Reviewerly/exHarmony huggingface dataset:
Discussion on mixed teaching mode of college English under the background of Internet

Under the background of the increasing progress of science and technology in China, the Internet, as a new industry, not only promotes the transformation of China's economic development mode, but also provides support for education. At the same time, the development of “Internet” has brought great innovation to the traditional educational thought and mode, and promoted the development of college English teaching. Nowadays, the innovation and development of college English education focuses on how to integrate the traditional classroom education method with the online teaching method, and what role the “Internet” will play in the process. This article will explore the promotion of the Internet to the innovation and development of traditional college English education, and briefly understand the situation and innovation of college English education and teaching under the background of intelligence. This paper studies the integration and application of mixed teaching mode in college English education under intelligent conditions.
Extracting the fundamental diagram from aerial footage

Efficient traffic monitoring is playing a fundamental role in successfully tackling congestion in transportation networks. Congestion is strongly correlated with two measurable characteristics, the demand and the network density that impact the overall system behavior. At large, this system behavior is characterized through the fundamental diagram of a road segment, a region or the network.In this paper we devise an innovative way to obtain the fundamental diagram through aerial footage obtained from drone platforms. The derived methodology consists of 3 phases: vehicle detection, vehicle tracking and traffic state estimation. We elaborate on the algorithms developed for each of the 3 phases and demonstrate the applicability of the results in a real-world setting.
New optimization algorithm to improve numerical integration method

This paper introduces a new proposed algorithm of numerical integration evaluation regarded as optimization problem solution. The new method is characterized to have superiority features such as attractive, accurate and rapid. An improvement of polynomial regression has been done by selecting nearest neighbors points being searched around of the values of regression coefficients which calculated by using least squares method. Furthermore, Trapezoidal and Simpson methods were considered as traditional methods in numerical integration. In this regard, comparison has been done among all four methods used in simulation application via MATLAB program that have been performed to achieve the desired numerical results for the four methods. As conclusion, the proposed algorithm approved its superiority.
CORRELATION BETWEEN LISTENING ABILITY AND VOCABULARY MASTERY AT STKIP PGRI TRENGGALEK

The purpose of this research was to find a correlation between listening ability and vocabulary mastery. In this research, respondents came from second and fourth-semester students at STKIP PGRI TRENGGALEK in the 2017/2018 school year. The number of the sample was 31 people using purposive sampling technique. This research is a correlation design and quantitative approach. The data obtained in this research used two tests: gap filling tests for listening and multiple choice tests for vocabulary tests. This research data is calculated using the Person Product Moment formula with Microsoft excels application by manually. It showed that the two variables result is 0.164 it means, there is a correlation but very low. So the conclusion of this research there is a very low Correlation between listening ability and vocabulary mastery at STKIP PGRI Trenggalek
Awareness and Use of Cloud Computing Services by Librarians in Selected Universities in Edo State

This study examined the awareness and use of cloud computing services by librarians in selected universities in Edo State. Descriptive survey research design was employed and the instrument used was questionnaire.  The population of the study was 132 professional and Para-professional librarians. The total enumeration technique was used to select the entire population because the size was manageable. Simple percentage, frequency count and mean were used to analyze the data collected. From the analysis of data gathered, it was found that the librarians are aware of the use of OCLC, world cat and Google docs to a very high extent. It was found that the librarians used cloud computing services for collection development functions, and cataloging. Based on the findings it was recommended that management of the libraries should support librarians by providing constant internet connections, constant power supply, adequate funding of the library for effective and efficient service delivery.
Design of Cluster Data Association Mining Algorithm Based on Multi-GANs

Design of general cluster data association mining algorithm based on Multi-GANs is studied in this paper. This article has tested this framework in a variety of environments. Experiments show that the method in this paper can achieve a higher attack success rate for targetless attacks in a white box environment, and it also has a certain attack effect in targeted attacks. The proposed research work considers the GANs, the clustering and the roles of association mining. In the process of error back propagation, the weight and threshold of the network are continuously adjusted to achieve the output that meets the set error. We improve the error coding model to enhance the performance. The experiment results have proven the results.
How Do Web-Active End-User Programmers Forage?

