Reviewerly/exHarmony huggingface dataset:
THE COMPARISON OF USING PARAGRAPH FRAME AND SENTENCE COMBINING STRATEGIES TO IMPROVE THE SEVENTH GRADE STUDENTS’ WRITING SKILL AT SMPN 33 PALEMBANG

The objective of this study was to find out whether or not there was any significant improvement on students’ writing skill between students who used paragraph frame strategy and those who used sentence combining strategy of the seventh grade students at SMPN 33 of Palembang. The research method was quasi-experimental method. The design of this study was non-equivalent control group design. The technique for collecting the data was the test. The population of this study was all Seventh Grade Students of SMPN 33 of Palembang, and the sample of this study was VII.1 and VII.2. The experimental group had 33 students; meanwhile, control group had 35 students. The data were collected by giving pretest, treatment and post-test for both groups. The data were analyzed by using independent and paired sample t-test. The result of the data analysis showed that the mean score of post-test of experimental group was 81.36 and post-test of control group was 63.14. Furthermore, it shows that the value of sig, (2-tailed) was 0.00 and it was lower than 0.05 as the significant level. The value of t-obtained was 4.809 which was higher than t-table critical value of 1.996 and the degree of freedom was 66. Based on the result of data analysis, It can be concluded that there was any significant improvement on students’ writing skill between students who used paragraph frame strategy and those who used sentence combining strategy. Keywords: paragraph frame strategy, sentence combining strategy, writing skill.
Evaluation of universities’ intellectual capital influence on the intellectual capital of the regions of their location

The paper presents the study’s results, which allow to reveal the role and importance of universities’ intellectual capital in the formation of a comprehensive assessment of the indicators of regional intellectual capital. Based on the study of theoretical materials and methods on the problems of intellectual capital of universities and regions, systems of indicators of their evaluation were composed. Hypotheses about the mutual influence of the intellectual capital of the region and universities, as well as their individual elements were put forward. As a result of hypothesis testing, based on the results of correlation-regression analysis, hypotheses about the influence of the universities’ intellectual capital as well as their individual elements (human and reputational capital) on the regions’ intellectual capital, as well as the influence of the universities’ intellectual capital on regions’ human capital were confirmed with an above-average level.
Efficient Large Scale Frequent Itemset Mining with Hybrid Partitioning Approach

In today’s world, voluminous data are available which are generated from various sources in various forms. Mining or analyzing this large scale data in an efficient way so as to make them useful for the mankind is difficult with the existing approaches. Frequent itemset mining is one such technique used for analyzing in many fields like finance, health care system where the main focus is gathering frequent patterns and grouping them to be meaningful inorder to gather useful insights from the data. Some major applications include customer segmentation in marketing, shopping cart analyses, management relationship, web usage mining, player tracking and so on. Many parallel algorithms, like Dist-Eclat Algorithm, Big FIM algorithm are available to perform large scale Frequent itemset mining. In Dist-Eclat algorithm, datasets are partitioned using Round Robin technique which uses a hybrid partitioning approach, which can improve the overall efficiency of the system. The system works as follows: Initially the data collected are distributed by mapreduce. Then the local frequent k-itmesets are computed using FP-Tree and sent to the map phase. Later the mining results are combined to the center node. Finally, global frequent itemsets are gathered by mapreduce. The proposed system is expected to improve in efficiency by using hybrid partitioning approach in the datasets based on the identification of frequent items.
comparatives study of steganography and steganalysis tools

Steganography is one of the oldest methods of secure communication. It was an art at the beginning, now became a science. It aims to conceal secret messages or data inside an innocent cover. Steganalysis is the science that can detect and extract hidden data. Many steganography and steganalysis tools exist, a lot of them are free which makes it easy for anyone to use these tools. In this paper, a comparative study will be done between two widely used steganography tools (StegHide and OurSecret) and between three steganalysis tools StegSpy, StegSecret and Hidden data detector.
Temporal Logic and Selection in the Sleeping Beauty Problem

The Sleeping Beauty Problem is a polarizing thought experiment involving a fair coin toss, memory erasure and temporal uncertainty. Despite its simplicity there is no agreed upon solution. In this work I put forward a set of arguments that support the so-called Halfer or 1/2 solution to the problem, while undermining the competing Thirder or 1/3 solution. In analyzing Elga’s original argument for the 1/3 solution, I bring to light a subtle but clear contradiction in his reasoning using temporal logic. Temporal reasoning also helps to neutralize the main criticisms against the 1/2 solution. Surprisingly, for some questions of probability or credence, it appears we need to distinguish between an event that has yet to occur, and the same event after it has already occurred. Knowledge that an event has been decided (without knowing the result) can be a type of admissible evidence when updating credences.
I think I already added you ...

