Reviewerly/exHarmony huggingface dataset:
Overview and Insights from the SciVer Shared Task on Scientific Claim Verification

We present an overview of the SciVer shared task, presented at the 2nd Scholarly Document Processing (SDP) workshop at NAACL 2021. In this shared task, systems were provided a scientific claim and a corpus of research abstracts, and asked to identify which articles SUPPORT or REFUTE the claim as well as provide evidentiary sentences justifying those labels. 11 teams made a total of 14 submissions to the shared task leaderboard, leading to an improvement of more than +23 F1 on the primary task evaluation metric. In addition to surveying the participating systems, we provide several insights into modeling approaches to support continued progress and future research on the important and challenging task of scientific claim verification.
Explore and Control with Adversarial Surprise

Reinforcement learning (RL) provides a framework for learning goal-directed policies given user-specified rewards. However, since designing rewards often requires substantial engineering effort, we are interested in the problem of learning without rewards, where agents must discover useful behaviors in the absence of task-specific incentives. Intrinsic motivation is a family of unsupervised RL techniques which develop general objectives for an RL agent to optimize that lead to better exploration or the discovery of skills. In this paper, we propose a new unsupervised RL technique based on an adversarial game which pits two policies against each other to compete over the amount of surprise an RL agent experiences. The policies each take turns controlling the agent. The Explore policy maximizes entropy, putting the agent into surprising or unfamiliar situations. Then, the Control policy takes over and seeks to recover from those situations by minimizing entropy. The game harnesses the power of multi-agent competition to drive the agent to seek out increasingly surprising parts of the environment while learning to gain mastery over them. We show empirically that our method leads to the emergence of complex skills by exhibiting clear phase transitions. Furthermore, we show both theoretically (via a latent state space coverage argument) and empirically that our method has the potential to be applied to the exploration of stochastic, partially-observed environments. We show that Adversarial Surprise learns more complex behaviors, and explores more effectively than competitive baselines, outperforming intrinsic motivation methods based on active inference, novelty-seeking (Random Network Distillation (RND)), and multi-agent unsupervised RL (Asymmetric Self-Play (ASP)) in MiniGrid, Atari and VizDoom environments.
Tourist Sentiment Mining Based on Deep Learning

Mining the sentiment of the user on the internet via the context plays a significant role in uncovering the human emotion and in determining the exactness of the underlying emotion in the context. An increasingly enormous number of user-generated content (UGC) in social media and online travel platforms lead to development of data-driven sentiment analysis (SA), and most extant SA in the domain of tourism is conducted using document-based SA (DBSA). However, DBSA cannot be used to examine what specific aspects need to be improved or disclose the unknown dimensions that affect the overall sentiment like aspect-based SA (ABSA). ABSA requires accurate identification of the aspects and sentiment orientation in the UGC. In this book chapter, we illustrate the contribution of data mining based on deep learning in sentiment and emotion detection.
Perceptually Validated Precise Local Editing for Facial Action Units with StyleGAN

The ability to edit facial expressions has a wide range of applications in computer graphics. The ideal facial expression editing algorithm needs to satisfy two important criteria. First, it should allow precise and targeted editing of individual facial actions. Second, it should generate high fidelity outputs without artifacts. We build a solution based on StyleGAN, which has been used extensively for semantic manipulation of faces. As we do so, we add to our understanding of how various semantic attributes are encoded in StyleGAN. In particular, we show that a naive strategy to perform editing in the latent space results in undesired coupling between certain action units, even if they are conceptually distinct. For example, although brow lowerer and lip tightener are distinct action units, they appear correlated in the training data. Hence, StyleGAN has difficulty in disentangling them. We allow disentangled editing of such action units by computing detached regions of influence for each action unit, and restrict editing to these regions. We validate the effectiveness of our local editing method through perception experiments conducted with 23 subjects. The results show that our method provides higher control over local editing and produces images with superior fidelity compared to the state-of-the-art methods.
Implementation of Cloud Security by Identity Based Encryption

This paper presents the concept of encrypting the Data from the client to the client. But using some Key generator which sets the password for sending the information. In this concept, we have two types of passwords those are Private Key and Cloud outsourced key. The password will be sent to the client through email by using unique human identity, example Special Name, user id, IP address, etc. This Paper Deals with the client, private key generator and cloud. First, the user has to register by giving their basic details for having user name and password, have to enter their personal details, including contact number, email id, country, etc. When the user Id has created, they have to log through the client login. If they have an account they can be logged in if they are not having an account, they have to register. If any loss of password can reset the password by providing the email Id. This Paper can provide the Security of the user Data. In this Paper we are using cloud storage system.
Individual vs. Joint Perception: a Pragmatic Model of Pointing as Smithian Helping

