Reviewerly/exHarmony huggingface dataset:
Latent semantic indexing (LSI) and its impact on copywriting

Latent semantic indexing (LSI) is becoming more and more popular in copywriting, gradually replacing texts written on the principles of SEO. LSI was called in the 2010s, when popular search engines switched to a qualitatively new way of ranking materials and sites. The difference between SEO and LSI ways of creation lies in the fact that search engines rank SEO materials by keywords, while LSI are ranked how fully the topic is covered and how useful the article will be to the reader. Consequently, in addition to keywords and phrases, the associative core is involved here. Materials written for people have replaced the texts created for the search engine. The article describes the algorithm for creation of the associative and thematic core, the ways in which this can be done. The basic steps helping to create an LSI text are also shown.The author underlines that due to the specificity of the presentation of a significant amount of information and the maximum expertise in the disclosure of the topic, text writers accustomed to working on the principles of SEO have to learn to write within a new paradigm. The owners of the websites that host articles created by LSI principles have discovered the advantages of this way of presenting information, since their resources have become better indexed and take the leading positions in search results. Such algorithms as “Baden-Baden”, “Korolev” and “Panda” have positively influenced the Internet environment as a whole, since re-optimized texts, which were filled with keys and were of little use to the reader, now have turned out to be on the last positions of issue. The new method of ranking according to the LSI method allows specialists to create the texts that are not only useful and expert but also differ in lexical richness, using expressive and figurative means of the language, which could not be assumed in SEO materials.It is highlighted in the article the use of neural networks should bring the way of presenting information to the consumer’s needs even more, inventing techniques that will allow leading materials created in an ordinary language to lead the positions without the need to incorporate key phrases into the text. We believe that the LSI-method, which has perfectly manifested itself in copywriting, is capable of unlocking the potential of the media texts, which are now being written on the principles of SEO.
L’apprendimento linguistico tra parametri e transfer

This article investigates the relation between L1 and L2 in the light of the transfer phenomena. More precisely a revision of the UG notion and parameter is proposed on the basis of the mentalist model proposed within the bio-linguistic program in some recent works by Chomsky. The idea being discussed here is that parameterization is a phenomenon associated with the externalization of linguistic expressions in terms of lexical and morpho-syntactic properties, on the basis of the basic properties of language. The notion of language coincides with a specialized cognitive capability, i.e. the combinatory mechanism (Merge), whereas its application implies the interaction with the external interpretive systems, namely sensory-motor and conceptual-intentional systems. As a consequence, transfer, as depending on the morpho-lexical organization of languages, is a mechanism that does not call into question the cognitive nature of language. On the contrary, we have to look at transfer as the natural solution for the acquisition of L2.
Multi-agent Path Planning with Non-constant Velocity Motion

Multi-agent path planning has wide application in fields such as robotics, transportation, logistics, computer games, etc.. To formulate the multi-agent path finding as a concisely discretized problem, most of the previous works did not construct a detailed motion model of each agent. While many elegant algorithms were proposed in the literature, a method to efficiently plan the paths for multi agents with non-constant velocity is still lacking. In this paper, we propose two methods CRISE and COB to extend the existing algorithms for non-constant velocity motion path planning.
Memory based Multiagent One Shot Learning

One shot learning is particularly difficult in multiagent systems where the relevant information is distributed across agents, and inter-agent interactions shape global emergent behavior. This paper introduces a distributed learning framework called Distributed Modular Memory Unit (DMMU) that creates a shared external memory to enable one shot adaptive learning in multiagent systems. In DMMU, a shared external memory is selectively accessed by agents acting asynchronously and in parallel. Each agent processes its own stream of sequential information independently while interacting with the shared external memory to identify, retain, and propagate salient information. This enables DMMU to rapidly assimilate task features from a group of distributed agents, consolidate it into a reconfigurable external memory, and use it for one shot multiagent learning. We compare the performance of the DMMU framework on a simulated cybersecurity task with traditional feedforward ensembles, LSTM based agents, and a centralized framework. Results demonstrate that DMMU significantly outperforms the other methods and exhibits distributed one shot learning.
An Underwater Image Bubble Noise Removal Method Based on Optical Flow