I think I already added you to it from @dogtrax list. I will put up a link to the Google Form on the Planet
Document tamper detection and verification using MD5 hashing algorithm and digital signature approach for online construction bidding System.

In an online bidding system the bidder bid for the best deal. The documents shared are in electronic format and that leaves lot of scope for document tampering. Electronic files are typically shared by disc or download link using the honour system. Once these files have been dispersed, anyone can modify the contents to fit their narrative, and then distribute that version as an official exhibit. Such changes can be difficult or impossible to trace to their source due to the number of people with access to the files. To prevent this we will use MD5 with Digital Signature Standardization algorithm. We can identify each file by its unique Hash value and then use that identifier to ensure file integrity once file sharing has begun. In this system MD5(Message Digest 5) algorithm is used as a cryptographic hash function. MD5 hash is composed of 32 hexadecimal characters. Along with this digital signature approach(Digital Signature Standardization Algorithm) is used for verification Based on hash value calculations at sender and receiver side conclusion can be drawn whether document has been tampered with or not.
FAKE NEWS PREVENTION AS THE EDUCATIONAL PROGRAM

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 7074-7080ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.1713Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
A Novel Approach for Mitigating Atmospheric Turbulence using Weighted Average Sobolev Gradient and Laplacian

Heat scintillation mainly leads to atmospheric turbulence which causes the image distortion due to the propagation of light through the volatile environment. The change in the refractive index due to variation in wind velocity is also the reason for causing turbulence in the atmosphere. Traditional image registration approach lags as it is computationally expensive and need post-processing algorithm for sharpening the image. A non-registration-based Sobolev gradient and Laplacian (SGL) algorithm removes turbulence but results in ghost artifacts in moving objects. This paper proposes a novel approach based on weighted average SGL. The proposed method mitigates atmospheric turbulence as well as restores the moving object in the scene. Performance metrics like SSIM and MSE prove that the proposed algorithm outperforms the state of the art algorithms in terms of restoring the geometric distortion as well as the object of interest.
Exploring the Practice of ''College, Government, Association, Research and Enterprise'' Collaborative Education Mode from the Perspective of Supply Side Reform - A Case Study of the Applied Chemistry Major of Yancheng Teachers University

At present, the training of engineering talents in higher education needs to carry out supply-side reform to solve the disconnection between the demand for social talents and the cultivation of talents in universities, and the phenomenon that there is a mismatch between the students' employment needs and the curriculum system of colleges and universities.The ''College, Government, Association, Research and Enterprise'' (CGARE) Collaborative Education Mode has been built to improve the quality of applied talents in the applied chemistry major of Yancheng Teachers University for nearly 10 years.Based on the "student-oriented" education concept, the collaboration of college, government, association, research and enterprise was taken as a breakthrough and the enterprise technology demand was taken as the carrier to improve the engineering practice ability and innovation and entrepreneurship ability of college students, and fully meet the needs of society and enterprises for high-quality talents in the CGARE collaborative education mode.The quality of applied talents has been improved significantly through the CGARE collaborative education mode.High-level achievements of the students of the applied chemistry major of Yancheng Teachers University are fruitful.The innovative and entrepreneurial ability and their professional self-confidence of the students have been greatly enhanced.Thus, the quality of student employments is high, and given high marks by the internship unit and employer.
Practical and technical suitability perceptions of sound sources and test signals used in room acoustic testing

High intensity and accurate test signals are required to be produced by sound sources for acoustic characterisation and evaluation of indoor spaces. A variety of modern room excitation test signals, sources and processing methods (systems) exist and their suitability for most purposes is well documented in the literature. Those test systems are firmly established and employed in academia and research applications due to their accuracy and reliability; despite requiring sophisticated, expensive and bulky equipment which needs electrical power. More convenient and traditional impulsive test signals and sources are widely used in the acoustic industry as an alternative to modern system mainly due to their low cost and practicality merits. However these alternatives are not as robust or as well documented. This paper reports on a preliminary attitude survey regarding perceived technical and practical suitability of different systems used in academia and industry in the UK. A social survey asked acoustic consultancies, researchers and academics questions about usage, perceived accuracy and reliability of systems used. Results conclusively showed that some traditional systems are widely used and favoured due to their practicality and convenience despite the acknowledged lack of robustness. A proposed novel all-round system addressing most of the technical and practical merits would be welcomed and adopted by the industry
Joseph Krauskopf Memorial Library: Help Desk and Technology: Residence Halls

Delaware Valley University technology and help desk services. Tech Services info for resident students.
SAMR: A Tool for Reflection for Ed Tech Integration

