (5) In carrying out teacher learning to plan online learning and luring. The plan for implementing online learning contains core competencies, competency standards and indicators of competency achievement, by referring to learning objectives and material descriptions, teachers make tasks and questions about learning evaluations to guide students in the independent learning process and measure their learning outcomes. Based on research findings, it can be concluded that the implementation of online learning policies during the Covid-19 pandemic period will be effective and supported by good school management.
THE INFLUENCE OF AUTHOR’S EDUCATIONAL SYSTEMS ON PERSONALITY FORMATION: HISTORICAL AND PEDAGOGICAL ASPECTS

The article highlights the essence of the concept of “educational system of educational institutions”, analyzes the impact of educational systems on the formation of personality in educational institutions and their potential in modern conditions.The purpose of the article is to characterize the influence of the author's educational systems on the formation of personality in the historical and pedagogical aspects.The educational system of an educational institution is considered as a set of interdependent and interconnected main components (educational goal, task, concept, subjects (students, teachers, parents), educational environment (system-forming activities, relationships, communication, interaction, management, self-government), which is a holistic socio-pedagogical structure and provides in the process of its functioning and development of formation, realization and self-realization of the individual, his life in the social, spiritual, physical, mental spheres.Emphasis is placed on the need to use the experience of creating and operating educational systems based on the principles of partnership pedagogy, humanism, the principles of subject-subject, personaldevelopmentalinteraction, communication and cooperation between participants in the educationalprocess (teachers, students, parents) and provide ample opportunities for personal development andformation. Research materials can be used in the process of formation and development of modern educationalsystems. Promising areas of research on this issue include, in particular, the study of insufficiently studieddomestic and foreign educational systems.&#x0D; Keywords: educational system; educational environment; participants of educational process; author’seducational system; influence of educational system; potential of author’s educational systems;personality; personality formation.
"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment

Many researchers and policymakers have expressed excitement about algorithmic explanations enabling more fair and responsible decision-making. However, recent experimental studies have found that explanations do not always improve human use of algorithmic advice. In this study, we shed light on how people interpret and respond to counterfactual explanations (CFEs) -- explanations that show how a model's output would change with marginal changes to its input(s) -- in the context of pretrial risk assessment instruments (PRAIs). We ran think-aloud trials with eight sitting U.S. state court judges, providing them with recommendations from a PRAI that includes CFEs. We found that the CFEs did not alter the judges' decisions. At first, judges misinterpreted the counterfactuals as real -- rather than hypothetical -- changes to defendants. Once judges understood what the counterfactuals meant, they ignored them, stating their role is only to make decisions regarding the actual defendant in question. The judges also expressed a mix of reasons for ignoring or following the advice of the PRAI without CFEs. These results add to the literature detailing the unexpected ways in which people respond to algorithms and explanations. They also highlight new challenges associated with improving human-algorithm collaborations through explanations.
MULTI-RESOLUTION REPRESENTATION USING GRAPH DATABASE

Abstract. Multi-resolution representation has always been an important and popular data source for many research and applications, such as navigation, land cover, map generation, media event forecasting, etc. With one spatial object represented by distinct geometries at different resolutions, multi-resolution representation is high in complexity. Most of the current approaches for storing and retrieving multi-resolution representation are either complicated in structure, or time consuming in traversal and query. In addition, supports on direct navigation between different representations are still intricate in most of the paradigms, especially in topological map sets. To address this problem, we propose a novel approach for storing, querying, and extracting multi-resolution representation. The development of this approach is based on Neo4j, a graph database platform that is famous for its powerful query and advanced flexibility. Benefited from the intuitiveness of the proposed database structure, direct navigation between representations of one spatial object, and between groups of representations at adjacent resolutions are both available. On top of this, collaborating with the self-designed web-based interface, queries within the proposed approach truly embraced the concept of keyword search, which lower the barrier between novice users and complicate queries. In all, the proposed system demonstrates the potential of managing multi-resolution representation data through the graph database and could be a time-saver for related processes.
FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue

Task transfer, transferring knowledge contained in related tasks, holds the promise of reducing the quantity of labeled data required to fine-tune language models. Dialogue understanding encompasses many diverse tasks, yet task transfer has not been thoroughly studied in conversational AI. This work explores conversational task transfer by introducing FETA: a benchmark for few-sample task transfer in open-domain dialogue. FETA contains two underlying sets of conversations upon which there are 10 and 7 tasks annotated, enabling the study of intra-dataset task transfer; task transfer without domain adaptation. We utilize three popular language models and three learning algorithms to analyze the transferability between 132 source-target task pairs and create a baseline for future work. We run experiments in the single- and multi-source settings and report valuable findings, e.g., most performance trends are model-specific, and span extraction and multiple-choice tasks benefit the most from task transfer. In addition to task transfer, FETA can be a valuable resource for future research into the efficiency and generalizability of pre-training datasets and model architectures, as well as for learning settings such as continual and multitask learning.
Implementasi Fuzzy Time Series Chen untuk Prediksi Jumlah Mahasiswa Baru Universitas Tidar

Higher education becomes a level of further education after pursuing a secondary education program. Tidar University is one of the public higher education institutions located in Central Java Province. Since its inception in 1979, Tidar University has only undergone a change in status to a public university in 2014. This change has an influence on the increase in the number of enthusiasts who want to study at Tidar University. In addition, there were several new study programs at Tidar University in different years which also led to an increase in the number of new students of Tidar University. However, the Covid-19 pandemic also brought an influence that led to a drastic decrease in the number of enthusiasts at Tidar University. This study tried to implement chen's fuzzy time series to predict the number of enthusiasts in the first 10 study programs of Tidar University. In this prediction process, the number of intervals used affects the forecasting results. To determine the number of intervals, the Sturges formula is used. The prediction results showed the smallest MAPE value of 5.7551% in the agrotechnology study program and the largest MAPE at 28.3936% in the accounting D3 study program
Creative AI and the Experience of Stories: Creative AI and Responses to Narratives

For many decades, digital technologies have assisted humans in producing artworks and entertainment products.The role of digital technologies in these fields, however, is not limited to serving as a tool to implement human ideas.Artificial intelligence (AI) could lead to technology becoming a creator itself.Our focus here is on stories created by AI.We assume that the information that a fictional story was created by AI leads to a distancing response.This psychological distancing should go along with feelings of eeriness and should prevent recipients from being transported into the story world and from sharing the story with others.We conducted two experiments and examined user responses to fictional stories supposedly written by AI (versus a human author).Results of Experiment 1 (N = 321) suggest that the information that a short story was written by an AI has no significant effect on eeriness or the willingness to share.However, it reduces the recipients' experience of being transported into the story world.Experiment 2 (N = 489) replicates this finding within a 2 (author: AI vs. human) x 2 (genre: contemporary fiction vs. science fiction) design.Again, AI as an author reduced transportation.
A Real Time Super Resolution Accelerator with Tilted Layer Fusion

Deep learning based superresolution achieves high-quality results, but its heavy computational workload, large buffer, and high external memory bandwidth inhibit its usage in mobile devices. To solve the above issues, this paper proposes a real-time hardware accelerator with the tilted layer fusion method that reduces the external DRAM bandwidth by 92\% and just needs 102KB on-chip memory. The design implemented with a 40nm CMOS process achieves 1920x1080@60fps throughput with 544.3K gate count when running at 600MHz; it has higher throughput and lower area cost than previous designs.
Implementation of the Professionally-Oriented Foreign Language Competence in Terms of Integrative Approach for Training Future Engineers

The article deals with the actual issues of forming professionally-oriented foreign language competence concerning the future engineers’ training. The article testifies the necessity of rendering future engineers with professionally-oriented foreign language training based on new engineering and technological approaches. The challenges of interdisciplinary studies of any area of economy cause enhanced intensive international collaboration and intercultural cooperation. It implies the improvement of professionally-oriented foreign language competence demand for the next generation of engineers and middle-line staffsince it is essential for interdisciplinary and international team work training. Considering the experimental results, it has been confirmed that professional foreign language competence is effectively developed within “Intensive integrative course of foreign language”, content and structure of which are based on an integrative approach and a set of suggested organisational principles. The article summarises the results of the direct observation and interviews.
Awareness and impacts on women helpline in India

