Reviewerly/exHarmony huggingface dataset:
Do We Still Need Grades in the Modern Educational System

Have you ever detected concerning the trendy training gadget? If you are doing not hold close what a modern-day education system is then we generally tend to are attending to inform you every bit regarding it. After we call the trendy schooling; therefore a selected device is seemingly advanced in reality to identify that what college students have learnt! There rectangular degree many alternative countries a company square measure taking importance over the fashionable education. Slowly and little by little those international locations are becoming and implementing education system and following this approach positioned planning! There conjointly a few signs and symptoms that show that the stylish schooling device if you are getting to modification the planet. But the real reality is this training device is grade primarily based.
Manifold-Inspired Single Image Interpolation

Manifold models consider natural-image patches to be on a low-dimensional manifold embedded in a high dimensional state space and each patch and its similar patches to approximately lie on a linear affine subspace. Manifold models are closely related to semi-local similarity, a well-known property of natural images, referring to that for most natural-image patches, several similar patches can be found in its spatial neighborhood. Many approaches to single image interpolation use manifold models to exploit semi-local similarity by two mutually exclusive parts: i) searching each target patch's similar patches and ii) operating on the searched similar patches, the target patch and the measured input pixels to estimate the target patch. Unfortunately, aliasing in the input image makes it challenging for both parts. A very few works explicitly deal with those challenges and only ad-hoc solutions are proposed. To overcome the challenge in the first part, we propose a carefully-designed adaptive technique to remove aliasing in severely aliased regions, which cannot be removed from traditional techniques. This technique enables reliable identification of similar patches even in the presence of strong aliasing. To overcome the challenge in the second part, we propose to use the aliasing-removed image to guide the initialization of the interpolated image and develop a progressive scheme to refine the interpolated image based on manifold models. Experimental results demonstrate that our approach reconstructs edges with both smoothness along contours and sharpness across profiles, and achieves an average Peak Signal-to-Noise Ratio (PSNR) significantly higher than existing model-based approaches.
Dialogue Summarization with Supporting Utterance Flow Modeling and Fact Regularization

Dialogue summarization aims to generate a summary that indicates the key points of a given dialogue. In this work, we propose an end-to-end neural model for dialogue summarization with two novel modules, namely, the \emph{supporting utterance flow modeling module} and the \emph{fact regularization module}. The supporting utterance flow modeling helps to generate a coherent summary by smoothly shifting the focus from the former utterances to the later ones. The fact regularization encourages the generated summary to be factually consistent with the ground-truth summary during model training, which helps to improve the factual correctness of the generated summary in inference time. Furthermore, we also introduce a new benchmark dataset for dialogue summarization. Extensive experiments on both existing and newly-introduced datasets demonstrate the effectiveness of our model.
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Efektivitas Penggunaan Media Kartu Numerik pada Siswa Jenjang Prasekolah

Abstrak&#x0D; Pembelajaran di jenjang prasekolah lebih banyak bermain sambil belajar. Pembelajaran matematika juga dapat diterima anak dalam dunia penddikan pra sekolah, yaitu dengan cara mengenal numerik 1-10. Hal demikian dilakukan dengan menggunakan media kartu numerik secara klasikal. Jenis penelitian ini adalah deskriptif kualitatif dengan subjek penelitian anak-anak pra sekolah dhiva school dengan jumlah 18 anak. Dalam penelitian ini diketahui bahwa siswa pra sekolah mampu mengenal numerik, mampu menulis dan mampu mengurutkan numerik 1-10. efektifitas media kartu numerik, dengan menggunakan 4 indikator hasilnya untuk indikator kemauan belajar siswa kategori sangat baik, dengan rata-rata 84,4. Untuk indikator keterampilan siswa juga kriteria sangat baik, dengan skor rata-rata 83,27. Indikator berikutnya mengenal angka 1-10 dengan benar dan tepat juga memproleh kriteria sangat baik, dengan rata-rata 83. Indikator yang terakhir diperoleh skor rata-rata 80,94 jika dibulatkan menjadi 81, jadi untuk indikator ini memperoleh kriteria sangat baik.&#x0D; &#x0D; Abstract&#x0D; Their experiences in preschool more level playing while learning. Math lessons are also a possible child in pre-world education, school namely through numerical know 1-10. It thereby conducted using the card classical. The purpose of this study was to describe the effectiveness of numeric card media for pre-school level students in terms of attitudes and abilities in understanding the material.Numerically kind of research this is the qualitative descriptive subject of study children preschool Dhiva school of 18. Children in this research are that students are, numerical know schools can pre and capable of writing. 1-10 numeric rank The effectiveness of media, numerical card using the 4 indicators for the student learning a very good, category with an average 84,4. To the student skills also excellent, criteria with the average score 83,27. Know the following indicators 1-10 correctly and precise criteria, get very well with an average of 83. The last average score obtained 80,94 if rounded into 81, so this question received excellent. So that the introduction of numeric card media for pre-school students is very effective in increasing the ability of students to learn to count (numbers).
Hand Crafted Plates / Muhammad Arif Mohd Mukhidin

