Reviewerly/exHarmony huggingface dataset:
When to Hold Them, When to Fold Them: Reassessing “Big Deals” in 2020

While cancellations of “Big Deals” at research institutions are making the headlines, small- and medium-sized schools are also addressing the issue of managing their journal packages by cancelling or unbundling major publishers’ journal packages. Although “Big Deals” were advantageous when first acquired, as the years passed, large publishers absorbed more publications annually, which brought higher costs and titles of lower relevance to the library. Each year librarians at Pepperdine University have analyzed cost per use, and each year the cost per use increased on many packages until these increases became unsustainable. Coinciding with this tipping point, alternatives to licensing entire packages emerged or became more viable. Libraries across the country realize that they no longer need to own everything. The authors go into details for each of the publishers’ “Big Deals,” present reasons why they were cancelled or restructured, the alternative solutions implemented, and what the reaction has been.
APLIKASI PERSEDIAAN BARANG MENGGUNAKAN METODE FIFO PADA CV BANDUNG JAYA

Technological progress greatly affects several activities, especially in the field of work, where all work processes have used technology that further speeds up work and saves time. But in managing inventory in CV Bandung Jaya warehouse, the process of entering and leaving the goods is still recorded in the stock book, so many warehouse records and workmanship must be long and irregular, besides there is no coding for old and new items in the warehouse resulting in the warehouse clerk not knowing the items that were first sold were useful for maintaining the quality of the goods. therefore the writer takes the FIFO method (first in first out) on the research on the supply of goods at CV Bandung Jaya, because the FIFO method (first in first out) is the item that first enters, the item will first be sold, the system will make coding specifically on goods in warehouse. In addition, the system will produce more effective and accurate goods management reports.
A Graph-boosted Framework for Adverse Drug Event Detection on Twitter

Detecting adverse drug events from Twitter is expected to reveal unreported side effects, thereby complementing current spontaneous reporting systems. However, existing studies usually only use word embeddings as the input for deep learning models, which ignores the structural information of sentences. In addition, deep learning models usually require a large number of cases for training, but the scale of annotated corpora that can be used for this task is limited. In order to solve the above problems, we propose a graph-boosted framework, that constructs the text into a graph structure. By using pre-trained graph embeddings and word embeddings for model training, our proposed framework provides richer semantic and structural information for prediction. The experimental results show that the proposed method can be used in different deep learning models and bring improvements when using the TwiMed corpus of different scales.
Disaster management of Malaka district government in flood disaster management

Purpose: This study aimed to analyze the disaster management of the Malaka Regency Government in flood disaster management. Research methodology: The research method used in this study is a qualitative research method. The informants in this study were elements of the government as well as elements of society consisting of the Flood Victims Community. The analysis technique in this study uses data analysis developed by Miles and Huberman (2014: 10) as follows; (a) data reduction (b) data display and (c) concluding. Finding: The result of this research is that the Malaka Regency Government's disaster management in flood disaster management has implemented the best management even though it is still not optimal. Limitations: This study's limitation is that this study only discusses the disaster management of the Malaka district government in overcoming the floods that occurred there. Contribution: This research becomes scientific information for public administration and disaster management. Keywords: Management, Disaster, Government
Collision Avoidance of a Kinodynamically Constrained System from Passive Agents

Robot motion planning in dynamic environments is significantly difficult, especially when the future trajectories of dynamic obstacles are only predictable over a short time interval and can change frequently. Moreover, a robot’s kinodynamic constraints make the task more challenging. This paper proposes a novel collision avoidance scheme for navigating a kinodynamically constrained robot among multiple passive agents with partially predictable behavior. For this purpose, this paper presents a new approach that maps collision avoidance and kinodynamic constraints on robot motion as geometrical bounds of its control space. This was achieved by extending the concept of nonlinear velocity obstacles to incorporate the robot’s kinodynamic constraints. The proposed concept of bounded control space was used to design a collision avoidance strategy for a car-like robot by employing a predict-plan-act framework. The results of simulated experiments demonstrate the effectiveness of the proposed algorithm when compared to existing velocity obstacle based approaches.
MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation.

