Reviewerly/exHarmony huggingface dataset:
Sistem Pendukung Keputusan Pemberian Kredit Koperasi Menggunakan Metode Weighted Product

Credit is a major part of financing economic activity. Credit is an important activity for cooperatives, because credit is a source of funds for cooperatives. Prior to commencement of lending activities, a good and thorough analysis is needed of all aspects of credit that can support the credit granting process, in order to prevent credit risks and irregularities, one of which is bad credit. Therefore it is necessary to have a system that can support decision making in providing credit. With the decision support system created, it is hoped that it can help the chairman of the cooperative in analyzing credit and reducing the level of bad credit in the cooperative. In the assessment, a good mechanism is needed, one of which can be done by using the weighted product (WP) method. The weighted product (WP) method uses multiplication to relate the attribute rating, where each attribute rating must first be ranked with the attribute weight in question. From the end result of the research conducted for the provision of credit is whether or not cooperative members deserve credit.
Runtime Analysis of the $$(\mu + 1)$$-EA on the Dynamic BinVal Function

Abstract We study evolutionary algorithms in a dynamic setting, where for each generation a different fitness function is chosen, and selection is performed with respect to the current fitness function. Specifically, we consider Dynamic BinVal, in which the fitness functions for each generation is given by the linear function BinVal, but in each generation the order of bits is randomly permuted. For the $$(1 + 1)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mn>1</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> -EA it was known that there is an efficiency threshold $$c_0$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>c</mml:mi> <mml:mn>0</mml:mn> </mml:msub> </mml:math> for the mutation parameter, at which the runtime switches from quasilinear to exponential. Previous empirical evidence suggested that for larger population size $$\mu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> , the threshold may increase. We prove that this is at least the case in an $$\varepsilon$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ε</mml:mi> </mml:math> -neighborhood around the optimum: the threshold of the $$(\mu + 1)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>μ</mml:mi> <mml:mo>+</mml:mo> <mml:mn>1</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> -EA becomes arbitrarily large if the $$\mu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> is chosen large enough. However, the most surprising result is obtained by a second-order analysis for $$\mu =2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mo>=</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:math> : the threshold in creases with increasing proximity to the optimum. In particular, the hardest region for optimization is not around the optimum.
Video Reconstruction by Spatio-Temporal Fusion of Blurred-Coded Image Pair

Learning-based methods have enabled the recovery of a video sequence from a single motion-blurred image or a single coded exposure image. Recovering video from a single motion-blurred image is a very ill-posed problem and the recovered video usually has many artifacts. In addition to this, the direction of motion is lost and it results in motion ambiguity. However, it has the advantage of fully preserving the information in the static parts of the scene. The traditional coded exposure framework is better-posed but it only samples a fraction of the space-time volume, which is at best 50% of the space-time volume. Here, we propose to use the complementary information present in the fully-exposed (blurred) image along with the coded exposure image to recover a high fidelity video without any motion ambiguity. Our framework consists of a shared encoder followed by an attention module to selectively combine the spatial information from the fully-exposed image with the temporal information from the coded image, which is then super-resolved to recover a non-ambiguous high-quality video. The input to our algorithm is a fully-exposed and coded image pair. Such an acquisition system already exists in the form of a Coded-two-bucket (C2B) camera. We demonstrate that our proposed deep learning approach using blurred-coded image pair produces much better results than those from just a blurred image or just a coded image.
Fisheye lens distortion correction

A new distortion correction algorithm for fisheye lens with equidistant mapping function is considered in the present study. The algorithm is much more data lossless and accurate than such a classical approach like Brown-Conrady model
Autoencoding Improves Pre-trained Word Embeddings

Prior work investigating the geometry of pre-trained word embeddings have shown that word embeddings to be distributed in a narrow cone and by centering and projecting using principal component vectors one can increase the accuracy of a given set of pre-trained word embeddings. However, theoretically, this post-processing step is equivalent to applying a linear autoencoder to minimise the squared l2 reconstruction error. This result contradicts prior work (Mu and Viswanath, 2018) that proposed to remove the top principal components from pre-trained embeddings. We experimentally verify our theoretical claims and show that retaining the top principal components is indeed useful for improving pre-trained word embeddings, without requiring access to additional linguistic resources or labelled data.
LibGuides: Education & Technology: Books

This Library Guide will help students find the resources they need for their education research.
Latte-Mix: Measuring Sentence Semantic Similarity with Latent Categorical Mixtures