Author(s): Jiang, Kaiwen; Stacy, Stephanie; Chan, Adelpha; Wei, Chuyu; Rossano, Federico; Zhu, Yixin; Gao, Tao | Abstract: The simple gesture of pointing can greatly augment one’s ability to comprehend states of the world based on observations. It triggers additional inferences relevant to one’s task at hand.We model an agent’s update to its belief of the world based on individual observations using a partially observable Markov decision process (POMDP), a mainstream artificial intelligence (AI) model of how to act rationally according to beliefs formed through observation. On top of that, we model pointing as a communicative act between agents who have a mutual understanding that the pointed observation must be relevant and interpretable. Our model measures “relevance” by defining a Smithian Value of Information (SVI) as the utility improvement of the POMDP agent before and after receiving the pointing. We model that agents calculate SVI by using the cognitive theory of Smithian helping as a principle of coordinating separate beliefs for action prediction and action evaluation. We then import SVI into rational speech act (RSA) as the utility function of an utterance. These lead us to a pragmatic model of pointing allowing for contextually flexible interpretations. We demonstrate the power of our Smithian pointing model by extending the Wumpus world, a classic AI task where a hunter hunts a monster with only partial observability of the world. We add another agent as a guide who can only help by marking an observation already perceived by the hunter with a pointing or not, without providing new observations or offering any instrumental help. Our results show that this severely limited and overloaded communication nevertheless significantly improves the hunters’ performance. The advantage of pointing is indeed due to a computation of relevance based on Smithian helping, as it disappears completely when the task is too difficult or too easy for the guide to help.
Machine Learning Assisted Oncotype Dx Recurrence Risk Classification Forecast System for Breast Cancer Based on 111,635 Patients Covering 11 Years

Background: TAILORx data confirm that using Oncotype DX (ODX) to assess the risk of early-stage breast cancer recurrence can spare women unnecessary chemotherapy. However, high up-front costs (list price, $4175) could dissuade usage. Also, from a technical perspective, this test cannot be widely used in developing countries, especially in relatively poor areas.Methods: By analyzing the Surveillance, Epidemiology, and End-Results database, multinomial ordinal logistic regression, random forest, gradient boosting decision tree, extreme gradient boosting, and multi-layer perceptron were adopted to develop an assistant forecast system for recurrence risk—low to intermediate (RS=2–25) or high (RS=26–100)—based on individuals’ sociodemographic and clinicopathological information. We validated the system using an independent dataset (training-test split of the original dataset) as validation.Results: We identified 111,635 patients with breast cancer: 86,617 patients (77.59%) were aged 50 years or younger; 23,514 patients (21.1%) had low risk scores, 71,439 patients (64.0%) had intermediate risk scores, and 16,682 patients (14.9%) had high risk scores. Variables closely associated (all P<0.05) with RS included age, sex, race, primary tumor site, histopathological grade, tumor size, pathology, and progesterone receptor status. In validation, for the multi-layer perceptron model, overall accuracy was 86.1% (sensitivity=0.69, specificity=0.87, and area under the curve=0.80).Conclusions Our assistant forecast system, based on sociodemographic and clinicopathological data, provides an alternative tool to estimate patients’ breast cancer recurrence risk.Funding: This work was supported by the Natural Science Foundation of China (No. 81872160), the Natural Science Foundation of China (No. 82072940), the China National Key R&D (or Research and Development) Program (No. 2020AAA0105000 and 2020AAA0105004), the Beijing Municipal Natural Science Foundation (Key Project) (No. 7191009), the Beijing Municipal Natural Science Foundation (No. 7204293), the Special Research Fund for Central Universities, Peking Union Medical College (No. 3332019053), the Beijing Hope Run Special Fund of Cancer Foundation of China (No. LC2019B03), the Beijing Hope Run Special Fund of Cancer Foundation of China (No. LC2019L07), the Beijing Hope Run Special Fund of Cancer Foundation of China (No. LC2020L01), the Golden Bridge Project Seed Fund of Beijing Association for Science and Technology (No. ZZ20004), and the National Key R&D Program of China (No. 2018YFC1315000 and No. 2018YFC1315003).Declaration of Interest: None to declare. Ethical Approval: The analysis followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College institutional review board approved this study as exempt.
MT-ORL: Multi-Task Occlusion Relationship Learning

Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image. We observe two key issues in existing works: firstly, lack of an architecture which can exploit the limited amount of coupling in the decoder stage between the two subtasks, namely occlusion boundary extraction and occlusion orientation prediction, and secondly, improper representation of occlusion orientation. In this paper, we propose a novel architecture called Occlusion-shared and Path-separated Network (OPNet), which solves the first issue by exploiting rich occlusion cues in shared high-level features and structured spatial information in task-specific low-level features. We then design a simple but effective orthogonal occlusion representation (OOR) to tackle the second issue. Our method surpasses the state-of-the-art methods by 6.1%/8.3% Boundary-AP and 6.5%/10% Orientation-AP on standard PIOD/BSDS ownership datasets. Code is available at this https URL.
Using Scrambled Pictures Media to Improve Students’ Writing Skill in Narrative Text

The present Classroom Action Research (CAR) initiated when the researcher found the students at the eighth-grade students of SMP Juara Pekanbaru had low writing skills. This problem could be identified from their base scores below the standard minimum score (GPA). It was 64,06. The purpose of this research was to try to develop the students’ writing skill and to know the factors that influenced the changing of students’ writing skill. This research was conducted from March up to May 2019 in two cycles consisted of ten meetings. The participants of this research were 27 students of the Andalusia class. In improving the students’ writing skill, a narrative text was used as a learning media. The instruments used in this research were writing test, interview, field note and also observation list to help understand the phenomenon. This research showed that the students got the score 72,22 in cycle 1 dan 84,49 in cycle 2, especially on organization with an increase of 4,47. It could be seen that scrambled pictures media could improve the students’ writing skill.
MODERN THEORETICAL AND PRACTICAL ASPECTS OF DISTANCE LEARNING IN INSTITUTIONS OF PROFESSIONAL PRE-HIGHER EDUCATION

The current modern requirements are distance education. Distance education is an opportunity to study and receive the necessary knowledge remotely from the school at any convenient time. Regardless of how distance education is implemented, different countries have their own peculiarities of its use at the level of secondary and higher education. Such training programs are especially useful for many people who, due to financial, physical or geographical circumstances, do not have the opportunity to receive traditional education. Thus, distance learning provides an opportunity to gain equal access to quality education. Other names for distance learning include “open education”, “e‑learning”, “virtual learning” and so on. The Regulations on Distance Education and the Concept of Distance Education Development in Ukraine regulate the rights and responsibilities of participants in the educational process. Distance learning has a number of undeniable advantages. In particular, the student can study at a time convenient to him, the usual environment and at a relatively autonomous pace. The statute has the meaning of the understanding “distance education”; problems, the formation of the methods of interaction to provide education with victories from the hour of remote access. There are platforms designed to enable Ukrainian students, regardless of location, to obtain a quality Ukrainian education. An analysis has been carried out and the main re-runs of distance courses have been determined. The authors have provided information about the practical training management system for electronic science (learning management system, LMS) Moodle at the initial process of the Kherson Polytechnic Faculty College of the Odessa National Polytechnic University. There are also recommendations for advancing the effectiveness of remote sensing, and special respect is given to diagnostics and knowledge of education.
Alternative non-Gaussianity measures for quantum states based on quantum fidelity

We propose three alternative measures for non-Gaussianity of quantum states: sine distance, Bures angle, and Bures distance, which are based on quantum fidelity introduced by Wang [ Phys. Lett. A 373 58 (2008)]. Using them, we evaluate the non-Gaussianity of some relevant single-mode and two-mode non-Gaussian states and find a good consistency of the three examined measures. In addition, we show that such metrics can exactly quantify the degree of Gaussianity of even Schrödinger-cat-like states of small amplitudes that can not be measured by other known non-Gaussianity measures such as the Hilbert–Schmidt metric and the relative entropy metric. We make a comparative study between all existing non-Gaussianity measures according to the metric axioms and point out that the sine distance is the best candidate among them.
Interactive visual facets to support fluid exploratory search