It is very important for underwater robots to accurately detect and locate target objects. However, under many circumstances, it is difficult to clearly observe the target object due to the existence of bubble noise. In this paper, we proposed a method to solve this problem. First, we used the LK optical flow algorithm to calculate the motion vector of the image background and compensate for the background motion. Then, the optical flow field of the bubbles was calculated by the HS optical flow algorithm, and the area where the bubble existed was obtained by binarizing the image. Finally, we used the adjacent frame image to repair the bubble area. We carried out a bubble noise removal experiment. The results show that this method can effectively remove the bubble noise in the image.
Deep Chit-Chat: Deep Learning for Chatbots

The tutorial is based on our long-term research on open domain conversation and rich hands-on experience on development of Microsoft XiaoIce. We will summarize the recent achievements made by both academia and industry on chatbots, and give a thorough and systematic introduction to state-of-the-art methods for open domain conversation modeling including both retrieval-based methods and generation-based methods. In addition to these, our tutorial will also cover some new trends of research of chatbots, such as how to design a reasonable evaluation metric for open domain dialogue generation, how to build conversation models with multiple modalities, and how to conduct dialogue management in open domain conversation systems.
The Influence of Various Text Characteristics on the Readability and Content Informativeness

Currently, businesses increasingly use various external big data sources for extracting and integrating information into their own enterprise information systems to make correct economic decisions, to understand customer needs, and to predict risks. The necessary condition for obtaining useful knowledge from big data is analysing high-quality data and using quality textual data. In the study, we focus on the influence of readability and some particular features of the texts written for a global audience on the texts quality assessment. In order to estimate the influence of different linguistic and statistical factors on the text readability, we reviewed five different text corpora. Two of them contain texts from Wikipedia, the third one contains texts from Simple Wikipedia and two last corpora include scientific and educational texts. We show linguistic and statistical features of a text that have the greatest influence on the text quality for business corporations. Finally, we propose some directions on the way to automatic predicting the readability of texts in the Web.
DEVELOPING READING COMPREHENSION ASSESSMENT BASED ADOBE FLASH CC2015 FOR BIPA INTERMEDIATE LEVEL

Purpose of Study: Learning Indonesian for foreign speakers of Indonesian Language classes (BIPA) needs to be assessed using an interesting evaluation device that serves to make it easier for students to do tests, especially tests to measure reading comprehension. The required media was developed based on the 2015 Adobe Flash Creative Cloud software for intermediate level BIPA. The purpose of this study is to develop assessment media to read properly and effective understanding.&#x0D; Methodology: Research and Development research uses the Borg and Gall model which is simplified into six stages, namely (1) needs analysis; (2) product design; (3) manufacture of products; (4) validation; (5) revisions; and (6) product testing. Data collection techniques used were questionnaires and tests.&#x0D; Results: The results showed that the media for reading comprehension based on Adobe Flash Creative Cloud 2015 software was proper 76 and practical.&#x0D; Implications/Applications: Learning Indonesian for BIPA students is certainly different from domestic student learning. The specificity of treatment is not only in the teaching material but also in the assessment. This is done with the aim that learning is more successful because it is provided by media that is very helpful for BIPA students in mastering reading skills. Quiz as a media assessment was developed using local wisdom materials in Indonesia.
INTERNET COMMUNICATION TOOLS: THE WAY OF CULTURAL DEVELOPMENT OF PERSONALITY OR FREEDOM OF CHOICE IN THE DIGITAL AGE

With the introduction of almost every sphere of human activity computer technologies, there is a need for the formation of holistic scientific position in determining further cultural development of the human being. An assumption has been made, that a resourceful basis for communication research via the Internet are philosophical categories and cultural-historical psychology, because its statements allow to conceptualize the Internet communication tools as indirect activity. The specific features of electronic interactions, which have a significant impact on development of the of the personality have been highlighted and analyzed in the article: a lack of tactile sensations, increasing the volume and speed of information transfer, the introduction of artificial intelligence in communication tools.
Securing Big Data

Recent cyber attacks have shown that the leakage/stealing of big data may result in enormous monetary loss and damage to organizational reputation, and increased identity theft risks for individuals. Furthermore, in the age of big data, protecting the security and privacy of stored data is paramount for maintaining public trust, and getting the full value from the collected data.
Spatially Biased Random Forests.

