Reviewerly/exHarmony huggingface dataset:
Shadow-Reading Strategy Effect on EFL Listening Comprehension Skills and Motivation

This paper examines the effect of shadow reading strategy on secondary school students’ listening comprehension skills and motivation. These participants, who constituted the human subjects for the study, were ninth-year students pursuing other subjects in Arabic and learning English as a Foreign Language (EFL) as well. The research questions asked to accomplish the purpose of the study focused on: (1) Determining listening comprehension skills suitable for the EFL secondary school students; (2) Finding out differences in listening comprehension test regarding the experimental and control group; and (3) Finding out differences in listening motivation scale scores regarding experimental and control group. Three instruments – designed by the researchers – that include: (listening comprehension skills checklist, listening comprehension skills test and listening motivation scale) were used. Results showed that the regular method used to teach listening is not as significant as the shadow reading strategy that developed listening comprehension skills and motivation. Consequently, the experimental group students outperformed their counterparts (the control group) in listening comprehension skills and motivation scores.
Malaria Parasite Detection using Deep Learning in Thick Blood Smears

Detection of malaria disease is done by finding the presence of malaria parasite or plasmodium in blood smear. Here malaria parasites are detected in thick blood smears. This paper proposes a version to detect the presence of malaria parasite(plasmodium) in thick blood smears automatically with the help of deep learning and not using microscopy examinations and chemical tests. This detection will be done using two steps, that is, intensity-based screening which is the preprocessing step, the first step, that extracts candidates for processing, and next is customized convolutional neural network (CNN), the processing step, which takes the preprocessed images and detects whether malaria parasite is present or not. Hold-out(3:1) technique is used for evaluation of the model. The model has achieved an accuracy reaching 91%. The two preprocessing and processing steps improves object detection of the system. Malaria is usually detected using chemical tests and microscopy examinations. This process requires a lot of resources mainly laboratories. Parasitologists who are experienced are sometimes difficult to find, so manually counting the malaria parasites can be prone to major errors. Due to which the cost for testing and even time for malaria diagnosis increases drastically. Since the traditional process of malaria parasite in blood smears detection has many drawbacks it needs a sophisticated, accurate diagnosing equipment or system which has low cost. This system can be used in regions and areas where there are constraints on resources, time of people and cost which they can afford. This system provides many advantages to rural diagnostic centres where the supplies are limited and not easily accessible.
Big Data Special Mining of Jiaojia Gold District for Deep Targeting( China)

The deposit-and district-scale three-dimensional (3D) models for deep targeting were constructed, based on multiple-scale geosciences big data including geology maps and drillholes and channels with assay and geophysics of gravity and magnetic and MT images additional several sesmic images and rock-type geochemical assay and high spectral data in the Jiaojia gold district.This study presents a combination of 3D geometric reconstructions of the Xincheng gold deposit and the Jiaojia gold district in China.Our intention is to demonstrate that these computer-based applications represent an innovative approach for metallogenic modeling, exploration criteria definition, and mineral potential targeting using multi-scale and multi-source geoscience big data in 3D space.The methodology are summaried as follows:(1) 3D geological model constructing and reconstructing using multi-scale and multi-source geosciences to respect predefined constraints to obtain the required accuracy and enable detailed integration of big data.In this study, we exploited the benefit of a geology-constrained 3D model using GOCAD and GeoCube2.0 to mimic ore genesis issues by using exploration drillhole and mining channel datasets.(2)The faults of ore-bearing structure analysis using 3D multi-source geological modeling and a numerical simulation was implemented in the Jiaojia gold district, China.(3) A Clustering modeling method was used to identify the samples geoscience features of geochemical and rock-type high spectram and the other features including geophysical physics in 3D space, and it can be used to delineate the goldforming path and trap using mineral system thoery,for example, the hydrothemal genesis of Jiaojia gold district additional fault structure constrain using 3D geological block cell model.(4) Newly developed geostatistical interpolation algorithms enable reconstruction of deposit-scale attributes at high resolution 3D space environment: such that the 3D grade modeling using SGS simulation modeling becomes not just a mineral resource definition tool but also a scientific tool for examining ore genesis and exploration targeting criteria; the alterated rocks modeling using SIS simulation modeling to analyze and identify metallogenic model of exploraiton criteria and exploration model using highspectal dataset with drillhole samples.
OBWD: an ontology and Bayesian network-based workflow design platform