• Business conceptsClay Craft one of the company will come out the product made by clay. The designers in this company will create the new design for the plates, bowls, teapot, cup and also bakery stuff. Our products are very recommended to everyone because it is very long-lasting product. Even the price are bit expensive and very worth it with the products. Our products be expensive because the design are hand craft and the material used very high-end.• Products or services being offeredThe products can get at the Clay Craft store in Kuala Lumpur. Our products also can get from the website and our company will deliver the order home to home. The promotion sale depends on festival celebration, new year, Merdeka sale and etc.• Market potential/ Target marketClay craft products made by hand craft and very attractive design. The target market for working people men and women age around 25 years old and above. The customers leave in Kuala Lumpur area. The food and beverage industry such as the restaurant, cafe, hotel and food court.• Competitive advantageClay Craft products made from clay. The products very long-lasting. The surface are non-stick and easy to wash. The design are hand crafted and look very attractive. The products heat resistant available for steamer, microwave, oven and etc• The profitability Sales are an important factor in determining profitability. The return on sales ratio measures profits after taxes based upon the current year's sales. Price setting is a key factor in determining profit. Careful analysis is necessary in determining the correct pricing strategy for a company. For a company to become profitable, income must exceed expenses. Expenses can be defined as the cost of resources used in the activities of a business.• Management teamClay Craft company have a team management as a back bone built the successful company. The team management included the designer, employers, promoter and finance manager. They are part of the Clay Craft team to built the successful company. Every team have their own work, as long as they give the 100% commitment for this company.
The Influence of Organizational Silence on Job Burnout: A Practical Study on Shipping Companies in Jordan

The current research aims to identify the influence of organizational silence on job burnout in the shipping companies in Jordan. Therefore, the research population consists of (570) managers, their assistants, and heads of departments in the shipping companies in Jordan .whereas, the research sample consists of (230) employees. The Questionnaires were collected from 207respondents and formed 90% as a response rate. In addition, the current research used a simple random sample to collect data from respondents. Furthermore, the current research used the Partial Least Square (PLS) technique to test the research hypotheses. The results of the current research reached that the dimensions of organizational silence have a positive impact on job burnout. While the most important recommendation that the shipping companies should adopt the policies and cultures to reduce the job burnout phenomenon by encouraging the employees to speak without any limitations.
The Application of Output Oriented Approach in College English Writing

From the beginning of primary school, students began to learn English letters, junior high school began to understand and learn English grammar and English words systematically, to high school, under the pressure of the college entrance examination, students try their best to memorize 3500 words that they have been looking forward to for a long time, but no matter in which grade, writing has been accompanied by students’ English learning. However, according to the results of college students’ English competitions in recent years, there are many problems in college students’ English writing, such as lack of vocabulary, grammatical errors, scribble and so on. These problems also play an alarm role for college teachers and students, so that they constantly start to think, to find the problems, and try to find better solutions in a short time.
Leader’s Social Relationship and the Policy of Dividend Distribution: Study of Tunisian Non-Financial Listed Companies.

In an attempt to examine the influence of the leader's social relation on dividend distribution policy in a context of listed non-financial Tunisian firms, a multiple linear model is constructed in a period stretching between 2001-2014.Thus, our empirical study is based on the estimation of a single model by following the multiple linear regression technique (Panel).Our results of the estimate of our model show a positive effect between the Leader's social relationship and the policy of dividend distribution in a context of the Tunisian non-financial listed companies.
Why I'm not Answering: An Abstention-Based Approach to Classify Cancer Pathology Reports

Safe deployment of deep learning systems in critical real world applicationsrequires models to make few mistakes, and only under predictable circumstances.Development of such a model is not yet possible, in general. In this work, weaddress this problem with an abstaining classifier tuned to have $>$95%accuracy, and identify the determinants of abstention with LIME (the LocalInterpretable Model-agnostic Explanations method). Essentially, we are trainingour model to learn the attributes of pathology reports that are likely to leadto incorrect classifications, albeit at the cost of reduced sensitivity. Wedemonstrate our method in a multitask setting to classify cancer pathologyreports from the NCI SEER cancer registries on six tasks of greatestimportance. For these tasks, we reduce the classification error rate by factorsof 2-5 by abstaining on 25-45% of the reports. For the specific case of cancersite, we are able to identify metastasis and reports involving lymph nodes asresponsible for many of the classification mistakes, and that the extent andtypes of mistakes vary systematically with cancer site (eg. breast, lung, andprostate). When combining across three of the tasks, our model classifies 50%of the reports with an accuracy greater than 95% for three of the six tasks andgreater than 85% for all six tasks on the retained samples. By using thisinformation, we expect to define work flows that incorporate machine learningonly in the areas where it is sufficiently robust and accurate, saving humanattention to areas where it is required.
Toward Human-Friendly ASR Systems: Recovering Capitalization and Punctuation for Vietnamese Text