Women Helpline (WHL) established in India to provide integrated support and assistance to women affected by violence, both in private and public spaces under one roof. Women Helpline is intended to provide 24 hours immediate and emergency response to women affected by violence. The questionnaires were distributed online using a Google form, after which they were processed and analyzed. This paper examines about the effectiveness of women helpline numbers in India.
Mitigating Gender Stereotypes in Hindi and Marathi

As the use of natural language processing increases in our day-to-day life, the need to address gender bias inherent in these systems also amplifies. This is because the inherent bias interferes with the semantic structure of the output of these systems while performing tasks like machine translation. While research is being done in English to quantify and mitigate bias, debiasing methods in Indic Languages are either relatively nascent or absent for some Indic languages altogether. Most Indic languages are gendered, i.e., each noun is assigned a gender according to each language's grammar rules. As a consequence, evaluation differs from what is done in English. This paper evaluates the gender stereotypes in Hindi and Marathi languages. The methodologies will differ from the ones in the English language because there are masculine and feminine counterparts in the case of some words. We create a dataset of neutral and gendered occupation words, emotion words and measure bias with the help of Embedding Coherence Test (ECT) and Relative Norm Distance (RND). We also attempt to mitigate this bias from the embeddings. Experiments show that our proposed debiasing techniques reduce gender bias in these languages.
Probability of generation by random permutations of given cycle type

Suppose $π$ and $π'$ are two random elements of $S_n$ with constrained cycle types such that $π$ has $x n^{1/2}$ fixed points and $yn/2$ two-cycles, and likewise $π'$ has $x' n^{1/2}$ fixed points and $y'n/2$ two-cycles. We show that the events that $G = \langle π, π' \rangle$ is transitive and $G \geq A_n$ both have probability approximately \[(1 - yy')^{1/2} \exp\left(- \frac{xx' + \frac12 x^2 y' + \frac12 {x'}^2 y}{1 - yy'}\right),\] provided $(x, x')$ is not close to $(0, \infty)$ or $(\infty, 0)$. This formula is derived from some preliminary results in a recent paper (arXiv:1904.12180) of the authors. As an application, we show that two uniformly random elements of uniformly random conjugacy classes of $S_n$ generate the group with probability about 51%.
Transformer Scale Gate for Semantic Segmentation

Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation. Existing transformer-based segmentation models combine features across scales without any selection, where features on sub-optimal scales may degrade segmentation outcomes. Leveraging from the inherent properties of Vision Transformers, we propose a simple yet effective module, Transformer Scale Gate (TSG), to optimally combine multi-scale features.TSG exploits cues in self and cross attentions in Vision Transformers for the scale selection. TSG is a highly flexible plug-and-play module, and can easily be incorporated with any encoder-decoder-based hierarchical vision Transformer architecture. Extensive experiments on the Pascal Context and ADE20K datasets demonstrate that our feature selection strategy achieves consistent gains.
Peningkatan Keterampilan Menyusun Teks Deskripsi Melalui Pembelajaran dengan Media Mind Map pada Siswa Kelas VII E SMP 2 Kumai

This CAR is a classroom action research that examines the improvement of the ability to write descriptive texts in class VII E SMP 2 Kumai students. The purpose of this study was to determine the improvement of compiling descriptive text through learning using appropriate mind map media for Indonesian descriptive text material based on the 2013 curriculum in Keels VII E of SMP 2 Kumai students. The classroom action research process is carried out in two cycles, each of which includes four main stages, namely planning, action, observation, and reflection. The instruments used are test and non-test. The test instrument is to get a score for the ability to write a descriptive text. The non-test instrument used by the researcher was a journal, an observation guide to obtaining data about students' abilities in writing descriptive texts. The results showed that the use of mind map media can improve students' writing descriptive text skills. The results of the analysis above show that the action hypothesis in this study is in accordance with the expectation that the use of mind map media can improve the ability to write a descriptive text. The results of this study can provide benefits for schools, teachers in the field of study, and students, especially those related to improving the ability to write descriptive texts.
Low-illumination underwater image enhancement based on Retinex and Dark Channel priori

For the problem of low-illumination underwater images caused by the use of filters, we provide an algorithm for image enhancement based on multiscale Retinex and Dark channel priori. First, we use the multi-scale Retinex algorithm for color correction. Second, we use a modified Dark channel priori algorithm for the defogging process. We acquired some underwater images and compared them with classical image processing algorithms, and the results show that our algorithm improves image brightness and contrast.