Workflow management provides a great convenience for the cooperation between different roles in modern industry and business. The task reuse and design automation are challenges of workflow management currently. In this paper, an ontology SDWMO is constructed for workflow resources integration and task request release. An algorithm DOMDM is proposed to achieve the conversion of the data from traditional workflow data base to SDWMO ontology. In order to provide workflow templates for designers, we extract statistic-oriented cases from the workflow database. Based on these cases a Bayesian network is established for workflow template recommendation. We have designed OBWD platform to implement the above methods. The experimental data indicates that OBWD is statistically effective and saves a lot of time for workflow designers. Currently, OBWD has been used in space debris mitigation domain for workflow management. Moreover, our methodology can also be applied in many other domains in the future.
From Index to Network: Topic Maps in the Enhanced Networked Monographs Project

The Enhanced Networked Monographs (ENM) project was an experimental publishing project funded by The Andrew W. Mellon Foundation and carried out from 2015-2018. Over the course of the project, we developed methods to extract topics from indexes, built tools to curate the result of the integration, and created a platform for reading. This article will discuss the creation of the ENM topic map, a meta-index created by combining many individual back-of-book indexes using the Topic Curation Toolkit.
Turning air into drinking water

According to the United Nations, more than two billion people are living in countries experiencing high water stress. However, an Israeli company has developed technology which uses humidity in the air to create clean drinking water, potentially making fresh water accessible worldwide.
A URANIUM ATLAS IN ASCII FORMAT, 20000&amp;nbsp;-&amp;nbsp;27000 cm&lt;sup&gt;&amp;#8722;1&lt;/sup&gt;

We offer a U/Ar emission spectrum in ascii format, fully compaHble with older atlases, as a possible aid to calibraHon in the near UV.§ Weak peaks omiMed from earlier atlas line-lists can now be incorporated if necessary.
Instrument Design for The Furies: A LaptOpera

In this article, we discuss the creation of The Furies: A LaptOpera, a new opera for laptop orchestra and live vocal soloists that tells the story of the Greek tragedy Electra. We outline the principles that guided our instrument design with the aim of forging direct and visceral connections between the music, the narrative, and the relationship between characters in ways we can simultaneously hear, see, and feel. Through detailed case studies of three instrumentsâThe Rope and BeatPlayer, the tether chorus, and the autonomous speaker orchestraâthis paper offers tools and reflections to guide instrument-building in service of narrative-based works through a unified multimedia art form.
Readability Techniques for Authors and Editors

Pointing out the advantages of readability research studies in a publications program, the writer stresses the importance of such knowledge to achieve optimum results. From a personal review of journalism courses, and a survey of editors in various communication programs, writer notes a considerable lack of knowledge of readability research among communicators. The discussion will show how the relationship of author-to-editor can produce an environment of growth for the reader if both are cognizant of how to serve the reader. Research studies have been conducted with various devices and methods and, in some cases, electronic scanners are used to record the movement of eyes when a subject begins a reading session. Assigning the priority to text in a publication provides another means to capitalize on reader responses. Most of the applications have been directed to the formal technical report, a publication in which continuous reading is both voluntary and required in work assignments by technicians and scientists in a company.
Usage of E-resources in Libraries of Selected Health and Family Welfare Institutes in India: a case study

Health sector is the largest discipline in the world and relates to all human beings. Hundreds of inventions and research are being carried out by the national and international organizations and scholars on minor to major areas of health sciences for well-being. Several estimates have pointed out that around 30,000 journals are published every year and more than 1000 articles are published per day worldwide in printed and electronic formats. Digital technology has enabled accessibility to the resources to be easy, speedy, and comfortable on 24×7 basis. This article discusses a study pertaining to the satisfaction level about the selected e-resources available in open domain and subscribed e-resources used by the users in the libraries of selected health and family welfare institutions in India.
NMT Multi-Sense Embeddings per Word

Recently, word embeddings have been used in many natural language processing problems successfully and how to train a robust and accurate word embedding system efficiently is a popular research area. Since many, if not all, words have more than one sense, it is necessary to learn vectors for all senses of word separately. Therefore, in this project, we have explored two multi-sense word embedding models, including Multi-Sense Skip-gram (MSSG) model and Non-parametric Multi-sense Skip Gram model (NP-MSSG). Furthermore, we propose an extension of the Multi-Sense Skip-gram model called Incremental Multi-Sense Skip-gram (IMSSG) model which could learn the vectors of all senses per word incrementally. We evaluate all the systems on word similarity task and show that IMSSG is better than the other models.
Arrays

What is an array? An array is one or more data objects of the same type positioned next to each other in memory. The array itself is also a type.
Causal Influence