Despite major advances in open-ended text generation, there has been limited progress in designing evaluation metrics for this task. We propose MAUVE -- a metric for open-ended text generation, which directly compares the distribution of machine-generated text to that of human language. MAUVE measures the mean area under the divergence curve for the two distributions, exploring the trade-off between two types of errors: those arising from parts of the human distribution that the model distribution approximates well, and those it does not. We present experiments across two open-ended generation tasks in the web text domain and the story domain, and a variety of decoding algorithms and model sizes. Our results show that evaluation under MAUVE indeed reflects the more natural behavior with respect to model size, compared to prior metrics. MAUVE's ordering of the decoding algorithms also agrees with that of generation perplexity, the most widely used metric in open-ended text generation; however, MAUVE presents a more principled evaluation metric for the task as it considers both model and human text.
Role of Higher Education in Creation of Knowledge Economy in Punjab, Pakistan

Knowledge is working as an engine in achieving sustainable economic development goals for societies who are shifting from labor intensive economy to knowledge based economy like Pakistan. Education works like a backbone in knowledge based economies. Hence, the current research is planned to find out that is the educational institutions of Pakistan are contribution in production of new knowledge or not. Survey was the technique used by researcher for collection of information. Tool for gathering data was questionnaire and sample was selected from six public and private universities of Punjab Pakistan by applying simple random technique while the sample size was comprised of 606 respondents. Both descriptive and inferential statistical techniques were considered to analyze the data. Association found between the efforts made by higher educational institutions by providing access to knowledge, rich infrastructure, funds, incentives, research and development, human capital development, collaboration with industry and creation of knowledge economy.
The Moderat Role Of Knowledge Sharing On The Effect Of Human Capital In Job Empowerment

This study is aimed at identifying the modified role of knowledge sharing in the relationship between human capital and job empowerment at Jadara University.To achieve the aim of the study, the researchers used the descriptive and analytical approach, where they designed a questionnaire that includes the study variables, and distributed it to the university's administrative workers.The appropriate statistical methods were used for its analysis.Accordingly, the study found out that there is a statistically significant effect of knowledge sharing on the relationship between human capital and empowerment at Jadara University .
The Development of Androids Application to Determine the Size of Indonesian Women Clothes Based on Indonesian National Standard (SNI)

Abstract During this time, process to determine the standard size of Indonesian women body is considered less practical. People need to take a look at the list of women clothes size based on Indonesian National Standard (SNI). With this clothing gauge application, it is one of the right solutions, practical and in accordance with the current digital era. This research includes development research that uses the ADDIE model, in this article which is discussed only up to the implementation or trial stage. The trial of developing an Android-based application to determine the size of Indonesian women’s clothing based on the Indonesian National Standards (SNI) will be carried out on 52 students in the Fashion Program of Universitas Negeri Malang. Before the trial or implementation phase, the analysis, design, and development stages are first carried out. The trial results showed 88.38% of applications included in the criteria very feasible. Based on the results of field test results, students think that this application has a presentation that is easily accessible on smartphone, easy to use and understand, practical, has an attractive appearance, is not boring, and makes the spirit to learn.
Real Time Image Classification Based Smart Railway Platform Using Convolutional Neural Network

By supporting smart cities and smart railways, India is heading in a smart direction now-a-days, we have taken a small initiative in this aspect by introducing an innovation in the Indian railway system in the domestic railway platform. The goal for this innovation is to resolve few issues faced by physically disabled individuals and senior citizens while crossing the bridge between the two railway platforms by foot. A updated smart platform is suggested on paper to solve this problem. The Smart Platform on the side of the Crossing Point Platform is interested in the railway tracks. The Smart Platform will open when there is no train arriving at the station. The smart interface can be used for visually disabled people to cross between platforms. On both sides of the road, proximity sensors and the camera unit are configured. If the train hits one sensor, the signals will be transmitted to the camera unit, the image will be captured further by the camera, and the CNN algorithm will decide whether the image captured is some other image of the train. The virtual platform works on the basis of this performance. If the captured image is of a train, the smart platform will then close and allow the trains to go through the tracks, and the smart platform will open automatically between the platforms when the train leaves the second sensor. The train entering the railway stations will be announced and demonstrated by LED signals in a voice system. The proposed system provides the best response without using foot over bridge for the travel of physically disabled people from one platform to another platform.
Organization of pedagogical diagnostics in military universities in the context of education digitalization

