Reviewerly/exHarmony huggingface dataset:
Knowledge Management Process Model using IHS based on Detecting Process with Less Energy Consumption

In this work, the major focus is on the improvement of management process, which is to reliably form asolution process of optimal. The imbalanced data managing process is maintained with efficient process of proposed system (IHS – Improved Hybrid Sampling) with less energy consumption. In this study, we present and suggest a comprehensive and phased knowledge management process framework that integrates and streamlines varied and multiple processes in a phased manner to collect analyze and manage knowledge. This KM process framework will help to identify the information needs and provide decision makers with useful step-by-step recommendations and guidelines based upon the integrated knowledge and past experience. The performance shows the improvement of the balancing the data and energy consumption for process in an efficient manner.
EXAMINING THE RELATIONSHIPS BETWEEN BITCOIN, GOLD AND FINANCIAL ASSETS

ABSTRACT Cryptocurrencies have obtained substantial interest from bankers, investors, media, social media, and regulators. Bitcoin is a cryptocurrency and has the largest market capitalization. This paper investigates the return and volatility spillovers from S&P 500 and ADRs to Bitcoin and gold. The results of this paper indicate that there are no significant price and volatility spillovers from Bitcoin and gold to S&P 500. Results also suggest no evidence of significant price and volatility spillovers from Bitcoin and gold to ADRs. This is in line with data compiled by VenEck (2021) that concludes that there is no patterns of movement between Bitcoin and other markets such as S&P 500, gold etc. Furthermore, we also see price spillovers from S&P 500 and ADRs to Bitcoin and volatility spillovers from S&P 500 and ADRs to gold. Keywords Bitcoin, Gold, American Depositary Receipts, Stocks
ANALISIS SISTEM INFORMASI AKUNTANSI PENGGAJIANDAN PENGUPAHAN PADA KOPERASI TKBM KARYA KALTIM BONTANG

Abstract&#x0D; The accounting system is a key component that can support business activities. The accounting system consists of several subsystems, one of which is the payroll and wages information system. The payroll information system plays an important role in the company and is directly connected to the workers employed in the company or organization.&#x0D; Payroll and wage accounting information system is an internal control tool to minimize fraudulent actions that may occur and harm the company. The purpose of this research is to provide an overview of whether the payroll accounting system implemented at the TKBM Karya Kaltim Bontang Cooperative is effective.&#x0D; &#x0D; &#x0D; Keywords :SIA, SPP, SIAPP
Optical Convolutional Neural Network with Atomic Non-linearity

Convolutional neural networks (CNNs) have become an indispensable part of machine learning due to their successful application on image-based machine learning problems. However, the compute resources required to train and infer such CNNs scale quadratically with problem size, thus expense of time and energy is large. Unlike electrons, photons can be used to naturally realize massive and parallel interconnections [1] , achieve clock speeds in the GHz range and most importantly the computational cost for optical convolutions scales only linear with problem size. Thus, optical computing is getting ever more attractive [2] .
Kemanfaatan Perpustakaan dalam Pembelajaran dan Penelitian Mahasiswa IPB serta Strategi Peningkatannya

Facing the disruptive era IPB Library needs to anticipate various changes by conducting self-evaluation through assessing the impact of their existence for students. Therefore, this study aims: (1) Knowing the relationship between the frequency of student visits to the IPB Library and the GPA; (2) Knowing the relationship between the number of IPB library books borrowed by students and the GPA; (3) Knowing the benefits of the IPB Library in supporting student learning and research processes; (4) Knowing the role of IPB librarians in supporting the learning and research processes of their students; (5) Formulate strategies for the IPB Library to increase its benefits for the learning and research processes of its students.          This research is a quantitative study, using a correlation test to see the relationship between the frequency of student visits to the IPB Library and the number of the IPB Library books borrowed by the students with the GPA. This study also used a survey method with a questionnaire accompanied by interviews with three IPB lecturers.          The results showed that there was no correlation between the frequency of student visits to the library and the number of library books borrowed on the student's GPA. However, students' perceptions regarding the support of the IPB Library on their learning and research are very good, the average percentage of respondents who agree on the benefits of the library in their learning and research processes is above 90%. Respondents' perception of librarian support in helping students learn is very good, but librarian support for student research is considered lacking.          Strategies to increase the benefits of the library and librarians on student learning and research process need to be adjusted to the behavior of the millennial generation. Therefore, it is recommended that the IPB Library immediately implement the concepts based on industrial revolution 4.0. IPB librarians should be improved their competence related to information literacy skills and mastery of information and communication technology.
Results Of Information Competence Formation Of Students Of Pedagogical Directions