Technology is a part of everyday life as digital tools and devices are ubiquitous.  As schools begin to increase technology available in the classroom, it is important for teachers to consider when, how, and why technology fits into a lesson.  Used properly, technology is a powerful tool that can transform teaching and learning.  It can be a means for collaboration, accessibility, personalization, differentiation, engagement, and innovation (US Department of Education, 2016). Technology should never be considered the classroom “babysitter” or the busy workstation.  Rather, technology is used intentionally and strategically as a tool to allow students to engage meaningfully in authentic learning experiences (Herrington & Kervin, 2007).
Selling and lending e-books : Changes in the Swedish literary field

This study explores the actors distributing e-books in the Swedish book market. The focus was on public libraries and booksellers, which included aggregators, subscription services, online booksell ...
Disclosable Restructuring Paper - Strengthening Evidence-Based Policymaking with Education Statistics and Analysis - P161312

The development objectives of Strengthening Evidence-Based Policymaking with Education Statistics and Analysis Project is to strengthen the capacity of Ukrainian education authorities to utilize administrative, statistical, and learning assessment data and analytical methods to inform policymaking. This restructuring requires the following changes: (i) extension of closing dates by six months from January 24, 2019 to July 24, 2019; ii) revise the project development objectives (PDO) indicator related to training of specialists on using programme for international student assessment (PISA) 2018 data to prepare the national analytical report; and (iii) change the distribution of financial resources among cost categories.
Learning and Investigating a Style-Free Representation for Fast, Flexible, and High-Quality Neural Style Transfer

Author(s): Zhang, Chi | Advisor(s): Zhu, Song-Chun | Abstract: We have just witnessed an unprecedented booming in the research area of artistic style transfer ever since Gatys et. al. introduced the neural method. One of the remaining challenges is to balance a trade-off among three critical aspects---speed, flexibility, and quality: (i) the vanilla optimization-based algorithm produces impressive results for arbitrary styles, but is unsatisfyingly slow due to its iterative nature, (ii) the fast approximation methods based on feed-forward neural networks generate satisfactory artistic effects but bound to only a limited number of styles, and (iii) feature-matching methods like AdaIN achieve arbitrary style transfer in a real-time manner but at a cost of the compromised quality. We find it considerably difficult to balance the trade-off well by merely using a single feed-forward step and ask, instead, whether there exists an algorithm that could adapt quickly to any style, while the adapted model maintains high efficiency and good image quality. Motivated by this idea, we propose a novel method, coined MetaStyle, which formulates the neural style transfer as a bilevel optimization problem and combines learning with only a few post-processing update steps to adapt to a fast approximation model. The qualitative and quantitative analysis in the experiments demonstrates that the proposed approach achieves high-quality arbitrary artistic style transfer effectively, with a good trade-off among speed, flexibility, and quality. We also investigate the style-free representation learned by MetaStyle. Apart from style interpolation and video style transfer, we also implement well-known style transfer methods and examine the style transfer results after substituting the original content image inputs with their style-free representation learned by MetaStyle. This could be thought of as inserting a preprocessing step to the content transformation branch. We show in the experiments that models trained using the MetaStyle preprocessing step produce consistently lower style loss and total loss, with a slightly higher content loss, compared to its counterparts without MetaStyle processing. And therefore, the stylized results achieve a better balance in appropriately combining semantics and styles. This shows that MetaStyle also learns a more general content representation in terms of adapting different artistic styles.
Generalized Interval Valued Nonnegative Matrix Factorization

In this paper, we propose a probabilistic model for analyzing the generalized interval valued matrix, a matrix that has scalar valued elements and bounded/unbounded interval valued elements. We derive a majorization minimization algorithm for parameter estimation and prove that the objective function is monotonically decreasing by the parameter update. An experiment shows that the proposed model well handles interval- valued elements and offers improved performance.
MOTIVATIONAL AND COGNITIVE CRITERIA TO REALIZE THE INNOVATIVE POTENTIAL OF THE EDUCATIONAL ESTABLISHMENT TEACHING STAFF

MOTIVATIONAL AND COGNITIVE CRITERIA TO REALIZE THE INNOVATIVE POTENTIAL OF THE EDUCATIONAL ESTABLISHMENT TEACHING STAFF
THE ADVANTAGES OF ONLINE TESTING IN LATVIAN GENERAL EDUCATION SCHOOLS

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 3001-3008ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0791Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
ИСПОЛЬЗОВАНИЕ АВТОМАТИЗИРОВАННОЙ ИНФОРМАЦИОННОЙ СИСТЕМЫ «СЕТЕВОЙ РЕГИОН. ОБРАЗОВАНИЕ» В ХОДЕ ПОВЫШЕНИЯ КВАЛИФИКАЦИИ УЧИТЕЛЕЙ