Abstract Exploratory search starts with ill-defined goals and involves browsing, learning, and formulating new targets for search. To fluidly support such dynamic search behaviours, we focus on devising interactive visual facets (IVF) , visualising information facets to support user comprehension and control of the information space. We reviewed existing faceted search interfaces and derived two design requirements (DR) that have not been fully addressed to support fluid interactions in exploratory search. We then exemplified the requirements through devising an IVF tool, which coordinates a linear and a categorical facet representing the distribution and summarisation of items, respectively, and providing context for faceted exploration (DR1). To support rapid transitions between search criteria (DR2), the tool introduces a novel design concept of using facets to select items without filtering the item space. Particularly, we propose a filter-swipe technique that enables users to drag a categorical facet value sequentially over linear facet bars to view the items in the intersection of the two facets along with the categorical facet dynamically summarising the items in the intersection. Three applications with various datasets demonstrate how the features support information discovery with ease. A comparison with a baseline system provided evidence that the task performance of the IVF tool was comparable to the typical query search interface. Another study of 11 participants with realistic email search tasks shows that dynamic suggestions through the timeline navigation can help discover useful suggestions for search; the novel design concept was favoured over using facet values as filters. Based on these practices, we derive IVF design implications for fluid, exploratory searches. Graphical abstract
The Research on the Strategy of College English Teaching Mode Based on Mobile Terminal Under the Background of Internet+

With the development and progress of the times, people have new ways to explore knowledge. With the advent of the information age, people can learn the knowledge they want more and more conveniently on the Internet, and through Internet-based big data methods, people can also effectively reduce the burden of learning. Through mobile phones, computers, tablets and other electronic people can learn all kinds of knowledge without leaving home, and get rid of the shackles of traditional preaching learning. At present, the study of college English is also adapting to the pace of social trends. The emergence of mobile terminal platforms has provided students with more possibilities for learning college English, not limited by time and place, and has multiple means and comprehensive customized learning programs. The advantage has been liked by more and more college students. The following is a research and analysis on the mode of college English teaching on the mobile terminal platform.
Three-Dimensional Scenic Spot Roaming System Based on Virtual Reality Technology

With the development of human civilization and the progress of society, some intelligent technologies such as computer software technology and electronic information technology are gradually improved. Data virtual technology has become a new development direction. In this context, virtual reality technology came into being. In this era of rapid economic development, tourism has become a way of life accepted and practiced by people. Therefore, in this information age, many scenic spots began to use the Internet to promote scenic spots, and the research of three-dimensional scenic spot roaming system based on virtual reality technology has started. In this paper, through the method of virtual reality modeling and roaming, combined with the specific situation of the scenic spot, the three-dimensional roaming model of the scenic spot is established, and the real-time three-dimensional roaming of multiple scenes and the humanized design of the system are realized. In the previous research, we found that virtual and augmented reality technology can directly use computer technology to generate a more realistic three-dimensional roaming environment of human-computer simulation, which makes users completely immersed in the virtual environment. The direct interaction between users and virtual environment has been realized through the virtual human-computer interaction interface. Through data analysis, it can be found that the overall success rate of transaction completion and successful transaction reaches 100%.
Teaching Improvement Strategies on E-Commerce and Logistics Module of Application-Oriented Undergraduate International Trade Training Program

This paper points out a series of problems existing in the current curriculum system of training programs, including the obscure understanding of curriculum concept, the inconsistency between curriculum objectives and actual content design, the untimely update of curriculum content, the unreasonable structure of curriculum and the traditional way of curriculum activities.
The Creative Process of Teaching Poetry Class V Elementary School

The aim of this research is determine the problem of learning Indonesian in grade V elementary schools with very low poetrythemed material. The results of this study can improve the material in the 2013 curriculum in elementary schools. The weakness of implementing the 2013 curriculum is the limited material in learning, especially material in learning poetry. In studying poetry material, students can express or express feelings, ideas or ideas in beautiful words and can enter the listener's feelings. This research is a method to develop literary writing in producing good poetry texts. The place in this study chosen was SDIT Mutiara Insan Sukoharjo. Poetry learning materials can be developed through the process of students producing poetry that is seen based on the content and language that is conveyed. Based on the results of the research that in studying Indonesian language learning materials, especially poetry, students can produce good work and succeed in achieving more advanced goals.
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Your gateway to gender and women's studies resources at the UW-Madison Libraries and beyond.
The Development Direction of Ideological and Political Education in the New Era

Strengthening the development of the right to speak in ideological and political education is not only the goal of the ideological work of the New Era Party, but also necessary to enhance the learning effect of the ideological political process. Currently, Western ideological discourse enters our school through various media. However, ideological and citizenship education in Korea has problems such as a lagging innovation discourse, barriers to broadcasting and limited coverage. The new era represents a new historical mission, the problems of the times and the needs of the people. Ideological and political education also brought new demands and new challenges for development. At the same time, he encounters a barrier to discrimination that weakens the basis for transformation, and the imbalance between subject and object causes the attempts at transformation. Inequalities and conflicting values lead to a transformational dilemma that has no motivation for transformation. In practice, we must vigorously resist the erosion of Western ideological discourse. Integrate the media to continuously optimize the dissemination of ideological and political educational discourse.