Reviewerly/exHarmony huggingface dataset:
Argument Retrieval from Web

We are well beyond the days of expecting search engines to help us find documents containing the answer to a question or information about a query. We expect a search engine to help us in the decision-making process. Argument retrieval task in Touché Track at CLEF2020 has been defined to address this problem. The user is looking for information about several alternatives to make a choice between them. The search engine should retrieve opinionated documents containing comparisons between the alternatives rather than documents about one option or documents including personal opinions or no suggestion at all. In this paper, we discuss argument retrieval from web documents. In order to retrieve argumentative documents from the web, we use three features (PageRank scores, domains, argumentative classifier) and try to strike a balance between them. We evaluate the method based on three dimensions: relevance, argumentativeness, and trustworthiness. Since the labeled data and final results for Toucheé Track have not been out yet, the evaluation has been done by manually labeling documents for 5 queries.
Research on the Influence of Psychological Capital and Job Involvement of Knowledge Workers on Innovation Performance: The Moderating Effect of Job Autonomy

Purpose The purpose of this study is based on knowledge workers as the research object, in view of the knowledge staff psychological capital has an...
Exploratory factor analysis of the QMCA

This investigation is situated within an ongoing project which seeks to understand student thinking in upperdivision introductory quantum mechanics courses.Recently, the Quantum Mechanics Concept Assessment (QMCA) was revised to include additional items in spin-basis contexts to reflect the rising prevalence of the "spins-first" instructional paradigm.In this work, we utilize exploratory factor analysis to group items on the QMCA based on common variance.Student responses were collected from several large institutions over the 2018-2019 academic year, with the three largest institutions following a "spins-first" curriculum.In interpreting our factor structure, we focus on the placement of isomorphic questions and the original concept framework of the QMCA, as well as a tentative interpretation of factor groupings.We conclude by discussing how these groupings may be further investigated, as well as implications for subsequent iterations of the QMCA and research on student thinking in these two contexts.
Hidden Markov Model-Based Walking Direction Improvement in PDR System for Multiple Poses of Smartphone

In this paper, we propose a solution for mismatching between the walking direction and device heading in a PDR (Pedestrian Dead Reckoning) system using a smartphone and the HMM (Hidden Markov Model). The PA Parametric Approach)-based PDR system consists of step detection, step length estimation, and heading estimation. In general, the device heading is regarded as the walking direction, but device heading and walking direction are sometimes mismatched due to the smartphone user assuming various poses. In these cases, the PA-based PDR produces an position error from the mismatched angle. The solution proposed in this paper is an IA(Integration Approach)-based PDR system and a walking direction estimation method using HMM. The IA-based PDR system estimates the position by integrating the acceleration twice. To correct the error produced by this system, the travel distance and the walking direction are used as measurements, and are obtained from the step length model of PA and walking direction from HMM, respectively. Through experiments, it is shown that the performance of the proposed algorithm can overcome the limitations of existing smartphone-based algorithms.
Geochemical evaluation pollution for some heavy metals in basra soil

The present study included determine concentrations of certain heavy metals (lead, cadmium, cobalt, copper, zinc, nickel, iron and manganese) of surface soils in selected areas of North, South and west of Basra governorate consisted of four seasons from autumn 2013 to summer 2014 by using Flame atomic absorption spectrum.The seasonal variation of these elements range from lowest value (1.80µg/g) for cadmium in winter and the highest value (13033.18µg/g)for iron in the summer.Total organic carbon TOC% and grain size analysis where also determined and there is not correlation between them, these factors suggesting that working in high concentrations of certain heavy elements in Basra than in natural soils is pollution from human activities.Geochemical index (Igeo) where also determined that average concentration ranged from less value (3.32) for cadmium and the highest value (18.81) for iron.While the Enrichment factor (EF) range from less value (0.0005) for manganese and highest value (0.414) for cadmium.Finally Contamination factor (CF) range from less value (0.46) for zinc and the highest value (223.21) for
The Efficiency of Medical Volume Data Processing Using Virtual Reality

The paper shows pilot studies aimed at examining the effectiveness of volumetric data processing in a virtual environment compared to standard solution. The speed and accuracy of the users' actions in the environments were analyzed.
Quantum computing with 20 photons in 60 modes

We resonantly excite a single quantum dot coupled to a polarized microcavity to create single photons with high efficiency, purity, and indistinguishability simultaneously. We inject 20 photons into a 60-mode interferometer to perform boson sampling at a Hilbert space size of 10×14.
Library Guides: SU Libraries Riddle of the Month: July's Riddle