Web-active end-user programmers spend substantial time and cognitive effort seeking information while debugging web mashups, which are platforms for creating web applications by combining data and functionality from two or more different sources. The debugging on these platforms is challenging as end user programmers need to forage within the mashup environment to find bugs and on the web to forage for the solution to those bugs. To understand the foraging behavior of end-user programmers when debugging, we used information forging theory. Information foraging theory helps understand how users forage for information and has been successfully used to understand and model user behavior when foraging through documents, the web, user interfaces, and programming environments. Through the lens of information foraging theory, we analyzed the data from a controlled lab study of eight web-active end-user programmers. The programmers completed two debugging tasks using the Yahoo! Pipes web mashup environment. On analyzing the data, we identified three types of cues: clear, fuzzy, and elusive. Clear cues helped participants to find and fix bugs with ease while fuzzy and elusive cues led to useless foraging. We also identified the strategies used by the participants when finding and fixing bugs. Our results give us a better understanding of the programming behavior of web-active end-users and can inform researchers and professionals how to create better support for the debugging process. Further, this study methodology can be adapted by researchers to understand other aspects of programming such as implementing, reusing, and maintaining code.
Application of Artificial Intelligence System in Smart Education in Cloud Environment with Optimization Models

Application of the artificial intelligence system in smart education in cloud environment with optimization models is studied in this research. As cloud computing is widely used in society, cloud computing has become the convenient and fast information equipment, hence, this technology is considered as a basis for the designed framework. The combination of the cloud computing and scientific research. Scientific research involves a lot of large-scale computing, and many research institutions do not have such a large-scale computing equipment. The designed model is tested on the scenario of smart education. The results will be applied to the real scenarios.
Local Binary Quaternion Rotation Pattern for colour texture retrieval

Color is very important feature for image representation, it assumes very essential in the human visual recognition process. Although, several color extension of Local Binary Pattern processes the color texture from the three color channels separately (Marginal way). Aware of the high interaction that exists between different channels in the color image, this work introduces a new vector process to define a local descriptor for color images named Local Binary Quaternion Rotation Pattern (LBQRP). In this LBQRP purpose, the quaternion representation is used to represent color texture. The distance between two color can be expressed as the angle of rotation between two unit quaternions using the geodesic distance. After a LBQRP coding, local histograms are extracted and used as features. Experiments on three challenging color datasets: Vistex, Outex-TC13 and USPtex are carried out to evaluate the LBQRP performance in texture classification. Results show the high efficiency of the proposed approach facing to several stat-of-art methods.
Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation

Homography estimation from a pair of natural images is a problem of paramount importance for computer vision. Specialized deep convolutional neural networks have been proposed to accomplish this task. In this work, a method to enhance the result of this kind of homography estimators is proposed. Our approach generates a set of tentative color transformations for the image pair. Then the color transformed image pairs are evaluated by a regressor that estimates the quality of the homography that would be obtained by supplying the transformed image pairs to the homography estimator. Then the image pair that is predicted to yield the best result is provided to the homography estimator. Experimental results are shown, which demonstrate that our approach performs better than the direct application of the homography estimator to the original image pair, both in qualitative and quantitative terms.
KEMAMPUAN MENULIS TEKS NEGOSIASI PADA SISWA SMK PERSADA KELAS X TAHUN PELAJARAN 2019/2020

Negotiation is a form of bargaining interaction carried out by two or more people in order to reach a mutual agreement with different goals. The purpose of this research is to find out and describe the extent to which the ability to write negotiating texts in class X students in the even semester of SMA Persada Bandar Lampung. This study used descriptive qualitative method. The population in this study amounted to 67 students from 3 classes. The sample in this study were 25 students. Data collection techniques used are performance techniques. The results of this study indicate that the ability to write negotiating texts for grade X students of SMK Persada Bandar Lampung in the 2019/2020 Academic Year analyzed based on aspects of title selection and formulation, relevance of content, organization of ideas, and spelling and writing mechanics can be conveyed that students' abilities in writing text negotiations are considered not optimal.
Cross-Regional Dimension of Students and Youth Educational Projects

The paper contains points introduced during the roundtable Cross-regional dimension of students and youth educational projects, that took place in the Russian Center for Science and Culture in Paris (February 2019). The speaker stresses the importance of the events of this kind within the framework of Trianon Dialogue format and introduces Meeting Russian Caucasus project.
Forthcoming: Constituency and convergence in the Americas

This volume brings together studies on morphosyntactic and phonological constituency from a host of languages across the Americas. The study expands on previous multivariate typological work on phonological domains by simultaneously coding the results of morphosyntactic constituency tests. The descriptions are geared towards developing a typology of constituency and linguistic levels in both morphosyntactic and phonological domains. The multivariate approach adopted in this volume deconstructs constituency tests and phonological domains into cross-linguistically comparable variables applying and extending autotypology method to the domain of constituent structure. Current methodologies for establishing constituents have been criticized for containing an in-built selection bias, where the results and interpretation of tests are chosen or sampled in such a fashion that specific analyses are prejudged to be correct or false in a non-rigorous fashion. The papers of this volume develop novel methodology for reporting and coding constituency variables for language description and comparison that seeks to reign in selection bias allowing theories concerning the relationship between morphosyntactic and phonological constituent structure to be more severely tested.
A Study of the Design of Emotional Points in Speech Drafts Writing