Recent successes in deep learning have led to explorations of what makes these techniques so powerful. One goal of such studies is to determine whether such properties can be transferred to alternative learning methods and yield similar benefits. Since the generalization power of any learning algorithm depends upon the inductive bias(es) of that algorithm, we hypothesize that utilizing a bias incorporated by CNNs and other deep methods--spatial locality--can benefit other learning methods as well. We test this hypothesis by incorporating spatial structure when constructing random forests. Our experiments demonstrate that incorporating a spatial locality bias improves the performance of random forests on several image classification tasks.
Alignment Errors vs. Measurability for Null-Measurements of Aspheres

We show that an imperfectly aligned asphere-CGH-measurement leads to artifacts that are indistinguishable from common manufacturing errors such as trefoil and spherical aberration. We apply a machine learning approach to correct for these artifacts.
A Voting Procedures Recommender System for Decision-Making

Facilitation is a critical element in decision-making using the tools of new technology. Voting is a tool commonly used in decision making. The choice of a voting procedure is not easy for a novice facilitator. So it is interesting to propose a recommendation system that assists novice facilitators in their voting procedures choice. There are several voting procedures, some of which are difficult to explain and which can elect different options or alternatives. The best choice is one whose election is easily accepted by the group. Voting in social choice theory is a widely studied discipline whose principles are often complex and difficult to explain at a decision-making meeting. So, a recommendation system can alleviate the facilitator on his work in finding adequate voting procedure to be applied in a group decision.
Research on the Cooperative Education Mode of Schools and Enterprises in the New Era

The development of China has put forward new requirements for the cultivation of talents in colleges and universities under the background of the new era.The paper mainly explores the school-enterprise collaborative education model based on the â€œSchool-Enterprise Cooperative Education Steering Committeeâ€, and investigates the current status of the school-enterprise collaborative education mechanism from the perspectives of enterprises, students and graduates. Formulating the program of talents training from four aspects, including the construction of school-enterprise cooperation faculty, the construction of the curriculum system, the innovation of teaching forms, the establishment of the evaluation system, the improvement of the teaching quality monitoring and security system, and thus truly realize the new era of students-college-enterprise win.
SWRR: The Link Scheduling Algorithm Based on Weighted Round-Robin

With the rapid development of the Internet, people pay more and more attention to the protection of privacy. The second-generation onion routing system Tor is the most commonly used among anonymous communication systems, which can be used to protect user privacy effectively. In recent years, Tor’s congestion problem has become the focus of attention, and it can affect Tor’s performance even user experience. Firstly, we investigate the causes of Tor network congestion and summarize some link scheduling algorithms proposed in recent years. Then we propose the link scheduling algorithm SWRR based on WRR (Weighted Round Robin). In this process, we design multiple weight functions and compare the performance of these weight functions under different congestion conditions, and the appropriate weight function is selected to be used in our algorithms based on the experiment results. Finally, we also compare the performance of SWRR with other link scheduling algorithms under different congestion conditions by experiments, and verify the effectiveness of the algorithm SWRR.
The use of statistics to define taxonomies of film voices: a practical approach to documentary classification

The study of visual content using qualitative methods currently involves much scholarly work in the field of digital humanities. Documentary films are considered among those objects defined as visual content and are therefore not the focus of most attention within Film Studies. One of the best-known researchers in this area, Bill Nichols, proposed a theoretical classification of six documentary voices that is widely recognized in academic circles. However, the classification is based on induction and intuition which, until now, have not been verified in accordance with the evidence. This study proposes a mixed qualitative and quantitative methodology that allows the authors to surpass Nichols’ model and generate a new classification based on empirical criteria. To that end, they study the opinions of users of and experts on Nichols’ theory through the card sorting technique borrowed from cognitive science that is based on multivariate statistics. In this way, they generate a hierarchy of formal cinematographic elements grouped into four documentary voices and Nicholas’ classification proposal is partly replaced as two of the voices in his model disappear but the four others are confirmed. In addition, this new model allows the authors to determine which formal elements are assigned to each one of the confirmed documentary modes and with what relative weights, thereby opening up the possibility of generating a predictive model. The article therefore demonstrates that cluster analysis and other techniques borrowed from multivariate statistics can be used to empirically and quantitatively verify theories in film studies as well as in other areas such as poetics. This suggests that it is possible to verify empirically and use quantitative models for the study of visual content and complement other methods based on induction and intuition.
Effective Evaluation of XML Queries in a Visual Environment