Speech recognition is a technique that recognizes words and sentences in audio form and converts them into text sentences. Currently, with the advancement of deep learning technologies, speech recognition has achieved very satisfactory results close to human abilities. However, there are still limitations in identification results such as lack of punctuation, capitalization, and standardized numerical data. Vietnamese also contains local words, homonyms, etc, which make it difficult to read and understand the identification results for users as well as to perform the next tasks in Natural Language Processing (NLP). In this paper, we propose to combine the transformer decoder with conditional random field (CRF) to restore punctuation and capitalization for the Vietnamese automatic speech recognition (ASR) output. By chunking input sentences and merging output sequences, it is possible to handle longer strings with greater accuracy. Experiments show that the method proposed in the Vietnamese post-speech recognition dataset delivers the best results.
Deep Pairwise Learning To Rank For Search Autocomplete

Autocomplete (a.k.a "Query Auto-Completion", "AC") suggests full queries based on a prefix typed by customer. Autocomplete has been a core feature of commercial search engine. In this paper, we propose a novel context-aware neural network based pairwise ranker (DeepPLTR) to improve AC ranking, DeepPLTR leverages contextual and behavioral features to rank queries by minimizing a pairwise loss, based on a fully-connected neural network structure. Compared to LambdaMART ranker, DeepPLTR shows +3.90% MeanReciprocalRank (MRR) lift in offline evaluation, and yielded +0.06% (p < 0.1) Gross Merchandise Value (GMV) lift in an Amazon's online A/B experiment.
GEOSTATISTICAL MODELLING FOR SULFUR ELEMENT IN GHORABI IRON ORE MINE AREA, BAHARIYA OASIS, EGYPT

Sulfuris a concern in Ghorabi iron oreand it is an unwantedcomponent when the ore is chargedinto a blast furnace. The goal of this paper aims to track thesulfur contentin Ghorabi iron ore by using geostatistical modelling. Geologically, the ore is splitinto fourdistinct zones. The experimental variograms were created tohighlight the spatial variability of sulfur element within the deposit. The experimental variogramswere fitted with Gaussian, linear and exponentialvariogram models. Finally,the appropriate fitted models were utilized to create a distribution mapsfor the four separated zones using the ordinary kriging and indicator kriging in 0.7% cut-offs. يمثل الکبريت مشکلة في خام حديد منطقة غرابي ويعتبر مکونا غير مرغوب فيه عند شحن الخام للفرن العالي. تهدفهذه الورقة إلى رصد تباين الکبريت الموجود في خام حديد منطقة غرابي باستخدام النمذجة الجيوإحصائية. تم تقسيمالخام جيولوجي ا إلى أربع مناطق منفصلة. لإظهار التباين المکاني لعنصر الکبريت ، تم إنشاء المتغيرات التجريبيةداخل الرواسب. تم ترکيب نماذج التباين )جاوسيان – الخطية – الأسية( للمتغيرات التجريبية. أخيرا ، تم استخدا م النماذج المناسبة لإنشاء خرائط توزيع لعنصر الکبريت باستخدام الکريجنج العادي و الکريجنج المؤشر لحد قطع معين للمناطق الأربعة المختلفة.
한국어 학습자의 그릿과 자기조절효능감이 한국어 성적에 미치는 영향 -회귀분석과 매개효과를 중심으로-

The purpose of this study is to examine how Korean language learners’ grit and self-regulatory efficacy influence their grades. To address the goal, this researcher selected two groups of foreign undergraduates (105) taking Korean classes and measured their grit and self-regulatory efficacy. After conducting statistic analysis, this author gained following results. First of all, regarding predictability about each group’s variable, grades, in group A that has learned Korean for a long period, grit and self-regulatory efficacy predict grades; however, in group B that has learned Korean for a short period, no variables predict grades. Also, despite the fact that grit is a task-general factor, it is found to influence Korean grades, a task-specific area, significantly, Lastly, in the process of grit influencing Korean grades, self-regulatory efficacy mediates grit completely, which verifies grit’s transferability. This study is significant in that it introduces the concept of grit that has not been dealt with in Korean language education and has multi-dimensionally verified correlation between the affective area and grades which has not been studied sufficiently in Korean language education. (Busan University of Foreign Studies, Changwon National University, Busan University of Foreign Studies)
An EM Framework for Online Incremental Learning of Semantic Segmentation

Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting. However, it remains challenging to acquire novel classes in an online fashion for the segmentation task, mainly due to its continuously-evolving semantic label space, partial pixelwise ground-truth annotations, and constrained data availability. To ad- dress this, we propose an incremental learning strategy that can fast adapt deep segmentation models without catastrophic forgetting, using a streaming input data with pixel annotations on the novel classes only. To this end, we develop a uni ed learning strategy based on the Expectation-Maximization (EM) framework, which integrates an iterative relabeling strategy that lls in the missing labels and a rehearsal-based incremental learning step that balances the stability-plasticity of the model. Moreover, our EM algorithm adopts an adaptive sampling method to select informative train- ing data and a class-balancing training strategy in the incremental model updates, both improving the e cacy of model learning. We validate our approach on the PASCAL VOC 2012 and ADE20K datasets, and the results demonstrate its superior performance over the existing incremental methods.
THE DESIGN STUDIO AS A NETWORK – APPLICATION OF CONNECTIVISM IN THE PLANNING OF AN ONLINE LEARNING SPACE

The design studio is the core element in the design curriculum where students gain key knowledge and skills.When the traditional classroom course had to be transferred to an online modality enforced by covid-19 pandemics, re-conceptualization of the structure and contents was required in order to ensure the quality of the teaching and students' satisfaction.Based on the premise that the contents should not be simply adapted to an online version, but an entirely new learning experience should be created, the redesign of the class was inspired by the principles of connectivism (Siemens, 2005).Connectivism as an alternative learning theory recognizes the societal shifts and the inevitable impact of technology on the learning processes.This new framework for understanding learning, states that knowledge is derived externally of the individual through a process of connecting nodes and patterns recognition.These abilities are considered especially important to prepare design students for the challenges of the profession within the context of the fourth industrial revolution.The paper explores the potential of connectivism as a holistic approach to the planning of the contents of an online design studio.It describes the process of designing the course structure and discusses the challenges encountered in the creation of a connectivist learning environment.The advantages of the networked design studio were verified in a survey on the perceptions of the students in regard to their satisfaction and the effectiveness of their knowledge acquisition.
Urdu & Hindi Poetry Generation using Neural Networks

One of the major problems writers and poets face is the writer's block. It is a condition in which an author loses the ability to produce new work or experiences a creative slowdown. The problem is more difficult in the context of poetry than prose, as in the latter case authors need not be very concise while expressing their ideas, also the various aspects such as rhyme, poetic meters are not relevant for prose. One of the most effective ways to overcome this writing block for poets can be, to have a prompt system, which would help their imagination and open their minds for new ideas. A prompt system can possibly generate one liner, two liner or full ghazals. The purpose of this work is to give an ode to the Urdu, Hindi poets, and helping them start their next line of poetry, a couplet or a complete ghazal considering various factors like rhymes, refrain, and meters. The result will help aspiring poets to get new ideas and help them overcome writer's block by auto-generating pieces of poetry using Deep Learning techniques. A concern with creative works like this, especially in the literary context, is to ensure that the output is not plagiarized. This work also addresses the concern and makes sure that the resulting odes are not exact match with input data using parameters like temperature and manual plagiarism check against input corpus. To the best of our knowledge, although the automatic text generation problem has been studied quite extensively in the literature, the specific problem of Urdu, Hindi poetry generation has not been explored much. Apart from developing system to auto-generate Urdu, Hindi poetry, another key contribution of our work is to create a cleaned and preprocessed corpus of Urdu, Hindi poetry (derived from authentic resources) and making it freely available for researchers in the area.
Fairer Chess: A Reversal of Two Opening Moves in Chess Creates Balance Between White and Black.

Unlike tic-tac-toe or checkers, in which optimal play leads to a draw, it is not known whether optimal play in chess ends in a win for White, a win for Black, or a draw. But after White moves first in chess, if Black has a double move followed by a double move of White and then alternating play, play is more balanced because White does not always tie or lead in moves. Symbolically, Balanced Alternation gives the following move sequence: After White's (W) initial move, first Black (B) and then White each have two moves in a row (BBWW), followed by the alternating sequence, beginning with W, which altogether can be written as WB/BW/WB/WB/WB... (the slashes separate alternating pairs of moves). Except for reversal of the 3rd and 4th moves from WB to BW, this is the standard chess sequence. Because Balanced Alternation lies between the standard sequence, which favors White, and a comparable sequence that favors Black, it is highly likely to produce a draw with optimal play, rendering chess fairer. This conclusion is supported by a computer analysis of chess openings and how they would play out under Balanced Alternation.