As it’s known to all, language is produced before written words, and speeches are also produced before speech drafts. Speech is not a simple oral expression, but a kind of language art. Many masterpieces that have been handed down for thousands of years are based on reason and emotion, making use of true feelings to move broad masses of readers. However, in the current speech drafts writing, there are many problems, such as empty content, rigid form and affectation, which can not meet the multi-level needs of contemporary social discourse scenes. Therefore, this paper takes the “emotional points” as the starting point, and discusses it from different aspects on the basis of expounding its concept and history. At the same time, this paper briefly analyses the prospects and outlets of emotional points design in the current speech drafts writing.
Examining the Drivers and Consequences of Salesperson Evasive Hiding: An Abstract

Salespeople often face the dilemma of having to protect their personally acquired market knowledge from others in their organization, while also seeming to be a team player. In order to not being perceived as being opportunistic by their colleagues, salespeople have the option of: (1) sharing their information, or (2) neglecting to divulge their knowledge, possibly being perceived as uncooperative, or (3) appearing to share information while in actuality obscuring substantive knowledge, which we call evasive hiding. As a way to protect their knowledge, evasive hiding occurs when salespeople intentionally appear to be openly sharing sales knowledge when they are actually deliberately avoiding the need to provide any useful information to others (Connelly et al. 2012). Research has shown that individuals evasively hide knowledge due to interpersonal and situational factors (Connelly et al. 2014). Yet, knowledge hiding can have serious consequences for performance (Černe et al. 2014; Peng 2013), as salespeople may not consider this to be so detrimental. We surmise that knowledge is a critical source of competitive advantage for individual salespeople, especially when you consider that research has shown a positive relationship between salesperson knowledge and performance (e.g., Mariadoss et al. 2014). To further exacerbate this, firms tend to foster situations where salespeople have to compete with one another in order to enhance sales force productivity, resulting in the unintentional side effect where salespeople end up viewing their colleagues as internal rivals in competition for limited organizational rewards like public recognition, promotion, and financial compensation (Anaza and Nowlin 2017). Therefore, salespeople may act to defend their source (e.g., knowledge) of competitive advantage much like any organization would. Leveraging social exchange theory, we investigate the relational antecedents and customer-directed outcomes of evasive hiding as well as the conditional effects of pushover manager and environmental dynamism. The empirical findings reveal that the antecedents’ effect on evasive hiding are conditional upon the managerially-actionable construct of pushover manager. Evasive hiding was subsequently found to have a negative impact on customer-directed outcomes, particularly at low levels of environmental dynamism.
High-resolution Sampling and Photogrammetry of the Permian-Triassic Boundary Within the Festningen Profile, Svalbard

&amp;lt;p&amp;gt;The Permian period ended with a mass extinction event about 252 million years ago. A likely trigger of the mass extinction was the eruption of large volumes of magma which had moved through the Tunguska Basin in Siberia. The renowned Festningen section in the outer part of Isfjorden, western Spitsbergen, offers a c. 7 km long nearly continuous stratigraphic section of Lower Carboniferous to Cenozoic strata, where the end-Permian extinction interval is well-exposed. Tectonic deformation associated with the Paleogene West Spitsbergen fold-and-thrust-belt tilted the strata to near-vertical, allowing easy access along the shoreline. The section is a regionally important stratigraphic reference profile and is a key locality for geologists visiting Svalbard. The main objective of our fieldwork in September 2020 was to collect closely spaced mudstone (0.25 to 1 m interval) and ash layer (6 layers of 0.5 to 1.5 cm thickness) samples across the Festningen Permian-Triassic boundary for chemostratigraphic and geochronological assessments. Carbon isotope data reveal a well-defined negative deltaC13 excursion in the lower part of the Vardebukta Fm. Zircons are present in most of the ash layer samples and these will be dated at the University of Oslo TIMS U-Pb Isotope Geology Laboratory. In this contribution, we will also present a new digital outcrop model of the P-Tr boundary section acquired using a UAV (Mavic 2 Pro, 20MP Hasselblad camera). During acquisition, the maximum drone speed was set to 1 meter/second (i.e., &amp;amp;#8220;tripod mode&amp;amp;#8221;), and photographs were taken automatically at set time intervals (e.g., 1 photo every 5 seconds &amp;amp;#8776; meters). The digital outcrop model offers a pixel resolution of 7.27 mm/pixel. The Festningen model will be available online through the Svalbox.no geoscience data platform.&amp;lt;/p&amp;gt;
Embedding Structured Dictionary Entries