This article discusses the most significant problems of the pedagogical diagnostics process in the system of Russian military education at the present stage of its development. At the same time, special attention is paid to the impact that digitalization, which been recorded over the past decades can have on pedagogical diagnostics in military universities. Also the article discuss the possibilities of using in this process such forms of control related to the introduction of informational and telecommunicational technologies, as a computer test tasks Bank, presentations and electronic textbooks, due to their features, also have a certain resource for modernizing the process of pedagogical diagnostics.
The Role of Electronic Means in Enhancing the Intellectual Security among Students at the University of Jordan

The study aims to identify the role of electronic means in enhancing intellectual security among students at the University of Jordan.To achieve the objective of the study, a study instrument is developed, and the study sample consists of (525) male and female students.The results show that the response of the university students in assessing the role of electronic means in enhancing the students' intellectual security is with an arithmetic mean of (3.07), and a standard deviation of (1.128), and this score is considered medium.In light of the results of the study, the researchers recommend employing electronic means in activating the intellectual security among the university education students in Jordan.
Graph Neural Network Acceleration via Matrix Dimension Reduction

Graph Neural Networks (GNNs) have become the de facto method for machine learning on graph data (e.g., social networks, protein structures, code ASTs), but they require significant time and resource to train. One alternative method is Graph Neural Tangent Kernel (GNTK), a kernel method that corresponds to infinitely wide multi-layer GNNs. GNTK's parameters can be solved directly in a single step, avoiding time-consuming gradient descent. Today, GNTK is the state-of-the-art method to achieve high training speed without compromising accuracy. Unfortunately, solving for the kernel and searching for parameters can still take hours to days on real-world graphs. The current computation of GNTK has running time O(N4), where N is the number of nodes in the graph. This prevents GNTK from scaling to datasets that contain large graphs. Theoretically, we present two techniques to speed up GNTK training while preserving the generalization error: (1) We use a novel matrix decoupling method to reduce matrix dimensions during the kernel solving. This allows us to reduce the dominated computation bottleneck term from O(N4) to O(N3). (2) We apply sketching to further reduce the bottleneck term to o(Nω), where ω≈2.373 is the exponent of current matrix multiplication. Experimentally, we demonstrate that our approaches speed up kernel learning by up to 19× on real-world benchmark datasets.
Cyclic Bent Functions and Their Applications in Sequences

Let m be an even positive integer. A Boolean bent function f on F(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> -1)×F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> is called a cyclic bent function if for any a≠b∈F(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> -1) and ε∈F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , f( ax <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ,x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> )+f( bx <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ,x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> +ε) is always bent, where x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ∈F(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> -1),x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ∈F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . Cyclic bent functions look extremely rare. This paper focuses on cyclic bent functions on F(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> -1)×F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and their applications. The first objective of this paper is to establish a link between quadratic cyclic bent functions and a special type of prequasifields, and construct a class of quadratic cyclic bent functions from the Kantor-Williams prequasifields. The second objective is to use cyclic bent functions to construct families of optimal sequences. The results of this paper show that cyclic bent functions have nice applications in several fields such as coding theory, symmetric cryptography, and CDMA communication.
Continual Learning Without Knowing Task Identities: Do Simple Models Work?

Due to the catastrophic forgetting phenomenon of deep neural networks (DNNs), models trained in standard ways tend to forget what it has learned from previous tasks, especially when the new task is sufficiently different from the previous ones. To overcome this issue, various continual learning techniques have been developed in recent years, which, however, often suffer from a substantially increased model complexity and training time. In this paper, we consider whether properly tailored simple models could perform well for continual learning. By proposing a relatively simple method based on Bayesian neural networks and model selection, we can in many cases outperform several state-of-the-art techniques in terms of accuracy, model size, and running time, especially when each mini-batch of data is known to come from the same task of an unknown identity. This leads to interesting observations suggesting that different continual learning techniques may be beneficial for different types of data and task diversity.
Space-time high-resolution data of the potential insolation and solar duration for Montenegro

The assessment of the potential use of renewable energy resources requires reliable and precise data inputs for sustainable energy planning on a regional, national and local scale. In this study, we examine high spatial resolution grids of potential insolation and solar duration in order to determine the location of potential solar power plants in Montenegro. Grids with a 25-m spatial resolution of potential solar radiation and duration were produced based on observational records and publicly available high-resolution digital elevation model provided by the European Environment Agency. These results could be further used for the estimation and selection of a specific location for solar panels. With an average annual potential insolation of 1800 kWh/m? and solar duration of over 2000 h per year for most of its territory, Montenegro is one of the European countries with the highest potential for the development, production, and consumption of solar energy.
VULNERLIZER: Cross-analysis Between Vulnerabilities and Software Libraries