A guide to support the SU Libraries Riddle of the Month, as seen on Facebook, Twitter, and Instagram.
Reversible Data Hiding using Prediction Error Adoption

Reversible data hiding in encrypted images is a technique that embedded additional data into an encrypted image without accessing the content of the original image, the embedded data can be extracted and the encrypted image can be recovered to the original one. In this work, two reversible data hiding methods in encrypted images, namely a joint method and a separable method, are introduced by adopting prediction error. In this paper, we propose joint and separable RDH techniques using an improved embedding pattern and a new measurement function in encrypted images with a high payload. The first problem in recent joint data hiding is that the encrypted image is divided into blocks, and the spatial correlation in the block cannot fully reflect the smoothness of a natural image. The second problem is that half embedding is used to embed data and the prediction error is exploited to calculate the smoothness, which also fails to give good performance  In the joint method, data extraction and image reconstruction are performed at the same time. The reversibility, number of incorrect extracted bits are significantly improved while maintaining good visual quality of recovered image, especially when embedding rate is high. In the separable method, data extraction and image recovery are separated. The separable method also provides improved reversibility and good visual quality of recovered image for high payload embedding.
LibGuides: Elementary Resources: Diversity, Equity and Inclusion Resources

Books, articles, journals, and online resources geared towards teachers of exceptional learners.
Design of Noise Shaping Quantizers for Data Compaction of Neural Networks

This paper focuses on the quantization problem of connection weights of neural networks. Our previous work proposed a class of quantizers, called noise-shaping quantizer, for the quantization of neural networks. The performance of the proposed quantizer depends on the error diffusion filter. This paper proposes a systematic design method of error diffusion filters based on features of learning data, which is used for the learning of neural networks. In the proposed design method, satisfactory error diffusion filters are given by solving a kind of traveling salesman problems.
Chinese News Data Extraction System Based on Readability Algorithm

In this era of data explosion, the number of Chinese news has increased exponentially. We need an efficient way to collect data to support the data analysis industry or to meet the data needs of artificial intelligence domain model training. The purpose of this article is to build an efficient data extraction system for Chinese news data collection. First, we will introduce the development of the field of network data collection, review the previous research routes and ideas, then we choose the Readability algorithm to extract the text data, improve some of the rules, and add the consideration of text data sparsity to make it more suitable for Chinese news data. The system is based on the Scrapy framework to facilitate large-scale Crawling. By comparing the basic readability algorithm with the experimental results, the improved crawling system can extract Chinese news data more accurately and efficiently.
Bayesian optimization for selecting training and validation data for supervised machine learning

Validation and verification of supervised machine learning models is becoming increasingly important as their complexity and range of applications grows. This paper describes an extension to Bayesi ...
STRATEGI PENGEMBANGAN TEKNOLOGI INFORMASI PERPUSTAKAAN PERGURUAN TINGGI DI ERA MILENIUM (Studi Kasus di UPT Perpustakaan Universitas Sebelas Maret)

Library library users are included in the millennial generation category that is familiar with information technology. The library manages information sources in developing library information technology with user-based approval. Things that need to be developed in the development of information technology in libraries include: 1)Determining the development strategy 2). Done as a user base, 3). Library readiness and librarians in improving service quality, 4). Implement the results of development, 5) carry out continuous evaluations. Keywords: Library information technology, college library, Millennium Era
Enfoque práctico de la aplicación del Toolbox Deep Learning del Matlab en el reconocimiento facial de estudiantes

The purpose of this article was to provide a practical approach to the application of the Toolbox Deep Learning, from the Matlab software, for facial recognition of a group of students from the Mechatronics Engineering Program, at the Ricardo Palma University, Lima-Peru. To do this, the methodology used consisted of defining the architecture, configuration and training of a deep learning convolutional neural network, to extract the relevant data of facial features in the photographs taken of the group of students. The sample used was 426 photographs corresponding to 14 students; Likewise, different tests were carried out to select the most appropriate number of layers, the highest percentage of precision and the shortest training time. And, the best result corresponded to the use of two convolution layers, of 16 and 32 filters, respectively, with a precision percentage of 94.00% in the facial recognition of the group of students.
Capriccio for Wind Quintet in 3 Movements

Author(s): Gurvitch, Leon | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Methods for developing visualizations in a non-designer environment : A case study

Teams consisting of only software developers will occasionally need to develop products that has to be easy to use. User Centered Design (UCD) is one approach to help increase the ease of use of a ...
A Novel Clone Detection Scheme Based on Generative Adversarial Networks