The formation of information competence is an urgent task in the modern education system. The professionalism of the future teacher includes various competencies, including information. Moreover, information competence is becoming one of the priorities of modern higher education. The practical result of the research carried out at a pedagogical university is a model of the formation of information competence of students in pedagogical areas of training. The model is a system of general requirements for the formation of information competence in a pedagogical higher educational institution. The article lists methodological recommendations that illustrate the constituent elements of the model. They are the result of lessons learned from practical activity and can be useful for teachers of natural science and engineering disciplines who solve the problems of forming information competence in the course of their educational activities. The analysis of the results of the implementation of the developed model shows its effectiveness. The comparison of indicators of the formation of information competence over the last three academic years allows us to conclude that the organization of educational activities in accordance with the model gives stable high results.
A Study on Security Event Detection in ESM Using Big Data and Deep Learning

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.
Image Enhancement Using Gamma and HE For the Face Detection System In Real-Time By Viola_Jones Algorithm

The process of detecting and recognition faces in real-time play an important role in many systems. Face detection is the first stage of face recognition systems. The poor lighting conditions effect on the results, significantly, in the case of using the Viola algorithm to detect faces in real-time, so image processing is a very important step in improving the accuracy Viola algorithm. Most systems use a single technique that handles all images, without distinguishing between the images in which the viola can detect the face or not, which costs unnecessary effort to the system, In addition to, the difference in the type of damage to the image that needs to be process varies according to the type of problem. In this paper, a simple and fast method presented based on studying the histogram of the image that suffers from a problem and tends to be dark or bright. Then the system uses the gamma only, or it uses both gamma and histogram equalization (HE) to processing the image with variables that differ according to the type of problem that it caucused by the lighting of the image. In this study, three types of datasets are used. Each type contains images that are taken in different lighting conditions. The final results proved the increase in the ability of the Viola algorithm to detect faces in easy and the accuracy reached 95.8%.
Feature-transferable Pyramid Network for Cross-scale Object Detection in SAR Images

Multiscale object detection in Synthetic Aperture Radar (SAR) images can locate and recognize key objects in large-scene SAR images, and it is one of the key technologies in SAR image interpretation. However, for the simultaneous detection of SAR objects with large size differences, that is, cross-scale object detection, existing object detection methods are difficult to extract the features of cross-scale objects, and also difficult to realize cross-scale object simultaneous detection. In this study, we propose a multiscale object detection method based on the Feature-Transferable Pyramid Network (FTPN) for SAR images. In the feature extraction stage, the feature migration method is used to obtain an effective mosaic of the feature images of each layer and extract feature images with different scales. Simultaneously, the void convolution method is used to increase the receptive field of feature extraction and aid the network in extracting large object features. These steps can effectively preserve the features of objects of different sizes, to realize the simultaneous detection of cross-scale objects in SAR images. The experiments based on the GaoFen-3 SAR dataset, SAR Ship Detection Dataset (SSDD), and high-resolution SSDD-2.0 show that the proposed method can detect cross-scale objects, such as airports and ships in SAR images, and the mean Average Precision (mAP) can reach 96.5% on the existing dataset, which is 8.1% higher than that of the characteristic pyramid network algorithm. Moreover, the overall performance of the proposed method is better than that of the latest YOLOv4 and other object detection algorithms.
Trabajo del docente de matemáticas en un Entorno Virtual de Aprendizaje

The disease known as Covid-19, among other consequences, slowed down face-to-face educational activities, which produced the need to migrate to a virtual learning environment and a challenge for math teachers to this mode of work, most of them were accustomed to carrying out teaching activities only in a classroom setting, and to ensuring that students can show whether or not they have understood how to solve the problems that arise. With the purpose of knowing the experiences that teachers of mathematics have had with CETis and CBTis in the state of Colima, their impressions regarding adapting their teaching activities from a classroom environment to a virtual environment were analyzed. In general, the information collected through an e-survey made it possible to identify the level of willingness to change the working environment, as well as some needs teacher professional development.
General Databases Data Curation Primer