Measuring sentence semantic similarity using pre-trained language models such as BERT generally yields unsatisfactory zero-shot performance, and one main reason is ineffective token aggregation methods such as mean pooling. In this paper, we demonstrate under a Bayesian framework that distance between primitive statistics such as the mean of word embeddings are fundamentally flawed for capturing sentence-level semantic similarity. To remedy this issue, we propose to learn a categorical variational autoencoder (VAE) based on off-the-shelf pre-trained language models. We theoretically prove that measuring the distance between the latent categorical mixtures, namely Latte-Mix, can better reflect the true sentence semantic similarity. In addition, our Bayesian framework provides explanations for why models finetuned on labelled sentence pairs have better zero-shot performance. We also empirically demonstrate that these finetuned models could be further improved by Latte-Mix. Our method not only yields the state-of-the-art zero-shot performance on semantic similarity datasets such as STS, but also enjoy the benefits of fast training and having small memory footprints.
ANALISIS KUALIFIKASI DAN KOMPETENSI PEMIMPIN PADA INSTITUSI PERPUSTAKAAN DI INDONESIA

Library in Indonesia is now facing a crisis of leadership where the leader of library is dominated by people who are not librarian. This condition is not in accordance with government regulation number 24, 2014 article 39. There are two assumption arouse regarding this issue, first is on the regulation on election of Head Library and the second one is on the librarian who doesn't have competence to be chosen as Head of Library. Seeing this phenomenon, it is important to study on what qualification and competence needed to be the head of library in Indonesia. Hopefully with this study, we will have the head of library who’s having a good qualification and competence in the field. This study employ literature methodology, which studying literature on qualification and competence of Head of Library. The result is that the qualification for head of library in province and district is at least Bachelor degree of diploma with minimum 5 years of experience in the field of library. While head of national library or university library, the minimum educational background is at least master degree with 10 years of experience in library field. For the point on competence of head of library, there are no exact regulation to regulate this from The National Library Committee. From some concept, writer proposes four basic competence which the candidate should have, which are planning, decision making, communication, and giving motivation.
Kognitionsverber og kontrasten mellem indikativ- og infinitivkomplement

Many Danish cognition verbs take both indicative and infinitive complements. We examine what the contrast between the two complement types codes. The literature offers two answers. One is that the contrast has to do with coreferentiality: if the cognition verb’s primary argument is coreferential with the primary argument of the complement, the complement tends to be infinitive; if not, the complement must be indicative. The other answer concerns the contrast between propositions and states-of-affairs: the indicative complement designates a proposition, the infinitive complement a state-of-affairs. Corpus studies support both answers. They also support an analysis of indicatives as proposition markers. But infinitives cannot – straightforwardly – be analysed as state-of-affairs markers.
Log Script Activity

If you don’t know what your code is doing, how are you supposed to troubleshoot it? How are you supposed to optimize it? To show what it changed in an environment? Log everything!
Develop Health Monitoring and Management System to Track Health Condition and Nutrient Balance for School Students

Health Monitoring and Management System (HMMS) is an emerging technology for decades. Researchers are working on this field to track health conditions for different users. Researchers emphasize tracking health conditions from an early stage to the human body. Therefore, different research works have been conducted to establish HMMS in schools. Researchers propose different frameworks and technologies for their HMMS to check student's health condition. In this paper, we introduce a complete and scalable HMMS to track health conditions and nutrient balance for students from primary school. We define procedures step by step to establish a robust HMMS where big data methodologies can be used for further prediction for diseases.
Estimation and validation of electric power output from a fixed-type floating photovoltaic system

&amp;lt;p&amp;gt;An accurate estimation of electric power production (EPP) is a crucial first step to design a floating photovoltaics (PV) project. This study estimates the EPP of a floating PV system and validates the results by comparing with the actual EPP observed at the Hapcheon Dam, Korea. Typical meteorological year data and system design parameters were entered into System Advisor Model (SAM) software to estimate the hourly and monthly EPPs. Three-year average observed EPPs (2012, 2013, and 2015) were used as reference values for the validation. The results showed the seasonal EPPs were the highest in spring and the lowest in winter. The monthly estimated EPPs were lower than the monthly observed EPPs. These results are ascribed to the fact the SAM was unable to consider the natural cooling effect of the water environment on the PV module. The error results showed it was possible to estimate the monthly EPPs with an error of less than 15% simply by simulation. However, it may possible to estimate the monthly EPPs with an error of approximately 9% when considering empirical results: The floating PV efficiency was approximately 1.1 times (110%) the overland PV efficiency. This indicates that the approach of using empirical results can provide reliable monthly estimation of EPP in feasibility assessment stage of floating PV projects.&amp;lt;/p&amp;gt;
Online Structured Meta-learning