Copy-move is one of the simple and effective operations to create digital image forgeries due to the gradually evolved image processing tools. In recent years, many studies were proposed by the literature to help restore some trust to digital images. In this paper, for the first time, we introduce a new end-to-end Generative Adversarial Networks (GAN) to the image copy-move forgery detection problem. Unlike classic solutions requiring carefully extracted features, the proposed solution only needs authentic and forge samples. Our experimental results demonstrate that the proposed method achieves better forgery detection performance than classic approaches relying on different features and/or Convolutional Neural Network (CNN).
О дискретных моделях колебательных систем

The algorithm of numerical integration of a task of Cauchy for the equations of the movement of nonlinear oscillatory systems is offered. Transformation of finite difference computing algorithms in objects of nonlinear dynamics in discrete time is shown.
Construcción de experiencias de aprendizaje en robótica educativa, para alumnos de secundaria basadas en gamificación e integración de tecnologías de la información y la comunicación

This article presents a proposal of learning experience aimed at students in their final years of secondary education, which integrates the use of different technological tools for the construction by students of their own robots, leaving aside the traditional assembly of pre-fabricated robots; this implies understanding the process of design and manufacture from concepts of geometry and kinematics, on the armed robots must incorporate the necessary electronics, which brings them closer to the fields of electricity, finally through programming achieve the desired behavior of the robot. A general incentive to achieve the same objective is the gamification of the process by generating a competition of speed or trajectory and then creativity between the different robots implemented.
Reset Attack: An Attack Against Homomorphic Encryption-Based Privacy-Preserving Deep Learning System

In some existing privacy-preserving deep learning systems, additively homomorphic encryption enables ciphertext computation across the gradients. Therefore, many learning participants can perform neural network-based deep learning over a combined dataset without revealing the participants’ local data to a central server. However, this privacy-preserving deep learning system is not secure against participant-level attack. We present an effective participant-level attack method against collaboration deep learning by uploading specific gradients to control the training process. With our method, even a single attacker can attack a learning task which is conducted by several participants. We implement our method and test it over the privacy-preserving learning framework. Considerable results show that this attack can greatly decrease the model accuracy.
Scaffolding the structure of organic chemistry students’ multivariate comparative mechanistic reasoning

Problem solving in all sciences requires the integration of multiple causal variables. Organic chemistry students often limit their reasoning about multivariate mechanism problems to single variables. To our knowledge, no teaching instrument that uses the structure of mechanistic reasoning to explicitly foster the consideration of multiple variables has been empirically evaluated to date. To fill this gap, we developed a scaffold based on findings in philosophy of organic chemistry and tested it in a qualitative interview setting. The scaffold provides a stepwise reasoning structure to compare the activation energy required for two different molecules to undergo the same type of mechanistic step. We found that the scaffold builds on what students already do when engaging in comparative mechanistic reasoning by themselves and supports their multivariate reasoning. The applicability of the structure of the scaffold in other contexts of mechanistic reasoning including physics is discussed.
Economic Growth Theories, And the Managing of Oil Curse; The Effect of Corruption

The paper discusses that Corruption, resources, private investment and economic growth are related. The inference is that the potential benefits of rising corruption in deeply authoritarian nations are practically greater than any other government intervention. Corruption awareness is essential in policy decisions that accelerate the policy platform. Emerging economies, notably the Middle East and North African countries with ample resources, can make a major contribution. further, the impact of corruption on the accumulation of human capital across two channels. It occurs on the first channel. It has the impact of corruption in public education spending and the second path. Corruption in spending on physical capital and investment. The paper argues that the pace of the reform initiatives is crucial and that the success of the policies is affected by corruption and affirms the existence effect in human resources and corruption.
GPRC Learning Commons: Evaluating News Sources : Newspapers at GPRC

Learn how to critically read and evaluate news sources. Discover some tips and tricks for identifying Fake News, propaganda, and bad information.
Efficient Identity-Based Signature Authentication Scheme for Smart Home System

The secure communication between users and devices is extremely important for Internet of Things (IoT) applications, if the communication between the two parties is not secure, user privacy and security will be threatened. So far, many solutions for secure communication between IoT devices have been proposed, but not all of them meet the security goals. Ashibani et al. proposed an identity-based signcryption scheme with message recover (IBS-MR) for smart home communications, they claimed that their solution not only provide effective authentication, but also ensure data integrity and confidentialty. But we find that it is not the case, their solution does not guarantee data integrity and is not resistant to replay attacks, in addition, it lacks formal security certification. Therefore, we propose a new identity-based signcryption scheme with message recover (IBS-MR) in smart home system to solve these problems, our scheme does not require hash-to-point operation and we prove our IBS-MR scheme secure in the random oracle model.
Subject guides: Scandinavian Studies: Databases

This guide provides a general introduction to Library and information resources for the study of Search tools, websites and gateways for Scandinavian studies. Databases
Research Guides: Training Resources: Using the UN Digital Library

A quick guide to point you to all the resources to help you navigate the UN Digital Library and make sense of the documents you are looking for.
They have a large barge with a radio antenna tower

Author(s): Filipsson, Faidon | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Board 79: Engineering Source: How Robust is the Coverage of the Engineering Literature?