The identification of vulnerabilities is a continuous challenge in software projects.This is due to the evolution of methods that attackers employ as well as the constant updates to the software, which reveal additional issues.As a result, new and innovative approaches for the identification of vulnerable software are needed.In this paper, we present VULNERLIZER, which is a novel framework for cross-analysis between vulnerabilities and software libraries.It uses CVE (Common Vulnerabilities and Exposures) and software library data together with clustering algorithms to generate links between vulnerabilities and libraries.In addition, the training of the model is conducted in order to reevaluate the generated associations.This is achieved by updating the assigned weights.Finally, the approach is evaluated by making the predictions using the CVE data from the test set.The results show a great potential of the approach in predicting future vulnerable libraries based on an initial input CVE entry or a software library.The trained model reaches a prediction accuracy of 75% or higher.
On Algorithms to Find p-ordering

The concept of p-ordering for a prime p was introduced by Manjul Bhargava (in his PhD thesis) to develop a generalized factorial function over an arbitrary subset of integers. This notion of p-ordering provides a representation of polynomials modulo prime powers, and has been used to prove properties of roots sets modulo prime powers. We focus on the complexity of finding a p-ordering given a prime p, an exponent k and a subset of integers modulo $$p^k$$ . Our first algorithm gives a p-ordering for a set of size n in time $$\widetilde{\mathcal {O}}(nk\log p)$$ , where set is considered modulo $$p^k$$ . The subsets modulo $$p^k$$ can be represented concisely using the notion of representative roots (Panayi, PhD Thesis, 1995; Dwivedi et al., ISSAC, 2019); a natural question is, can we find a p-ordering more efficiently given this succinct representation. Our second algorithm achieves precisely that, we give a p-ordering in time $$\widetilde{\mathcal {O}}(d^2k\log p + nk \log p + nd)$$ , where d is the size of the succinct representation and n is the required length of the p-ordering. Another contribution is to compute the structure of roots sets for prime powers $$p^k$$ , when k is small. The number of root sets have been given before (Dearden and Metzger, Eur. J. Comb., 1997; Maulick, J. Comb. Theory, Ser. A, 2001), we explicitly describe all the root sets for $$k\le 4$$ .
Research on UAV Image Matching Algorithm Based on Improved AKAZE Feature and VFC Algorithm

Aiming at the problems of UAV image matching difficulty, time-consuming and low matching efficiency of traditional AKAZE algorithm, an improved algorithm combining AKAZE and LATCH algorithm is proposed. The algorithm first uses the AKAZE algorithm to extract feature points from the image to ensure the accuracy of feature detection, then uses the LATCH algorithm to calculate feature descriptors, and finally uses Vector Field Consensus (VFC) algorithm to accurately match the original image extracted feature points, and eliminate Mismatch points in the rough matching process. Experimental research shows that: comparing and analyzing the feature point extraction time and matching accuracy of image matching, compared with the traditional SIFT algorithm, ORB algorithm, and AKAZE algorithm, the feature point extraction time is increased by about 30%, and the feature matching time is increased by about 22 %, the feature accurate matching effect is the best. The method in this paper has significant matching effect and matching efficiency, and is more suitable for UAV image matching.
RETRACTED: Research on the relationship between new business talents’ ability and its thinking mode in the era of big data

Abstract In the era of big data, the development of “new business” really needs talents who use new ways of thinking to solve economic management problems.Therefore, it is very important to comprehensively analyze the relationship between the ability of new business talents and the way of thinking in the era of big data.Through combing the literature, we have collected and sorted out the thinking mode in the era of big data and the ability requirements of new business for talents. This article selects 9 ability elements, including 4 ways of thinking and 5 talent abilities, to present the structural model of the relationship between the ability of new business talents and their thinking mode in the era of big data. Analyzing the relationship between talent abilities and thinking styles from a new perspective of big data, supplementing and expanding the existing research on new business talent’s abilities, is conducive to the update of training programs, and has certain significance for integrating teaching resources and optimizing curriculum structure.