Learning quickly is of great importance for machine intelligence deployed in online platforms. With the capability of transferring knowledge from learned tasks, meta-learning has shown its effectiveness in online scenarios by continuously updating the model with the learned prior. However, current online meta-learning algorithms are limited to learn a globally-shared meta-learner, which may lead to sub-optimal results when the tasks contain heterogeneous information that are distinct by nature and difficult to share. We overcome this limitation by proposing an online structured meta-learning (OSML) framework. Inspired by the knowledge organization of human and hierarchical feature representation, OSML explicitly disentangles the meta-learner as a meta-hierarchical graph with different knowledge blocks. When a new task is encountered, it constructs a meta-knowledge pathway by either utilizing the most relevant knowledge blocks or exploring new blocks. Through the meta-knowledge pathway, the model is able to quickly adapt to the new task. In addition, new knowledge is further incorporated into the selected blocks. Experiments on three datasets demonstrate the effectiveness and interpretability of our proposed framework in the context of both homogeneous and heterogeneous tasks.
Assessment of Heavy Metal Pollution of the Peter the Great Bay (North-West Pacific Region) Using Brown Algae

According to the content of heavy metals Fe, Mn, Cu, Zn, Pb, Cd and Ni in brown algae Sargassum miyabei from the Peter the Great Bay of the Sea of Japan, geochemical factors were calculated.The algae geochemical anomaly index (I GA ) characterizes the degree of excess of the background concentrations of metals.The heavy metal pollution factor (F p ) is used to estimate the degree of pollution of the marine environment with heavy metals.The Peter the Great Bay has a low level of heavy metal pollution, but some parts of second-order bays, such as Amurskii Bay, Ussuriiskii Bay and Vostok Bay, have a moderate degree of pollution.The high pollution level was registed on the western coast of the Ussuriiskii Bay near the Vladivostok city landfill.Thirty percent of sampling stations were noted to have higher threshold levels of metals in the algae.These areas need to be monitored to assess their environmental status and measures should be applied to reduce the impact on the environment.
Big Data and Other Big Changes

The chapter describes developments in campaign technology, focusing on advances in microtargeting capabilities and explaining why the presidential election in 2000 represents a watershed moment in this process.
Use of Altmetrics to Analyze ScholarWorks in Natural Resource Management

Digital preservation of library materials has increased the need for methods to access the documents and contents maintained in digital archives. The use of altmetrics to quantify the impact of scholarly works, including PlumX, is increasing readership by listing articles in reference services. The outreach from the digital repository ScholarWorks at Stephen F. Austin State University (SFASU) highlights the impact within the natural resources community from Digital Commons, Forest Sciences Commons; and from the Natural Products Chemistry and Pharmacognosy Commons. The use of PlumX altmetrics was examined to evaluate usage, impact, and digital audience downloads for the Arthur Temple College of Forestry and Agriculture (ATCOFA) at SFASU.
A Qualitative Analysis of Haptic Feedback in Music Focused Exercises

We present the findings of a pilot-study that analysed the role of haptic feedback in a musical context. To examine the role of haptics in Digital Musical Instrument (DMI) design an experiment was formulated to measure the users' perception of device usability across four separate feedback stages: fully haptic (force and tactile combined), constant force only, vibrotactile only, and no feedback. The study was piloted over extended periods with the intention of exploring the application and integration of DMIs in real-world musical contexts. Applying a music orientated analysis of this type enabled the investigative process to not only take place over a comprehensive period, but allowed for the exploration of DMI integration in everyday compositional practices. As with any investigation that involves creativity, it was important that the participants did not feel rushed or restricted. That is, they were given sufficient time to explore and assess the different feedback types without constraint. This provided an accurate and representational set of qualitative data for validating the participants' experience with the different feedback types they were presented with.
LibGuides: National Voter Registration Day: Home

Links and resources that promote National Voter Registration Day, voting at Alkek Library, and general voter literacy.
Improving pronunciation assessment via ordinal regression with anchored reference samples