Abstract Background: In June 2013, EBSCO launched Engineering Source, a new database that is touted as the “premier collection of engineering-related content” [1]. The authors encountered this database 5 years after it was released after moving to new institutions, and investigating the engineering resources available. Upon learning about the database, the authors asked a few engineering librarian colleagues, many of whom had also not heard of the database, and none had used it. Purpose: Given the claim of a premier collection and the lack of knowledge on the part of engineering librarians at flagship engineering schools, the authors decided to do a comparison of the indexing coverage of Engineering Source with Compendex. The goal is to determine how the breadth and depth of coverage in Engineering Source compares to the acknowledged top resource for engineering literature [3]. Scope and Method: The authors elected to use the method developed by Meier and Conkling [2] to compare relative coverage of Google Scholar with Compendex. In this case, the same searches will be completed in Compendex, and a random selection of articles from the results in Compendex will be searched for inclusion in Engineering Source. Results: The total number of results per subject were smaller for Engineering Source than for Compendex, which is expected just from considering the number of resources included in the databases, as outlined in the indexing scope. An apparent English language bias was found in the content that is indexed by Engineering Source. Conclusions: For very small schools offering selected engineering disciplines that match the strengths of Engineering Source, it could be a good resource. The inclusion of some full text would also be a strength for schools without the ability to purchase many of these publications. In addition, the ability to do searches across multiple databases on the EbscoHost platform could work really well if complementary information is already in an Ebsco database.
Avaliação de algoritmos de aprendizado de máquina aplicados à classificação de dados em nı́veis de confidencialidade

The correct definition of the access level for each available document in a business environment is challenging and flawed. These processes fall on procedures that are eithermanual or based on generic regular expressions. In this project, we propose an autonomous approach capable of classifying, in different degrees of confidentiality, the information contained in a real database of a financial institution. The approach includes theapplication of natural language processing techniques as well as different supervised andunsupervised learning algorithms. The proposal’s performance evaluation shows that theRandom Forest algorithm, associated with the bag of words vectorization of the contentin documents, presents a similar performance in the discrimination between the classesof confidentiality and total accuracy of 89.29%. The best vectorization technique, featurehashing, showed that the privacy level depends on identifying groups of keywords in thedocument.
Speckle-Based Optical Waveguide Reservoir Computer for Blind Signal Classification

An opto-electronic reservoir computer based on a light valve, multimode fiber speckle, and a camera combined with back-end signal processing experimentally performs blind signal classification for return-to-zero and non-return-to-zero communications signals at low signal-tonoise ratio.
LibGuides: Remote Services and Resources: Remote Services

Services and Resources Tufts University students, faculty, and staff can use while working from home or from off campus
SPECTRAL ALGORITHM FOR CONTENT-BASED IMAGE RETRIEVAL

Colour images are rich in visual information. The process of searching for the most similar images in large-scale database based on visual features of query image is still a challenge in Content-Based Image Retrieval (CBIR) due to a semantic gap issue. In this paper, we proposed a fusing retrieval method to diminish the gap between high-level and low-level meanings by involving two aspects. The first aspect is increasing the effectiveness of image representation. Hence, data-level fusion features were suggested, a local feature from Discrete Cosine Transform (DCT) and Local Binary Patterns (LBP) in frequency and spatial domains respectively that was applied by a spectral clustering algorithm (graph-based) in addition to a global weighted LBP feature. The second aspect is fusing multiple retrieved similarity measures (scores/evidences) obtained from above global (LBP) and local features (DCTLBP) in terms of score-level fusion. The method is evaluated in WANG standard publically dataset.
Quantum Information on Nonlinearly Coupled Optical Modes

Pursuing room-temperature quantum hardware, we discuss multi-mode optical cavities with nonlinear couplings and focus on material and fabrication requirements for such devices. We demonstrate their use for a number of quantum communication and computation tasks.
LSC-CyFair Library Guides: Online Library Introduction (OLI): Post-OLI Survey

Al things OLI: pre-recorded asynchronous OLI, post-OLI survey, Glossary of Library Terms, and more. If you took the OLI but didn't get a chance to fill out the survey right afterwards, you can take it here.