This work was created as part of the “Specialized Data Curation” Workshop #3 held at Washington University in St. Louis, MO on November 5-6, 2019.
BabelCalib: A Universal Approach to Calibrating Central Cameras

Existing calibration methods occasionally fail for large field-of-view cameras due to the non-linearity of the underlying problem and the lack of good initial values for all parameters of the used camera model. This might occur because a simpler projection model is assumed in an initial step, or a poor initial guess for the internal parameters is pre-defined. A lot of the difficulties of general camera calibration lie in the use of a forward projection model. We side-step these challenges by first proposing a solver to calibrate the parameters in terms of a back-projection model and then regress the parameters for a target forward model. These steps are incorporated in a robust estimation framework to cope with outlying detections. Extensive experiments demonstrate that our approach is very reliable and returns the most accurate calibration parameters as measured on the downstream task of absolute pose estimation on test sets. The code is released at this https URL.
APPLICATION OF NONLINEAR DYNAMIC EXPECTATION AND STOCHASTIC DIFFERENTIAL EQUATION IN VALUATION AND FINANCING RISK MEASUREMENT OF TECHNOLOGY-BASED SMALL AND MEDIUM-SIZED ENTERPRISES

The purpose of this paper is to determine the assets of Small and Medium-sized Enterprises (SMEs), reasonably value this type of enterprise, and effectively use available data to measure their financing risks. Based on the previous research, the nonlinear expectation and the stochastic differential equation are adopted to combine the enterprise’s financing risk with the psychological factors of the consumer market to construct different risk measurement models according to the current technology-based enterprise’s pricing and financing problems. Besides, the nonparametric estimation method is applied to the nonlinear expectation, which improves the application of the model in finance. The effectiveness of the model in technology-based SMEs pricing and financing risk measurement evaluation is verified using the instance data of technology-based SMEs. Results demonstrate that the traditional pricing models for technology-based SMEs need to ensure that every investor is rational. Although the price of the enterprise cannot be effectively predicted, the nonlinear expectation and stochastic differential equation can reflect the changes in the value of the enterprises and the impacts of investors’ psychological factors on the financing effect of the enterprises. Different risk measurement models constructed can effectively price and measure technology-based SMEs. The non-parametric estimation method can effectively improve the accuracy of the model prediction. The results can provide some research ideas and practical value for the market valuation and financing risk assessment of technology-based SMEs.
PEMANFAATAN INFORMASI PERPUSTAKAAN OLEH PUSTAKAWAN

The oldest and most well-established information professionals are librarians, archivists, and museum curators. If you want to expand, the information profession includes librarians, archivists, those who practice information science, information management, librarians with information development, record management, and documentation.  In a broader definition, information includes visual objects and three-dimensional objects that are preserved because of the quality of the information, so the information profession includes curators in museums. So in this case the information officer handling external publicity and communication of a cooperative body is also included in the information profession.
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition

Multi-modal learning, which focuses on utilizing various modalities to improve the performance of a model, is widely used in video recognition. While traditional multi-modal learning offers excellent recognition results, its computational expense limits its impact for many real-world applications. In this paper, we propose an adaptive multi-modal learning framework, called AdaMML, that selects on-the-fly the optimal modalities for each segment conditioned on the input for efficient video recognition. Specifically, given a video segment, a multi-modal policy network is used to decide what modalities should be used for processing by the recognition model, with the goal of improving both accuracy and efficiency. We efficiently train the policy network jointly with the recognition model using standard back-propagation. Extensive experiments on four challenging diverse datasets demonstrate that our proposed adaptive approach yields 35%-55% reduction in computation when compared to the traditional baseline that simply uses all the modalities irrespective of the input, while also achieving consistent improvements in accuracy over the state-of-the-art methods.
Pengaruh Penerapan Media Pembelajaran Pop-Up Book Terhadap Motivasi Dan Hasil Belajar IPA Peserta Didik Kelas V SDN 3 Kawo Tahun Ajaran 2020/2021