Sentence level pronunciation assessment is important for Computer Assisted Language Learning (CALL). Traditional speech pronunciation assessment, based on the Goodness of Pronunciation (GOP) algorithm, has some weakness in assessing a speech utterance: 1) Phoneme GOP scores cannot be easily translated into a sentence score with a simple average for effective assessment; 2) The rank ordering information has not been well exploited in GOP scoring for delivering a robust assessment and correlate well with a human rater's evaluations. In this paper, we propose two new statistical features, average GOP (aGOP) and confusion GOP (cGOP) and use them to train a binary classifier in Ordinal Regression with Anchored Reference Samples (ORARS). When the proposed approach is tested on Microsoft mTutor ESL Dataset, a relative improvement of Pearson correlation coefficient of 26.9% is obtained over the conventional GOP-based one. The performance is at a human-parity level or better than human raters.
AI-lead Court Debate Case Investigation

The multi-role judicial debate composed of the plaintiff, defendant, and judge is an important part of the judicial trial. Different from other types of dialogue, questions are raised by the judge, The plaintiff, plaintiff's agent defendant, and defendant's agent would be to debating so that the trial can proceed in an orderly manner. Question generation is an important task in Natural Language Generation. In the judicial trial, it can help the judge raise efficient questions so that the judge has a clearer understanding of the case. In this work, we propose an innovative end-to-end question generation model-Trial Brain Model (TBM) to build a Trial Brain, it can generate the questions the judge wants to ask through the historical dialogue between the plaintiff and the defendant. Unlike prior efforts in natural language generation, our model can learn the judge's questioning intention through predefined knowledge. We do experiments on real-world datasets, the experimental results show that our model can provide a more accurate question in the multi-role court debate scene.
Pengembangan Aplikasi Blended Learning Di Sekolah Saat Pandemi Covid19 (Corona)

This research aims to develop the Blended Learning application because of the COVID19 pandemic that is hitting the world. The application is built in such a way as to simplify the process of use in school learning by using the Research and Development (RB 2) The practicality of the Blended Learning application based on user responses, namely teachers and students, was stated to be very practical. Based on the findings of this study, it is concluded that the Blended Learning application is very valid and very practical.
School Management’s Perception of Corporate Social Responsibility (CSR): An Exploratory Study

Background: In recent years, the importance of school as a stake-holder in CSR activities is gaining recognition. Companies channel financial and human resources into developing schools. School Development and Monitoring Committee (SDMC) plays an important part in the management of Primary schools in Karnataka and as such should have a role in CSR activities. Purpose: This exploratory study attempted to answer the following questions- (1) How aware are SDMC members of CSR and its role in schools (2) what is their perception of CSR in their schools? (3) Do rural and urban SDMC members differ in their perception of CSR Methods: Sample consisted of SDMC members from 50 rural and 50 urban Government run primary schools in Bangalore Educational districts. 100 SDMC members, one from each school, were interviewed using a semi structured information schedule developed for this study. Results: Management is not very clear about the nature of CSR support . However, 75% of them perceive CSR as beneficial to their schools. Rural subjects have a more favourable perception of CSR impact and they differ significantly from urban counterparts in rating ‘ how CSR has benefited students’ (t = 2.052).Conclusions: SDMC members do not clearly distinguish between support provided under CSR and support received from other sources. Overall, CSR is seen as beneficial to school by supplementing government support and helping the management. Rural schools seem to benefit more from CSR support. Though SDMC is supposed to monitor the developmental activities of the school, they are not often consulted by companies about the requirements for the school. Involving SDMC in planning, executing and monitoring would enhance the efficacy of CSR programmes.
CRYPTANALYSIS OF AN AUTHENTICATION PROTOCOL FOR DIGITAL RIGHTS MANAGEMENT SYSTEM

The latest progress of communication technology and low-power devices has led to in all kinds of resources environment to provide digital content services, such as smart home and the Internet of things . However, digital content is easily replicated and distributed through open channels. Therefore, authentication is becoming more and more important for digital rights management (DRM) systems to provide security services to authorized users .In 2019, SungJin Yu et al. proposed a l ightweight three-factor authentication protocol for digital rights management system .This paper introduces the research background of the identity authentication scheme, and reviews the authentication protocol of Sungjin Yu et al. from the perspective of the registration phase and the login authentication phase .Then,through the cryptanalysis, We here prove that the DRM system protocol of SungJin Yu et al. is unsafe, and provide two attack schemes, namely, privileged insider impersonating a legitimate user and privileged insider impersonating a legitimate license server.