Since its emergence in 1997, Extensible Markup Language (XML) has become a standard data format for data exchange among a variety of web applications.In this paper, we present a framework to effectively evaluate XML queries in a visual environment.We have developed a system termed VXPath, which is a visual XPath query evaluator that allows the user to evaluate various XPath queries by clicking the nodes in an expanding tree instead of typing the whole XPath queries manually.Our system GUI is built on top of Microsoft .NET Windows Forms Applications.We have implemented most XPath axes in our system, including child, descendant, self, parent, ancestor, following-sibling, preceding-sibling, predicate and so on.In order to handle large size XML documents, instead of loading the whole XML document into memory, we developed an effective algorithm to extract a concise data synopsis called structural summary from the original XML document to avoid the loading overhead for large XML documents.We evaluated our system over the data from XMark and DBLP and our system can handle large XML documents up to gigabytes.
DNS Firewall Data Visualization

Common security tools generate a lot of data suitable for further analysis. However, the raw form of the data is often too complex and useful information gets lost in a large volume of records. In this paper, we propose a system for visualization of the data generated by a DNS firewall and outline a process of visually emphasizing information important to incident handlers. Our prototype suggests that such visualization is possible, keeping the balance between the amount of displayed information and the level of detail.
Progress with the Geological and Ecological Survey in the Critical Zone of the Global Black Soil Which is Linked with the Sky and Ground Monitoring Methods (ICGP665)

Acta Geologica Sinica - English EditionVolume 93, Issue S3 p. 160-162 PART 2: Research Progress of the Chinese IGCP ProjectsFree Access Progress with the Geological and Ecological Survey in the Critical Zone of the Global Black Soil Which is Linked with the Sky and Ground Monitoring Methods (ICGP665) jiajia YANG, Corresponding Author jiajia YANG haixianxiaomei@163.com Shenyang Geological Survey Center, China Geological Survey, Shenyang 100034 Liaoning, ChinaCorresponding author. E-mail: haixianxiaomei@163.comSearch for more papers by this authorHuimin DAI, Huimin DAI Shenyang Geological Survey Center, China Geological Survey, Shenyang 100034 Liaoning, ChinaSearch for more papers by this author jiajia YANG, Corresponding Author jiajia YANG haixianxiaomei@163.com Shenyang Geological Survey Center, China Geological Survey, Shenyang 100034 Liaoning, ChinaCorresponding author. E-mail: haixianxiaomei@163.comSearch for more papers by this authorHuimin DAI, Huimin DAI Shenyang Geological Survey Center, China Geological Survey, Shenyang 100034 Liaoning, ChinaSearch for more papers by this author First published: 31 May 2019 https://doi.org/10.1111/1755-6724.14277Citations: 1 About the first author (also corresponding author): YANG Jiajia, male, born in 1984 in Jincheng City, Shanxi Province; doctor; graduated from Jilin University; Senior engineer of remote sensing of Shenyang Geological Survey Center of China Geological Survey. He is now interested in the study on combined application of remote sensing and geochemistry in integrated soil surveys. Email: haixianxiaomei@163.com; phone: 024-86002913, 18704048774. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume93, IssueS3Special Issue: Abstracts of Deep-time Digital Earth (DDE) Forum, 26–28 Feb 2019, Beijing, ChinaMay 2019Pages 160-162 RelatedInformation
Big Data Help Paint a New Picture of Trace Element Cycling

A new framework for understanding the suite of processes acting on marine particulate trace metals exemplifies how alternative analyses can maximize the information that large data sets provide.
A Detection Aided Multi-Filter Target Tracking Algorithm

When the target is partially occluded or undergoes drastic appearance change, drift is prone to occur in traditional correlation filter-based trackers and ultimately leads to tracking failure. This paper proposes a robust tracking algorithm, which can be applied to practical engineering. The proposed algorithm divides all training samples into different training sets based on their similarities. An independent filter is trained for every training set. In each frame of the tracking process, the similarity between the candidate region and any training set's training samples is calculated to select the most matched filter for target location. As a newly introduced training sample, a feature map within the current frame's estimated target bounding box is assigned to the most similar training set to update the most matched filter. The updating of each filter is relatively independent. Each filter corresponds to one kind of target's typical appearance, and thus, the proposed tracking algorithm can memorize a variety of typical target appearances that appeared in the past and adapt to target's discontinuous appearance change. The detector improves tracking accuracy and assists occlusion judgment. After occlusion, the target may reappear with a different posture. As long as similar postures have been captured in the previous tracking process, the target can be retrieved accurately while not being confused with other objects of the target's category. We evaluated our method on massive videos shot in actual engineering sites, and the result demonstrates that the proposed tracking algorithm can handle occlusion and target's posture changes very well and significantly outperforms other tracking algorithms.