This chapter argues that the reductive method of explanation assumes an ontology of causal powers that manifest invariant causal influence. The reductive method takes what we know about how systems behave in one situation (typically a situation of relative isolation), and apply that knowledge to explain or predict the behaviour of the system in another situation (such as when it is a part of a more complex system). If this method is to work, then there must be something that remains constant from one situation to another in a way that supports the method. It is shown that standard ontologies do not contain anything that can fulfil this role. It is then shown that a relatively novel kind of entity, dubbed ‘causal influence’, can do the job.
Chapter 13: Density-Based Clustering Algorithms

The density-based clustering approach is a methodology that is capable of finding arbitrarily shaped clusters, where clusters are defined as dense regions separated by low-density regions. A density-based algorithm needs only one scan of the original data set and can handle noise. The number of clusters is not required, since density-based clustering algorithms can automatically detect the clusters, along with the natural number of clusters (El-Sonbaty et al., 2004).
Exploiting better motion cues for better action recognition

Several recent studies on action recognition have emphasised the significance of including motioncharacteristics clearly in the video description. This work shows that properly partitioning visualmotion into dominant and residual motions enhances action recognition algorithms greatly, both interms of extracting space-time trajectories and computing descriptors. Then, using differentialmotion scalar variables, divergence, curl, and shear characteristics, we create a new motiondescriptor, the DCS descriptor. It adds to the results by capturing additional information on localmotion patterns. Finally, adopting the recently proposed VLAD coding technique in image retrievalimproves action recognition significantly. On three difficult datasets, namely Hollywood 2,HMDB51, and Olympic Sports, our three additions are complementary and lead to beat all reportedresults by a large margin.
An Enhanced Technique for Analyzing Sentiments of Public Reviews - II

Enhnaced Dual Sentiment Analysis (EDSA) is an improved system which enhances the performance of the existing Dual Sentiment Analysis (DSA) which is implemented in literature. It mainly focuses on improving the efficiency of the existing system by making some modifications to the existing DSA approach. EDSA improves the classification accuracy of the public reviews. Apart from the classification accuracy other parameters considered in EDSA are precision, recall and fmeasure. In the first phase, a data pre-processing is performed to clean the data where subjectivity analysis is performed to obtain the subjective reviews and sentiment analysis is performed on subjective reviews only. Second phase deals with negation detection and sentiment word sreversal to obtain the reversed reviews. Third phase performs polarity calculation on the original and reversed reviews to obtain positive and negative reviews based on sentiment score of the reviews. Fourth phase performs the enhanced dual training and prediction where the positive and negative reviews are provided to various classifiers which provides the final results as the output. Final phase is the graphical representation of the various parameter values obtained from the previous phase which helps in comparing the results of the various classifiers.
An Evaluation of Blockchain-Based Technologies in the Food Supply Chain.

Beyond the financial sector, the use of blockchain in supply chain traceability is extremely important, although the tradeoffs between implementation difficulties and attainable effect are uncertain. Six components of blockchain-based technologies in the food supply chain were examined in this research using a technology elvaluation methodology that differentiates between six distinct components of a technology: technique, knowledge, organization, innovation, environment and product. The research aims to offer fresh crucial insights into how blockchain-based technologies may be applied in the food supply chain, as well as to further the debate on blockchain-based technologies' social and environmental implications. The findings show that blockchain is not a stand-alone technology, but rather one component in a larger system of technologies. While blockchain-based technologies are anticipated to have a wide range of effects, only a few are directly related to the blockchain: Change management and external pressure, Complexity of integrating different systems, Lack of knowledge and expertise, high investment are the impediment and constraints affecting full adoption of block chain based technologies. More study is required to establish if blockchain-based technologies enhance the sustainability of agricultural supply chains as anticipated. Keywords: Micropolar-Casson fluid; Magnetohydrodynamic, Variable viscosity; Variable thermal conductivity; Viscous dissipation
Application of STEM in Higher Vocational Education Curriculum

This paper integrates the core concept of STEM education into the teaching reform and curriculum design of higher vocational education. It has carried out bold reforms in the original progressive and progressive education mode of higher vocational education, and proposed a kind of the curriculum division according to disciplines is divided into the curriculum design concepts of higher vocational education courses according to typical work tasks. In the design of higher vocational courses, the courses are taught according to the requirements of how to comprehensively apply the knowledge and skills of various subjects to solve the typical tasks. Design a pattern, comprehensively integrate the original scattered knowledge points into the higher vocational curriculum, improve students' learning efficiency and learning enthusiasm, and save teaching resources for the society.
Imprint: Geomechanics and Tunneling 3/2021