Previous work has shown how to effectively use external resources such as dictionaries to improve English-language word embeddings, either by manipulating the training process or by applying post-hoc adjustments to the embedding space. We experiment with a multi-task learning approach for explicitly incorporating the structured elements of dictionary entries, such as user-assigned tags and usage examples, when learning embeddings for dictionary headwords. Our work generalizes several existing models for learning word embeddings from dictionaries. However, we find that the most effective representations overall are learned by simply training with a skip-gram objective over the concatenated text of all entries in the dictionary, giving no particular focus to the structure of the entries.
Decode Human Immune System for Blood Disease Detection using Machine Learning Algorithms

Quick and accurate medical diagnosis are crucial for the successful treatment of diseases. Using machine learning algorithm and based on laboratory blood test result, we have built a model to predict hematology diseases. It is a predictive model which uses various symptoms causing the disease and a few blood parameters to detect the disease. Blood analysis is an essential indicator for many diseases. It contains several parameters which are sign for various specific blood diseases. For predicting the disease according to blood analysis, symptoms that leads to identifying the disease precisely should be recognized. Our model uses machine learning which is the field responsible for building models for predicting the output based on previous data. Accuracy of the machine learning algorithm is based on quality of data collected for learning process. Keywords: Disease, Symptoms, Blood Parameters, technology, human immune system, algorithm. Cite this Article: Ria Vijay Nagaonkar, Suraj Rajaram Jare, Rishi Vinod Pandey, Suhasini Parvatikar. Decode Human Immune System for Blood Disease Detection using Machine Learning Algorithms. Journal of Advancements in Robotics. 2020; 7(2): 9–14p.
IEEE Access Special Section Editorial: Blockchain-Enabled Trustworthy Systems

We are enjoying the benefits brought by the accelerated development of computing systems and the Internet. However, we are also facing a few security and privacy vulnerabilities caused by the increasing system complexity, heterogeneity, dynamicity, and decentralized nature. These security and privacy vulnerabilities may prevent the wide adoption of information and communications technology (ICT). Therefore, trust management has become a crucial aspect of developing trustworthy systems with the preservation of security and privacy. The recent advances in blockchain technologies are bringing opportunities in fully realizing trustworthy systems. Blockchain technologies can enable anonymous and trustful transactions in decentralized and trustless environments. As a result, blockchain-enabled trust management must help to reduce system risks, mitigate financial fraud, and cut down the operational cost of computing systems. Blockchain-enabled trustworthy systems can apply to diverse areas, such as financial services, social management, the Internet of Things, and supply chain management.
Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organizational factors raise the need for flexible traceability. We present how traceability can be evolved in the development lifecycle, from early elicitation of traceability needs to the implementation of mature traceability strategies. Moreover, we shed light on how traceability can be managed flexibly within an agile team and more formally when crossing team borders and organizational borders. Based on these insights, we present requirements for flexible tool solutions, supporting varying levels of data quality, change propagation, versioning, and organizational traceability.
Security, Trust and Privacy: Challenges for Community-Oriented ICT Support

With ICT increasingly becoming the main basis for community communication and cooperation, security, trust, and privacy protection are commonly accepted as core aspects of system design and operations. Starting with a representative example illustrating the resulting challenges, this talk will then give an overview of major legal requirements with the focus on privacy protection. Against this background the feasibility of security and trust mechanisms will be discussed in the context of communities that need to share information and have to cooperate in multiple ways to reach their common goals.
THE EFFECTIVENESS OF SCHOOLOGY ON TECHNOLOGY SKILLS: E-LEARNING INTEGRATION IN EDUCATION

Schoology is an e-learning platform that offers several exciting features that can be optimized by educators and students in tandem with parents. This can be one of the media in optimizing strong communication between the three. Schoology is also able to be one of the pathways to improving the skills in utilizing the technology of students who have also become one of the demands of the 4.0 revolution. Schoology is able to be used by educators in particular types of education and in certain subjects. This study aims to identify the effectiveness of Schoology on the technology skills of students in higher education ranking. The research results have shown that Schoology poses an effect on improving technology skills in aspects of text formatting and searching the web.