The automated information system Network region. Education and its possibilities are considered in the article. It is shown that the systematic use of an automated information system to solve educational, cognitive and professional tasks contributes to the improvement of self-education and the qualifications of teachers in the application of information and communication technologies.
LibGuides: Sources Types (Popular, Scholarly, Authoritative): Home

Source types exist on a spectrum. Learn about this spectrum and how to determine where yours fall.
PO 8584 MULTIPLEXED MOLECULAR DETECTION OF MALARIA IN SIERRA LEONE

Background Despite several control measures and policy changes in Africa, malaria remains one of the most prevalent diseases in West Africa. The gold standard for malaria diagnosis is microscopy. However, due to low technical capacities in resource-poor countries, rapid immunochromatographic tests are commonly used. In Sierra Leone, P. falciparum -specific ICT with histidine-rich proteins2(HRP-2) are used. HRP2 is specific to P. falciparum and the kit cannot be used to detect other species of malaria which are also present in the disease ecology in Sierra Leone. Methods In this study, we assessed 182 febrile subjects for malaria between April 2017-July 2018 at the Mercy Hospital Research Laboratory in Sierra Leone. The blood samples collected were assessed using the Walter Reed Army Institute for Research(WRAIR) multiplex malaria PCR kit packaged by BioGX, Inc. (Alabama, USA) for detecting and speciation of malaria from human blood. Thin and thick slides were done for each sample and the images recorded by a digital scope. Results Results show that, out of 163 samples run by multiplex PCR for malaria, 81 (49.7%) were positive for P. falciparum , while 82 (50.3%) were positive for Plasmodium vivax . Conclusion The presence of P. vivax in the disease ecology without any significant difference (p&gt;0.05) with P. falciparum poses problems for clinical outcomes of febrile illnesses. Pan-malaria diagnostics in combination with P. falciparum could avert under-diagnosis of malaria.
Pre-School Educators Inspired by KINDY TALK- English for STEM CSR Workshop

Gambang - 3 November 2018 Due to tremendous response, KINDY TALK: English for STEM, that was supposed to be limited to only 30 participants, drew a crowd of forty pre-school educators at Tun Fatimah Hall, Universiti Malaysia Pahang (UMP), Gambang campus. The participants were mainly from Kuantan; some were from Pekan and some came from as far as Bera. The workshop emphasised on two key aspects with two hours focusing on motivation and another two hours on language.
Compiling for Encrypted Computing: Obfuscation but Not in Name

An `obfuscation' for encrypted computing is quantified exactly here, leading to an argument that security against polynomial-time attacks has been achieved for user data via the deliberately `chaotic' compilation required for security properties in that environment. Encrypted computing is the emerging science and technology of processors that take encrypted inputs to encrypted outputs via encrypted intermediate values (at nearly conventional speeds). The aim is to make user data in general-purpose computing secure against the operator and operating system as potential adversaries. A stumbling block has always been that memory addresses are data and good encryption means the encrypted value varies randomly, and that makes hitting any target in memory problematic without address decryption, yet decryption anywhere on the memory path would open up many easily exploitable vulnerabilities. This paper `solves (chaotic) compilation' for processors without address decryption, covering all of ANSI C while satisfying the required security properties and opening up the field for the standard software tool-chain and infrastructure. That produces the argument referred to above, which may also hold without encryption.
Non-monotonic Reasoning on the Web

In this tutorial we describe the approaches to non monotonic reasoning as a means for inference on the web. In particular we are focusing on the ways in which reasoning technologies have adapted to five different issues of the modern era world wide web: (a) epistemic aspects, bound by the new models of the social web, (b) changes over time, (c) language variants, including different languages of deployment of a web site, (d) agent-based knowledge deployment, due to social networks and blogs, (e) dialogue aspects, introduced again in blogs and social networks. The presentation covers these aspects by a technical viewpoint, including the introduction of specific knowledge-driven methods. The technical issues will be provided within a general logical framework known as defeasible logic.
Semi-supervised Cross-media Feature Learning via Efficient L2,q Norm

With the rapid growth of multimedia data, research on cross-media feature learning has significance in many applications, such as multimedia search and recommendation.Existing methods are sensitive to noise and edge information in multimedia data.In this paper, we propose a semi-supervised method for cross-media feature learning by means of L 2,q norm to improve the performance of cross-media retrieval, which is more robust and efficient than the previous ones.In our method, noise and edge information have less effect on the results of cross-media retrieval and the dynamic patch information of multimedia data is employed to increase the accuracy of cross-media retrieval.Our method can reduce the interference of noise and edge information and achieve fast convergence.Extensive experiments on the XMedia dataset illustrate that our method has better performance than the state-of-the-art methods.