Geomechanics and TunnellingVolume 14, Issue 3 p. 315-315 ImprintFree Access Imprint: Geomechanics and Tunneling 3/2021 First published: 11 June 2021 https://doi.org/10.1002/geot.202170309AboutPDF 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 No abstract is available for this article. Volume14, Issue3June 2021Pages 315-315 RelatedInformation
A Novel Human Parsing Method Enhanced by Cross-Refinement

The existing human parsing methods lead to some semantic errors and incomplete semantic recognition.To solve this two problems, we design a novel approach, called Cross Refinement Network (CRN).It is built based on the Part Grouping Network (PGN).The CRN remains the same as the PGN in the backbone network and the final refinement block, and uses the ResNet-101 and the Refinement branch separately, just like the PGN.Compared to the PGN, CRN innovatively utilizes the atrous convolution to map the last three feature modules of the backbone network into the feature space, and proposes the cross-refinement module, which consists of the semantic segmentation refinement branch and the edge detection refinement branch, to cross-merge the output feature maps.Experiments are performed based on Crowd Instance-level Human Parsing(CIHP), Pascal-Person-Part (PPP), and LIP datasets separately.The results show that our method outperforms the typical methods on the task of human parsing.
A STUDY OF SCRAMBLE METHOD IN TEACHING ENGLISH FOR SECONDARY STUDENT’S WRITING SKILL

In Indonesia secondary school, students are equipped with any English subject to arrange their own writing. In this case, writing is the one of difficult English skill for students. Because of that, to increase students writing skill teacher need a certain method in teaching writing. Based on student’s ability in writing that also suitable with their grades, they were difficult to arrange the sentence to be good paragraph. To solve these problem several teachers had applied a method that called scramble sentence method. This study used qualitative research method with concept analysis method or library research. The data of this study came from eight articles related about scramble method to secondary student’s writing skill. Data had analyzed from reading, reviewing, supporting and contra journal article and concluding. As the result, according to eight articles, the researcher found that scramble method was effective to increased student’s writing skill. Based on the implementation of each articles, scramble method helped students to write. It proven by the improvement of several writing aspects, such as topic sentence, supporting sentence, coherence, organization, generic structures, grammar, vocabulary, content, discourse, syntax, mechanic and language use. From the analysis, the research question of this study had answered.&#x0D; Keyword : Scramble method, writing, library research
"In These Uncertain Times"

This issue of School Libraries Worldwide is based on “the basics.” At the time that the call for papers was released, I never could have envisioned the Covid-19 pandemic and the extreme circumstances school librarians and their communities are experiencing. True to form, school librarians throughout the world responded as they always do: center on the basics of meeting our users’ needs.
Build Your E‐Mail List

Special Events GaloreVolume 21, Issue 2 p. 7-7 Articles Build Your E-Mail List First published: 12 January 2021 https://doi.org/10.1002/speg.31529Read the full textAboutPDF 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. Volume21, Issue2February 2021Pages 7-7 RelatedInformation
An efficient data masking method for encrypted 3D mesh model

The industrial 3D mesh model (3DMM) plays a significant part in engineering and computer aided designing field. Thus, protecting copyright of 3DMM is one of the major research problems that require significant attention. Further, the industries started outsourcing its 3DMM to cloud computing (CC) environment. For preserving privacy, the 3DMM are encrypted and stored on cloud computing environment. Thus, building efficient data masking of encrypted 3DMM is considered to be efficient solution for masking information of 3DMM. First, using the secret key, the original 3DMM is encrypted. Second without procuring any prior information of original 3DMM it is conceivable mask information on encrypted 3D mesh models. Third, the original 3DMM are reconstructed by extracting masked information. The existing masking methods are not efficient in providing high information masking capacity in reversible manner and are not robust. For overcoming research issues, this work models an efficient data masking (EDM) method that is reversible nature. Experiment outcome shows the EDM for 3DMM attain better performance in terms of peak signal-to-noise ratio (PSNR) and root mean squared error (RMSE) over existing data masking methods. Thus, the EDM model brings good tradeoffs between achieving high data masking capacity with good reconstruction quality of 3DMM.
A method of value measurement based on conditional probability theory

Abstract Value is one of the most fundamental concepts in economics. The existing main definitions of value have certain limitations and are difficult to be unified and quantified. Thus, this article presents a method of quantifying value based on the conditional probability theory; we set value as a random variable, and thus uses conditional probability distribution to measure value. Furthermore, the mean and variance of random variables are used to describe the weighted average of the possible values and the dispersion of values distribution. This method provides a new perspective for the measurement of value.