This study aims to determine the effect of the application of pop-up book learning media on the motivation and learning outcomes of fifth grade students at SDN 3 KAWO in the 2020/2021 academic year. The population in this study were all students of class V at SDN 3 KAWO, while the samples were students of class VA as the experimental class and students of class VB as the control class. Data analysis begins with a normality test using the One-Sample Kolmogrov Smirnov formula with a significance level of 5% (0.05) and continues with a homogeneity test further testing the research hypothesis and further testing with a gain-score test. Then the motivational data and learning outcomes were analyzed by Independent t-test. Samples Test to determine the research hypothesis, the results of data analysis obtained a t-count value of 3,241 while the t-table at a significance level of 5% was 2,048 so that the t-count value&gt; t-table, which means that Ha, which states there is an effect of application pop-up book learning media on science learning motivation of fifth grade students at SDN 3 KAWO in the 2020/2021 academic year, was accepted and H0 rejected. And the obtained t-count is 2.209 while the t-table at the 5% significance level is 2.048 so that the t-count value is &gt;t-table, which means that Ha which states that there is an effect of the application of pop-up book learning media on participants' science learning outcomes fifth grade students of SDN 3 KAWO for the academic year 2020/2021, were accepted and H0 was rejected. Then a follow-up test was carried out using gain-score test, the value of learning motivation is 0.403 which is included in the medium category, while the learning outcomes of 0.576 are included in the medium category.
Long-Term Anticipation of Activities with Cycle Consistency

With the success of deep learning methods in analyzing activities in videos, more attention has recently been focused towards anticipating future activities. However, most of the work on anticipation either analyzes a partially observed activity or predicts the next action class. Recently, new approaches have been proposed to extend the prediction horizon up to several minutes in the future and that anticipate a sequence of future activities including their durations. While these works decouple the semantic interpretation of the observed sequence from the anticipation task, we propose a framework for anticipating future activities directly from the features of the observed frames and train it in an end-to-end fashion. Furthermore, we introduce a cycle consistency loss over time by predicting the past activities given the predicted future. Our framework achieves state-of-the-art results on two datasets: the Breakfast dataset and 50Salads.
Desarrollo de habilidades metacognitivas a través del recurso tecnológico ‘‘software libre de Scratch’’

Underlying this experience is the development of metacognitive skills through the free soft- ware, Scratch, in the context of the COVID-19 pandemic. To begin, reference is made to the elaboration of a regional teaching proposal for an approach to the subject of Mathematics II of the second semester of high school, based on the guidelines given by the federal and state authorities of Mexico, in relation to the approach of alternative solutions to real or hypothetical situations raised in the Study Program that guide the New Educational Model for Compulsory Education in Mexico. The pedagogical application of of Scratch is then described specifying the necessary components for the development of metacognitive skills in students which leads to the elaboration of the contextualized problem for the execution of the technological resource as a didactic sequence, designed according to the different distance educational scenarios presented by experienced students. Finally, the conclusions and proposals emanating from the distance educational experience during the pandemic are presented as a transcendent conjuncture for mathematics teachers to improve and offer different ways of teaching mathematics in an enjoyable way.
Key Security Problems - Research Challenges Regarding Cloud Computing

On request or on pay in step with utilization of helpful asset comprising of: system, stockpiling and server these all offices are outfitted by utilizing distributed computing through web is known as distributed computing. Regardless of the way that, distributed computing is encouraging the realities time venture, the innovative work on this territory is yet to be fine. We have commitment on this paper is a confounded review that have practical experience in distributed computing idea and most developed research issues. This paper manages a higher mastery of the distributed computing and distinguishes basic examinations inconveniences on this expanding region of PC mechanical expertise. Stage 1 incorporates the presentation, inside the stage 2, we offer a layout of distributed computing, stage three comprises of the security design and stage four will mindfulness on the exploration issues and wellbeing inconvenience. We finish the paper on section five together with references.
The solace of quantum

Governments see quantum computers as something to both fear and revere when it comes to security, reports Matthew Sparkes
Getting Started with Voice Assistant

According to a report, by 2024 there will be around 8.4 billion units of voice assistants—a number higher than the world’s population. Voice assistants are becoming more popular and a key component of the smart device industry as we head toward an era of AI- and IoT-based systems. As the industry grows and its technology becomes more advanced, companies are increasingly searching for bigger and better uses of “smart” technology. People can now communicate with their connected smart devices in much the same way that they can with their smartphones. Nowadays, voice assistants are coming preinstalled in smartphones and laptops.